{"id":676431,"date":"2020-07-18T10:54:37","date_gmt":"2020-07-18T17:54:37","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/?post_type=msr-event&#038;p=676431"},"modified":"2025-08-06T11:52:34","modified_gmt":"2025-08-06T18:52:34","slug":"kdd-2020-truefact-workshop-making-a-credible-web-for-tomorrow","status":"publish","type":"msr-event","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/event\/kdd-2020-truefact-workshop-making-a-credible-web-for-tomorrow\/","title":{"rendered":"KDD 2020 TrueFact Workshop: Making a Credible Web for Tomorrow"},"content":{"rendered":"\n\n<p>The second international <em>TrueFact Workshop: Making a Credible Web for Tomorrow<\/em> will provide a forum where researchers and practitioners from academia, government and industry can share insights and identify new challenges and opportunities in resolving conflicts, fact-checking and ascertaining credibility of claims. The workshop will be held in San Diego, CA on August 24, 2020 in conjunction with the <em>ACM SIGKDD 2020<\/em>.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter\" src=\"https:\/\/www.nsf.gov\/images\/logos\/NSF_4-Color_bitmap_Logo.png\" width=\"121\" height=\"122\" \/><span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<p>In recent times, the explosion of information from a variety of sources and cutting edge techniques such as Deepfake have made it increasingly important to check the credibility and reliability of the data. Large volumes of data generated from diverse information channels like social media, online news outlets, and crowd-sourcing contribute valuable knowledge; however, this comes with additional challenges to ascertain the credibility of user-generated and machine-generated information, resolving conflicts among heterogeneous data sources, identifying misinformation, rumors and bias, etc.<\/p>\n<ul>\n<li>Given diverse information about an object (e.g., a natural language claim text, an entity, structured triples and social network context) from heterogeneous and multi-modal sources, how do we identify high quality and trustworthy information and information sources?<\/li>\n<li>How can we leverage Knowledge Bases and external evidence sources from the Web for reasoning, explaining, and validating claims?<\/li>\n<li>How can we generate human-interpretable explanations for the models\u2019 verdict How can we design robust fake information (e.g., reviews and news) detection mechanisms to withstand adversarial generation strategies, as spammers and content generators are co-evolving with the advanced detectors?<\/li>\n<\/ul>\n<p>In order to answer these questions, this workshop encourages submissions to focus on big ideas \u2013 for resolving conflicts, fact-checking, ascertaining credibility of claims, explaining predictions from deep fake detectors, developing robust adversarial mechanisms for fake content detection, manipulation and safeguards, and making detection algorithms fair and unbiased to the involved participants \u2013 in heterogeneous and multi-modal sources of information including texts, images, videos, relational data, social networks and knowledge graphs.<span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<ul>\n<li><a href=\"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/people\/submukhe\/\">Subhabrata Mukherjee (Microsoft Research)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.cs.iastate.edu\/people\/qi-li\">Qi Li (UIUC)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"http:\/\/www.cse.lehigh.edu\/~sxie\/\">Sihong Xie (Lehigh University)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"http:\/\/hanj.cs.illinois.edu\/\">Jiawei Han (UIUC)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.cs.uic.edu\/~psyu\/\">Philip S. Yu (UIC)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/cse.buffalo.edu\/~jing\/\">Jing Gao (SUNY Buffalo)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<\/ul>\n<p><span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<p>Our workshop on truth discovery and fact-checking is motivated by the need for new research, tools and techniques to advance the field with the following focus areas:<\/p>\n<ul>\n<li>Data heterogeneity, multi-modality, novel applications and data sources related to truth discovery, fact-checking, and rumor detection<\/li>\n<li>Explore tools and methods that can generate human-interpretable explanations as opposed to black box methods, as transparency and lack of explanation remain a concern for industry to readily deploy these techniques in practise<\/li>\n<li>Security and robustness of fake content detection under a known or unknown environment where spammers can learn and then commit arbitrary attack strategy to poison the data or evade the detectors<\/li>\n<\/ul>\n<p><em>In addition to the regular workshop, we will also host a data challenge track with two shared tasks for fake review detection in an adversarial framework and fake news detection (details will be announced soon).<\/em><\/p>\n<p>The second workshop on\u00a0<em>Truth Discovery and Fact Checking: Making a Credible Web for Tomorrow<\/em>\u00a0will provide a forum where researchers and practitioners from academia, government and industry can share insights and identify new challenges and opportunities in resolving conflicts, fact-checking and ascertaining credibility of claims. The workshop will be held in San Diego, CA on August 23, 2020 in conjunction with the\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.kdd.org\/kdd2020\/\">ACM SIGKDD 2020<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>.<\/p>\n<p><strong>In view of the recent COVID-19 outbreak, the format of the workshop (in-person, virtual, or both) will be in accordance to the SIGKDD 2020 main conference format<\/strong>.<\/p>\n<h2 id=\"topics-of-interest-include-but-are-not-limited-to\">Topics of interest include, but are not limited to:<\/h2>\n<p>Topics of interest include, but are not limited to:<\/p>\n<ul>\n<li>Truth finding and discovery<\/li>\n<li>Fact-checking, rumor, and misinformation<\/li>\n<li>Credibility analysis and spam detection<\/li>\n<li>Fake reviews and reviewers<\/li>\n<li>Leveraging knowledge bases for reasoning, validating and explaining contentious claims<\/li>\n<li>Transparency, fairness, bias, privacy and ethics of information systems<\/li>\n<li>Emerging applications, novel data sources, and case studies<\/li>\n<li>Explainable and interpretable models<\/li>\n<li>Robustness detection under adversarial and unknown data poisoning and evasion attacks.<\/li>\n<li>Heterogeneous and multi-modal information including relational data, natural language text, search logs, images, video, etc.<\/li>\n<\/ul>\n<h2 id=\"submission-guidelines\">Submission Guidelines<\/h2>\n<p>We invite submissions for original research papers both theory and application-oriented as well as submissions from the research track and applied data science track of the main KDD conference. We encourage the participants to submit papers on novel datasets and release them to advance the field. Papers must be submitted in PDF according to the ACM Proceedings Template\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.acm.org\/publications\/proceedings-template\">https:\/\/www.acm.org\/publications\/proceedings-template<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>\u00a0in a single-blind format (including author names and affiliations). We welcome both long papers (maximum length of 9 pages) and short papers (maximum length of 5 pages). The accepted papers will be published on the workshop\u2019s website, and will not be considered archival for resubmission purposes. Please submit your papers at the EasyChair submission link\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/easychair.org\/conferences\/?conf=truefact2020\">https:\/\/easychair.org\/conferences\/?conf=truefact2020<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>.<\/p>\n<p>We also invite participants for TrueFact 2020 Shared Tasks. Instructions for participation and awards will be announced soon!<\/p>\n<h2 id=\"important-dates\">Important Dates<\/h2>\n<p>All deadlines are 11:59 PM Pacific Standard Time<\/p>\n<p>Workshop paper submissions:\u00a0<del>May 20<\/del>\u00a0June 15, 2020<\/p>\n<p>Workshop paper notifications:\u00a0<del>June 15<\/del>\u00a0July 15, 2020<\/p>\n<p>Workshop date: August 24, 2020<span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<h2 id=\"shared-task-1-adversarial-attacks-against-review-spam-detectors\">Shared Task 1 (Adversarial attacks against review spam detectors).<\/h2>\n<ul>\n<li>The competition is hosted on Kaggle:\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.kaggle.com\/c\/adversarial-attacks-against-spam-detectors\">https:\/\/www.kaggle.com\/c\/adversarial-attacks-against-spam-detectors<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li>Prize: first-place $300, runner-up $150<\/li>\n<li>Please email Sihong Xie\u00a0<a href=\"mailto:xiesihong1@gmail.com\">xiesihong1@gmail.com<\/a>\u00a0for any questions.<\/li>\n<\/ul>\n<h2 id=\"shared-task-2-fake-news-detection\">Shared Task 2 (Fake news detection).<\/h2>\n<ul>\n<li>The competition is hosted on Kaggle:\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.kaggle.com\/c\/fakenewskdd2020\/overview\">https:\/\/www.kaggle.com\/c\/fakenewskdd2020\/overview<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li>Prize: first-place $300, runner-up $150<\/li>\n<li>Please email Subhabrata Mukherjee\u00a0<a href=\"mailto:subhabrata.mukherjee@microsoft.com\">subhabrata.mukherjee@microsoft.com<\/a>\u00a0for any questions.<\/li>\n<\/ul>\n<p><span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<p>We are releasing the pre-recorded video presentations for all the talks in the links below.<\/p>\n<table style=\"border-spacing: inherit;border-collapse: collapse;height: 1080px;width: 616px\">\n<tbody>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\"><strong>Time<\/strong><\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\"><strong>Topic<\/strong><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><strong>Speaker \/Authors<\/strong><\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">13:00-13:10<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">Welcome Note<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/sites.google.com\/iastate.edu\/qili\/\" target=\"_blank\" rel=\"noopener\">Prof. Qi Li<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0(Iowa State University)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">13:10-13:45<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">(<strong>Keynote<\/strong>) <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891561\" target=\"_blank\" rel=\"noopener\">Mining Reliable Information from Crowdsourced Data<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.cse.buffalo.edu\/~jing\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Jing Gao <\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a>(University at Buffalo)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">13:45-14:00<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">(<em>Spotlight<\/em>) <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891789\" target=\"_blank\" rel=\"noopener\">XTREME Learning for Affordable and Accessible AI<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a href=\"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/people\/submukhe\/\" target=\"_blank\" rel=\"noopener\">Subhabrata Mukherjee<span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (Microsoft Research)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">14:00-14:12<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">KNH: Multi-View Modeling with K-Nearest Hyperplanes Graph for Misinformation Detection<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1BBNtSQeayy7ozonQbsbXmMdtEKDF4DLi\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Long Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891642\" target=\"_blank\" rel=\"noopener\">[Presentation]<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Sara Abdali, Neil Shah and Evangelos Papalexakis (University of California, Riverside; Snap)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">14:12-14:24<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">Learning to Detect Few-Shot-Few-Clue Misinformation<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1B9Pz8snw-TPEPGWSh1g7sQ3fswJslq2R\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Long Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891582\" target=\"_blank\" rel=\"noopener\">[Presentation]<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\">Qiang Zhang, Shangsong Liang and Emine Yilmaz (University College London; Amazon)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">14:24-14:44<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">(<em>Spotlight<\/em>) <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891759\" target=\"_blank\" rel=\"noopener\">Securing Opinion Spam Detection<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.cse.lehigh.edu\/~sxie\/\" target=\"_blank\" rel=\"noopener\">Prof. Sihong Xie<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>\u00a0 (Lehigh University)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">14:45-15:20<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">(<strong>Live<\/strong> <strong>Keynote<\/strong>) Advances in Detection and Prediction of Malicious Activity on\u00a0 the Web<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.cse.gatech.edu\/people\/srijan-kumar\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Srijan Kumar <\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a>(Georgia Institute of Technology)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">15:20-15:40<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px;text-align: left\">(<em>Invited Talk<\/em>) <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891883\" target=\"_blank\" rel=\"noopener\">Rumor Detection on Social Media with Graph Structured Adversarial Learning<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Prof. Xi Zhang (Bejing University of Posts and Telecommunications)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">15:40-15:52<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">Explainable Rumor Detection using Inter and Intra-feature Attention Networks<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1BrknpRz3jbjMWXIdyG7Lf-9tP0XHDhnE\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Long Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] [<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891606\" target=\"_blank\" rel=\"noopener\">Presentation<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>]<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Mingxuan Chen, Ning Wang and Koduvayur P. Subbalakshmi (Stevens Institute of Technology)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">15:52-16:00<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">Out-of-Bag Anomaly Detection<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1BgaSSRPOK1rLXpIRL5O93JieuCN6N6js\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Short Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] [<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891545\" target=\"_blank\" rel=\"noopener\">Presentation<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>]<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Egor Klevak, Sangdi Lin, Andy Martin, Ondrej Linda and Eric Ringger (Zillow)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">16:00-16:08<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">Multi-Modal Classification for Polarization Intent Detection in Social Media<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1BvAdp4SB2pqI48hvMDhzSZVVCnj8r4p8\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Short Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] [<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891840\" target=\"_blank\" rel=\"noopener\">Presentation<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>]<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Tobby Lie, Haadi Jafarian, Stephen Hartnett, Hamilton Bean, Farnoush Banaei-Kashani (University of Colorado, Denver)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">16:10-16:50<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\"><strong>Live Panel Discussion<\/strong><\/p>\n<p>&nbsp;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.cs.uic.edu\/~liub\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Bing Liu<\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (UIC), <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/cse.buffalo.edu\/~jing\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Jing Gao<\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (SUNY Buffalo), <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.meng-jiang.com\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Meng Jiang<\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (Notre Dame), <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.cse.gatech.edu\/people\/srijan-kumar\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Srijan Kumar<\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (Georgia Tech)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">16:50-17:00<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">Shared Cup: Fake News Challenge<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.kaggle.com\/c\/fakenewskdd2020\/leaderboard\" target=\"_blank\" rel=\"noopener\">Kaggle Leaderboard<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\"><\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\"><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\"><\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\"><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The second international TrueFact Workshop: Making a Credible Web for Tomorrow will provide a forum where researchers and practitioners from academia, government and industry can share insights and identify new challenges and opportunities in resolving conflicts, fact-checking and ascertaining credibility of claims. The workshop will be held in San Diego, CA on August 24, 2020 in conjunction with the ACM SIGKDD 2020.<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_startdate":"2020-08-24","msr_enddate":"2020-08-24","msr_location":"Virtual\/Online","msr_expirationdate":"","msr_event_recording_link":"","msr_event_link":"","msr_event_link_redirect":false,"msr_event_time":"","msr_hide_region":true,"msr_private_event":false,"msr_hide_image_in_river":0,"footnotes":""},"research-area":[13556,13545,13559],"msr-region":[256048],"msr-event-type":[210063],"msr-video-type":[],"msr-locale":[268875],"msr-program-audience":[],"msr-post-option":[],"msr-impact-theme":[],"class_list":["post-676431","msr-event","type-msr-event","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-human-language-technologies","msr-research-area-social-sciences","msr-region-global","msr-event-type-workshop","msr-locale-en_us"],"msr_about":"<!-- wp:msr\/event-details {\"title\":\"KDD 2020 TrueFact Workshop: Making a Credible Web for Tomorrow\",\"backgroundColor\":\"grey\"} \/-->\n\n<!-- wp:msr\/content-tabs --><!-- wp:msr\/content-tab {\"title\":\"Abstract\"} --><!-- wp:freeform --><p>The second international <em>TrueFact Workshop: Making a Credible Web for Tomorrow<\/em> will provide a forum where researchers and practitioners from academia, government and industry can share insights and identify new challenges and opportunities in resolving conflicts, fact-checking and ascertaining credibility of claims. The workshop will be held in San Diego, CA on August 24, 2020 in conjunction with the <em>ACM SIGKDD 2020<\/em>.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter\" src=\"https:\/\/www.nsf.gov\/images\/logos\/NSF_4-Color_bitmap_Logo.png\" width=\"121\" height=\"122\" \/><span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<p>In recent times, the explosion of information from a variety of sources and cutting edge techniques such as Deepfake have made it increasingly important to check the credibility and reliability of the data. Large volumes of data generated from diverse information channels like social media, online news outlets, and crowd-sourcing contribute valuable knowledge; however, this comes with additional challenges to ascertain the credibility of user-generated and machine-generated information, resolving conflicts among heterogeneous data sources, identifying misinformation, rumors and bias, etc.<\/p>\n<ul>\n<li>Given diverse information about an object (e.g., a natural language claim text, an entity, structured triples and social network context) from heterogeneous and multi-modal sources, how do we identify high quality and trustworthy information and information sources?<\/li>\n<li>How can we leverage Knowledge Bases and external evidence sources from the Web for reasoning, explaining, and validating claims?<\/li>\n<li>How can we generate human-interpretable explanations for the models\u2019 verdict How can we design robust fake information (e.g., reviews and news) detection mechanisms to withstand adversarial generation strategies, as spammers and content generators are co-evolving with the advanced detectors?<\/li>\n<\/ul>\n<p>In order to answer these questions, this workshop encourages submissions to focus on big ideas \u2013 for resolving conflicts, fact-checking, ascertaining credibility of claims, explaining predictions from deep fake detectors, developing robust adversarial mechanisms for fake content detection, manipulation and safeguards, and making detection algorithms fair and unbiased to the involved participants \u2013 in heterogeneous and multi-modal sources of information including texts, images, videos, relational data, social networks and knowledge graphs.<span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<!-- \/wp:freeform --><!-- \/wp:msr\/content-tab --><!-- wp:msr\/content-tab {\"title\":\"Organizers\"} --><!-- wp:freeform --><ul>\n<li><a href=\"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/people\/submukhe\/\">Subhabrata Mukherjee (Microsoft Research)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.cs.iastate.edu\/people\/qi-li\">Qi Li (UIUC)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"http:\/\/www.cse.lehigh.edu\/~sxie\/\">Sihong Xie (Lehigh University)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"http:\/\/hanj.cs.illinois.edu\/\">Jiawei Han (UIUC)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.cs.uic.edu\/~psyu\/\">Philip S. Yu (UIC)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<li><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/cse.buffalo.edu\/~jing\/\">Jing Gao (SUNY Buffalo)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/li>\n<\/ul>\n<p><span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<!-- \/wp:freeform --><!-- \/wp:msr\/content-tab --><!-- wp:msr\/content-tab {\"title\":\"Call For Papers\"} --><!-- wp:freeform --><p>Our workshop on truth discovery and fact-checking is motivated by the need for new research, tools and techniques to advance the field with the following focus areas:<\/p>\n<ul>\n<li>Data heterogeneity, multi-modality, novel applications and data sources related to truth discovery, fact-checking, and rumor detection<\/li>\n<li>Explore tools and methods that can generate human-interpretable explanations as opposed to black box methods, as transparency and lack of explanation remain a concern for industry to readily deploy these techniques in practise<\/li>\n<li>Security and robustness of fake content detection under a known or unknown environment where spammers can learn and then commit arbitrary attack strategy to poison the data or evade the detectors<\/li>\n<\/ul>\n<p><em>In addition to the regular workshop, we will also host a data challenge track with two shared tasks for fake review detection in an adversarial framework and fake news detection (details will be announced soon).<\/em><\/p>\n<p>The second workshop on\u00a0<em>Truth Discovery and Fact Checking: Making a Credible Web for Tomorrow<\/em>\u00a0will provide a forum where researchers and practitioners from academia, government and industry can share insights and identify new challenges and opportunities in resolving conflicts, fact-checking and ascertaining credibility of claims. The workshop will be held in San Diego, CA on August 23, 2020 in conjunction with the\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.kdd.org\/kdd2020\/\">ACM SIGKDD 2020<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>.<\/p>\n<p><strong>In view of the recent COVID-19 outbreak, the format of the workshop (in-person, virtual, or both) will be in accordance to the SIGKDD 2020 main conference format<\/strong>.<\/p>\n<h2 id=\"topics-of-interest-include-but-are-not-limited-to\">Topics of interest include, but are not limited to:<\/h2>\n<p>Topics of interest include, but are not limited to:<\/p>\n<ul>\n<li>Truth finding and discovery<\/li>\n<li>Fact-checking, rumor, and misinformation<\/li>\n<li>Credibility analysis and spam detection<\/li>\n<li>Fake reviews and reviewers<\/li>\n<li>Leveraging knowledge bases for reasoning, validating and explaining contentious claims<\/li>\n<li>Transparency, fairness, bias, privacy and ethics of information systems<\/li>\n<li>Emerging applications, novel data sources, and case studies<\/li>\n<li>Explainable and interpretable models<\/li>\n<li>Robustness detection under adversarial and unknown data poisoning and evasion attacks.<\/li>\n<li>Heterogeneous and multi-modal information including relational data, natural language text, search logs, images, video, etc.<\/li>\n<\/ul>\n<h2 id=\"submission-guidelines\">Submission Guidelines<\/h2>\n<p>We invite submissions for original research papers both theory and application-oriented as well as submissions from the research track and applied data science track of the main KDD conference. We encourage the participants to submit papers on novel datasets and release them to advance the field. Papers must be submitted in PDF according to the ACM Proceedings Template\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.acm.org\/publications\/proceedings-template\">https:\/\/www.acm.org\/publications\/proceedings-template<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>\u00a0in a single-blind format (including author names and affiliations). We welcome both long papers (maximum length of 9 pages) and short papers (maximum length of 5 pages). The accepted papers will be published on the workshop\u2019s website, and will not be considered archival for resubmission purposes. Please submit your papers at the EasyChair submission link\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/easychair.org\/conferences\/?conf=truefact2020\">https:\/\/easychair.org\/conferences\/?conf=truefact2020<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>.<\/p>\n<p>We also invite participants for TrueFact 2020 Shared Tasks. Instructions for participation and awards will be announced soon!<\/p>\n<h2 id=\"important-dates\">Important Dates<\/h2>\n<p>All deadlines are 11:59 PM Pacific Standard Time<\/p>\n<p>Workshop paper submissions:\u00a0<del>May 20<\/del>\u00a0June 15, 2020<\/p>\n<p>Workshop paper notifications:\u00a0<del>June 15<\/del>\u00a0July 15, 2020<\/p>\n<p>Workshop date: August 24, 2020<span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<!-- \/wp:freeform --><!-- \/wp:msr\/content-tab --><!-- wp:msr\/content-tab {\"title\":\"Shared Tasks\"} --><!-- wp:freeform --><h2 id=\"shared-task-1-adversarial-attacks-against-review-spam-detectors\">Shared Task 1 (Adversarial attacks against review spam detectors).<\/h2>\n<ul>\n<li>The competition is hosted on Kaggle:\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.kaggle.com\/c\/adversarial-attacks-against-spam-detectors\">https:\/\/www.kaggle.com\/c\/adversarial-attacks-against-spam-detectors<\/a><\/li>\n<li>Prize: first-place $300, runner-up $150<\/li>\n<li>Please email Sihong Xie\u00a0<a href=\"mailto:xiesihong1@gmail.com\">xiesihong1@gmail.com<\/a>\u00a0for any questions.<\/li>\n<\/ul>\n<h2 id=\"shared-task-2-fake-news-detection\">Shared Task 2 (Fake news detection).<\/h2>\n<ul>\n<li>The competition is hosted on Kaggle:\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" target=\"_blank\" href=\"https:\/\/www.kaggle.com\/c\/fakenewskdd2020\/overview\">https:\/\/www.kaggle.com\/c\/fakenewskdd2020\/overview<\/a><\/li>\n<li>Prize: first-place $300, runner-up $150<\/li>\n<li>Please email Subhabrata Mukherjee\u00a0<a href=\"mailto:subhabrata.mukherjee@microsoft.com\">subhabrata.mukherjee@microsoft.com<\/a>\u00a0for any questions.<\/li>\n<\/ul>\n<p><span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<!-- \/wp:freeform --><!-- \/wp:msr\/content-tab --><!-- wp:msr\/content-tab {\"title\":\"Program Schedule\"} --><!-- wp:freeform --><p>We are releasing the pre-recorded video presentations for all the talks in the links below.<\/p>\n<table style=\"border-spacing: inherit;border-collapse: collapse;height: 1080px;width: 616px\">\n<tbody>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\"><strong>Time<\/strong><\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\"><strong>Topic<\/strong><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><strong>Speaker \/Authors<\/strong><\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">13:00-13:10<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">Welcome Note<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/sites.google.com\/iastate.edu\/qili\/\" target=\"_blank\" rel=\"noopener\">Prof. Qi Li<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0(Iowa State University)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">13:10-13:45<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">(<strong>Keynote<\/strong>) <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891561\" target=\"_blank\" rel=\"noopener\">Mining Reliable Information from Crowdsourced Data<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.cse.buffalo.edu\/~jing\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Jing Gao <\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a>(University at Buffalo)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">13:45-14:00<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">(<em>Spotlight<\/em>) <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891789\" target=\"_blank\" rel=\"noopener\">XTREME Learning for Affordable and Accessible AI<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a href=\"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/people\/submukhe\/\" target=\"_blank\" rel=\"noopener\">Subhabrata Mukherjee<span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (Microsoft Research)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">14:00-14:12<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">KNH: Multi-View Modeling with K-Nearest Hyperplanes Graph for Misinformation Detection<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1BBNtSQeayy7ozonQbsbXmMdtEKDF4DLi\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Long Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891642\" target=\"_blank\" rel=\"noopener\">[Presentation]<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Sara Abdali, Neil Shah and Evangelos Papalexakis (University of California, Riverside; Snap)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">14:12-14:24<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">Learning to Detect Few-Shot-Few-Clue Misinformation<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1B9Pz8snw-TPEPGWSh1g7sQ3fswJslq2R\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Long Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891582\" target=\"_blank\" rel=\"noopener\">[Presentation]<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\">Qiang Zhang, Shangsong Liang and Emine Yilmaz (University College London; Amazon)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">14:24-14:44<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">(<em>Spotlight<\/em>) <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891759\" target=\"_blank\" rel=\"noopener\">Securing Opinion Spam Detection<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.cse.lehigh.edu\/~sxie\/\" target=\"_blank\" rel=\"noopener\">Prof. Sihong Xie<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>\u00a0 (Lehigh University)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">14:45-15:20<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">(<strong>Live<\/strong> <strong>Keynote<\/strong>) Advances in Detection and Prediction of Malicious Activity on\u00a0 the Web<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.cse.gatech.edu\/people\/srijan-kumar\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Srijan Kumar <\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a>(Georgia Institute of Technology)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">15:20-15:40<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px;text-align: left\">(<em>Invited Talk<\/em>) <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891883\" target=\"_blank\" rel=\"noopener\">Rumor Detection on Social Media with Graph Structured Adversarial Learning<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Prof. Xi Zhang (Bejing University of Posts and Telecommunications)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">15:40-15:52<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">Explainable Rumor Detection using Inter and Intra-feature Attention Networks<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1BrknpRz3jbjMWXIdyG7Lf-9tP0XHDhnE\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Long Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] [<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891606\" target=\"_blank\" rel=\"noopener\">Presentation<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>]<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Mingxuan Chen, Ning Wang and Koduvayur P. Subbalakshmi (Stevens Institute of Technology)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">15:52-16:00<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">Out-of-Bag Anomaly Detection<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1BgaSSRPOK1rLXpIRL5O93JieuCN6N6js\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Short Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] [<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891545\" target=\"_blank\" rel=\"noopener\">Presentation<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>]<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Egor Klevak, Sangdi Lin, Andy Martin, Ondrej Linda and Eric Ringger (Zillow)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 72px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">16:00-16:08<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">Multi-Modal Classification for Polarization Intent Detection in Social Media<\/p>\n<p>[<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/drive.google.com\/file\/d\/1BvAdp4SB2pqI48hvMDhzSZVVCnj8r4p8\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Short Paper<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>] [<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/vimeo.com\/445891840\" target=\"_blank\" rel=\"noopener\">Presentation<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>]<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Tobby Lie, Haadi Jafarian, Stephen Hartnett, Hamilton Bean, Farnoush Banaei-Kashani (University of Colorado, Denver)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">16:10-16:50<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\"><strong>Live Panel Discussion<\/strong><\/p>\n<p>&nbsp;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.cs.uic.edu\/~liub\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Bing Liu<\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (UIC), <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/cse.buffalo.edu\/~jing\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Jing Gao<\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (SUNY Buffalo), <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"http:\/\/www.meng-jiang.com\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Meng Jiang<\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (Notre Dame), <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.cse.gatech.edu\/people\/srijan-kumar\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Srijan Kumar<\/strong><span class=\"sr-only\"> (opens in new tab)<\/span><\/a> (Georgia Tech)<\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8212;&#8211;<\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">16:50-17:00<\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">Shared Cup: Fake News Challenge<\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.kaggle.com\/c\/fakenewskdd2020\/leaderboard\" target=\"_blank\" rel=\"noopener\">Kaggle Leaderboard<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/td>\n<\/tr>\n<tr style=\"height: 24px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\"><\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\"><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><\/td>\n<\/tr>\n<tr style=\"height: 48px\">\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\"><\/td>\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\"><\/td>\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<span id=\"label-external-link\" class=\"sr-only\" aria-hidden=\"true\">Opens in a new tab<\/span><\/p>\n<!-- \/wp:freeform --><!-- \/wp:msr\/content-tab --><!-- \/wp:msr\/content-tabs -->","tab-content":[{"id":0,"name":"Abstract","content":"In recent times, the explosion of information from a variety of sources and cutting edge techniques such as Deepfake have made it increasingly important to check the credibility and reliability of the data. Large volumes of data generated from diverse information channels like social media, online news outlets, and crowd-sourcing contribute valuable knowledge; however, this comes with additional challenges to ascertain the credibility of user-generated and machine-generated information, resolving conflicts among heterogeneous data sources, identifying misinformation, rumors and bias, etc.\r\n<ul>\r\n \t<li>Given diverse information about an object (e.g., a natural language claim text, an entity, structured triples and social network context) from heterogeneous and multi-modal sources, how do we identify high quality and trustworthy information and information sources?<\/li>\r\n \t<li>How can we leverage Knowledge Bases and external evidence sources from the Web for reasoning, explaining, and validating claims?<\/li>\r\n \t<li>How can we generate human-interpretable explanations for the models\u2019 verdict How can we design robust fake information (e.g., reviews and news) detection mechanisms to withstand adversarial generation strategies, as spammers and content generators are co-evolving with the advanced detectors?<\/li>\r\n<\/ul>\r\nIn order to answer these questions, this workshop encourages submissions to focus on big ideas \u2013 for resolving conflicts, fact-checking, ascertaining credibility of claims, explaining predictions from deep fake detectors, developing robust adversarial mechanisms for fake content detection, manipulation and safeguards, and making detection algorithms fair and unbiased to the involved participants \u2013 in heterogeneous and multi-modal sources of information including texts, images, videos, relational data, social networks and knowledge graphs."},{"id":1,"name":"Organizers","content":"<ul>\r\n \t<li><a href=\"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/people\/submukhe\/\">Subhabrata Mukherjee (Microsoft Research)<\/a><\/li>\r\n \t<li><a href=\"https:\/\/www.cs.iastate.edu\/people\/qi-li\">Qi Li (UIUC)<\/a><\/li>\r\n \t<li><a href=\"http:\/\/www.cse.lehigh.edu\/~sxie\/\">Sihong Xie (Lehigh University)<\/a><\/li>\r\n \t<li><a href=\"http:\/\/hanj.cs.illinois.edu\/\">Jiawei Han (UIUC)<\/a><\/li>\r\n \t<li><a href=\"https:\/\/www.cs.uic.edu\/~psyu\/\">Philip S. Yu (UIC)<\/a><\/li>\r\n \t<li><a href=\"https:\/\/cse.buffalo.edu\/~jing\/\">Jing Gao (SUNY Buffalo)<\/a><\/li>\r\n<\/ul>"},{"id":2,"name":"Call For Papers","content":"Our workshop on truth discovery and fact-checking is motivated by the need for new research, tools and techniques to advance the field with the following focus areas:\r\n<ul>\r\n \t<li>Data heterogeneity, multi-modality, novel applications and data sources related to truth discovery, fact-checking, and rumor detection<\/li>\r\n \t<li>Explore tools and methods that can generate human-interpretable explanations as opposed to black box methods, as transparency and lack of explanation remain a concern for industry to readily deploy these techniques in practise<\/li>\r\n \t<li>Security and robustness of fake content detection under a known or unknown environment where spammers can learn and then commit arbitrary attack strategy to poison the data or evade the detectors<\/li>\r\n<\/ul>\r\n<em>In addition to the regular workshop, we will also host a data challenge track with two shared tasks for fake review detection in an adversarial framework and fake news detection (details will be announced soon).<\/em>\r\n\r\nThe second workshop on\u00a0<em>Truth Discovery and Fact Checking: Making a Credible Web for Tomorrow<\/em>\u00a0will provide a forum where researchers and practitioners from academia, government and industry can share insights and identify new challenges and opportunities in resolving conflicts, fact-checking and ascertaining credibility of claims. The workshop will be held in San Diego, CA on August 23, 2020 in conjunction with the\u00a0<a href=\"https:\/\/www.kdd.org\/kdd2020\/\">ACM SIGKDD 2020<\/a>.\r\n\r\n<strong>In view of the recent COVID-19 outbreak, the format of the workshop (in-person, virtual, or both) will be in accordance to the SIGKDD 2020 main conference format<\/strong>.\r\n<h2 id=\"topics-of-interest-include-but-are-not-limited-to\">Topics of interest include, but are not limited to:<\/h2>\r\nTopics of interest include, but are not limited to:\r\n<ul>\r\n \t<li>Truth finding and discovery<\/li>\r\n \t<li>Fact-checking, rumor, and misinformation<\/li>\r\n \t<li>Credibility analysis and spam detection<\/li>\r\n \t<li>Fake reviews and reviewers<\/li>\r\n \t<li>Leveraging knowledge bases for reasoning, validating and explaining contentious claims<\/li>\r\n \t<li>Transparency, fairness, bias, privacy and ethics of information systems<\/li>\r\n \t<li>Emerging applications, novel data sources, and case studies<\/li>\r\n \t<li>Explainable and interpretable models<\/li>\r\n \t<li>Robustness detection under adversarial and unknown data poisoning and evasion attacks.<\/li>\r\n \t<li>Heterogeneous and multi-modal information including relational data, natural language text, search logs, images, video, etc.<\/li>\r\n<\/ul>\r\n<h2 id=\"submission-guidelines\">Submission Guidelines<\/h2>\r\nWe invite submissions for original research papers both theory and application-oriented as well as submissions from the research track and applied data science track of the main KDD conference. We encourage the participants to submit papers on novel datasets and release them to advance the field. Papers must be submitted in PDF according to the ACM Proceedings Template\u00a0<a href=\"https:\/\/www.acm.org\/publications\/proceedings-template\">https:\/\/www.acm.org\/publications\/proceedings-template<\/a>\u00a0in a single-blind format (including author names and affiliations). We welcome both long papers (maximum length of 9 pages) and short papers (maximum length of 5 pages). The accepted papers will be published on the workshop\u2019s website, and will not be considered archival for resubmission purposes. Please submit your papers at the EasyChair submission link\u00a0<a href=\"https:\/\/easychair.org\/conferences\/?conf=truefact2020\">https:\/\/easychair.org\/conferences\/?conf=truefact2020<\/a>.\r\n\r\nWe also invite participants for TrueFact 2020 Shared Tasks. Instructions for participation and awards will be announced soon!\r\n<h2 id=\"important-dates\">Important Dates<\/h2>\r\nAll deadlines are 11:59 PM Pacific Standard Time\r\n\r\nWorkshop paper submissions:\u00a0<del>May 20<\/del>\u00a0June 15, 2020\r\n\r\nWorkshop paper notifications:\u00a0<del>June 15<\/del>\u00a0July 15, 2020\r\n\r\nWorkshop date: August 24, 2020"},{"id":3,"name":"Shared Tasks","content":"<h2 id=\"shared-task-1-adversarial-attacks-against-review-spam-detectors\">Shared Task 1 (Adversarial attacks against review spam detectors).<\/h2>\r\n<ul>\r\n \t<li>The competition is hosted on Kaggle:\u00a0<a href=\"https:\/\/www.kaggle.com\/c\/adversarial-attacks-against-spam-detectors\">https:\/\/www.kaggle.com\/c\/adversarial-attacks-against-spam-detectors<\/a><\/li>\r\n \t<li>Prize: first-place $300, runner-up $150<\/li>\r\n \t<li>Please email Sihong Xie\u00a0<a href=\"mailto:xiesihong1@gmail.com\">xiesihong1@gmail.com<\/a>\u00a0for any questions.<\/li>\r\n<\/ul>\r\n<h2 id=\"shared-task-2-fake-news-detection\">Shared Task 2 (Fake news detection).<\/h2>\r\n<ul>\r\n \t<li>The competition is hosted on Kaggle:\u00a0<a href=\"https:\/\/www.kaggle.com\/c\/fakenewskdd2020\/overview\">https:\/\/www.kaggle.com\/c\/fakenewskdd2020\/overview<\/a><\/li>\r\n \t<li>Prize: first-place $300, runner-up $150<\/li>\r\n \t<li>Please email Subhabrata Mukherjee\u00a0<a href=\"mailto:subhabrata.mukherjee@microsoft.com\">subhabrata.mukherjee@microsoft.com<\/a>\u00a0for any questions.<\/li>\r\n<\/ul>"},{"id":4,"name":"Program Schedule","content":"We are releasing the pre-recorded video presentations for all the talks in the links below.\r\n<table style=\"border-spacing: inherit;border-collapse: collapse;height: 1080px;width: 616px\">\r\n<tbody>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\"><strong>Time<\/strong><\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\"><strong>Topic<\/strong><\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><strong>Speaker \/Authors<\/strong><\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">13:00-13:10<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">Welcome Note<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">\u00a0<a href=\"https:\/\/sites.google.com\/iastate.edu\/qili\/\" target=\"_blank\" rel=\"noopener\">Prof. Qi Li<\/a>\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0(Iowa State University)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 48px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">13:10-13:45<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">(<strong>Keynote<\/strong>) <a href=\"https:\/\/vimeo.com\/445891561\" target=\"_blank\" rel=\"noopener\">Mining Reliable Information from Crowdsourced Data<\/a><\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a href=\"http:\/\/www.cse.buffalo.edu\/~jing\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Jing Gao <\/strong><\/a>(University at Buffalo)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 48px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">13:45-14:00<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">(<em>Spotlight<\/em>) <a href=\"https:\/\/vimeo.com\/445891789\" target=\"_blank\" rel=\"noopener\">XTREME Learning for Affordable and Accessible AI<\/a><\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a href=\"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/people\/submukhe\/\" target=\"_blank\" rel=\"noopener\">Subhabrata Mukherjee<\/a> (Microsoft Research)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 72px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">14:00-14:12<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">KNH: Multi-View Modeling with K-Nearest Hyperplanes Graph for Misinformation Detection\r\n\r\n[<a href=\"https:\/\/drive.google.com\/file\/d\/1BBNtSQeayy7ozonQbsbXmMdtEKDF4DLi\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Long Paper<\/a>] <a href=\"https:\/\/vimeo.com\/445891642\" target=\"_blank\" rel=\"noopener\">[Presentation]<\/a><\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Sara Abdali, Neil Shah and Evangelos Papalexakis (University of California, Riverside; Snap)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 48px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">14:12-14:24<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">Learning to Detect Few-Shot-Few-Clue Misinformation\r\n\r\n[<a href=\"https:\/\/drive.google.com\/file\/d\/1B9Pz8snw-TPEPGWSh1g7sQ3fswJslq2R\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Long Paper<\/a>] <a href=\"https:\/\/vimeo.com\/445891582\" target=\"_blank\" rel=\"noopener\">[Presentation]<\/a><\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\">Qiang Zhang, Shangsong Liang and Emine Yilmaz (University College London; Amazon)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 48px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">14:24-14:44<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">(<em>Spotlight<\/em>) <a href=\"https:\/\/vimeo.com\/445891759\" target=\"_blank\" rel=\"noopener\">Securing Opinion Spam Detection<\/a><\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a href=\"http:\/\/www.cse.lehigh.edu\/~sxie\/\" target=\"_blank\" rel=\"noopener\">Prof. Sihong Xie<\/a>\u00a0 (Lehigh University)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">14:45-15:20<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">(<strong>Live<\/strong> <strong>Keynote<\/strong>) Advances in Detection and Prediction of Malicious Activity on\u00a0 the Web<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><a href=\"https:\/\/www.cse.gatech.edu\/people\/srijan-kumar\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Srijan Kumar <\/strong><\/a>(Georgia Institute of Technology)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 72px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">15:20-15:40<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px;text-align: left\">(<em>Invited Talk<\/em>) <a href=\"https:\/\/vimeo.com\/445891883\" target=\"_blank\" rel=\"noopener\">Rumor Detection on Social Media with Graph Structured Adversarial Learning<\/a><\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Prof. Xi Zhang (Bejing University of Posts and Telecommunications)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 72px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">15:40-15:52<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">Explainable Rumor Detection using Inter and Intra-feature Attention Networks\r\n\r\n[<a href=\"https:\/\/drive.google.com\/file\/d\/1BrknpRz3jbjMWXIdyG7Lf-9tP0XHDhnE\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Long Paper<\/a>] [<a href=\"https:\/\/vimeo.com\/445891606\" target=\"_blank\" rel=\"noopener\">Presentation<\/a>]<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Mingxuan Chen, Ning Wang and Koduvayur P. Subbalakshmi (Stevens Institute of Technology)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 72px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">15:52-16:00<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">Out-of-Bag Anomaly Detection\r\n\r\n[<a href=\"https:\/\/drive.google.com\/file\/d\/1BgaSSRPOK1rLXpIRL5O93JieuCN6N6js\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Short Paper<\/a>] [<a href=\"https:\/\/vimeo.com\/445891545\" target=\"_blank\" rel=\"noopener\">Presentation<\/a>]<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Egor Klevak, Sangdi Lin, Andy Martin, Ondrej Linda and Eric Ringger (Zillow)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 72px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 72px\">16:00-16:08<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 72px\">Multi-Modal Classification for Polarization Intent Detection in Social Media\r\n\r\n[<a href=\"https:\/\/drive.google.com\/file\/d\/1BvAdp4SB2pqI48hvMDhzSZVVCnj8r4p8\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\">Short Paper<\/a>] [<a href=\"https:\/\/vimeo.com\/445891840\" target=\"_blank\" rel=\"noopener\">Presentation<\/a>]<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 72px\">Tobby Lie, Haadi Jafarian, Stephen Hartnett, Hamilton Bean, Farnoush Banaei-Kashani (University of Colorado, Denver)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">16:10-16:50<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\"><strong>Live Panel Discussion<\/strong>\r\n\r\n&nbsp;<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><a href=\"https:\/\/www.cs.uic.edu\/~liub\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Bing Liu<\/strong><\/a> (UIC), <a href=\"https:\/\/cse.buffalo.edu\/~jing\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Jing Gao<\/strong><\/a> (SUNY Buffalo), <a href=\"http:\/\/www.meng-jiang.com\/\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Meng Jiang<\/strong><\/a> (Notre Dame), <a href=\"https:\/\/www.cse.gatech.edu\/people\/srijan-kumar\" target=\"_blank\" rel=\"noopener\"><strong>Prof. Srijan Kumar<\/strong><\/a> (Georgia Tech)<\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\">-----------------<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\">------------------------------------------------<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\">-----------------------------<\/td>\r\n<\/tr>\r\n<tr style=\"height: 48px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\">16:50-17:00<\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\">Shared Cup: Fake News Challenge<\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><a href=\"https:\/\/www.kaggle.com\/c\/fakenewskdd2020\/leaderboard\" target=\"_blank\" rel=\"noopener\">Kaggle Leaderboard<\/a><\/td>\r\n<\/tr>\r\n<tr style=\"height: 24px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 24px\"><\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 24px\"><\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 24px\"><\/td>\r\n<\/tr>\r\n<tr style=\"height: 48px\">\r\n<td style=\"width: 142px;padding: inherit;border: inherit;height: 48px\"><\/td>\r\n<td style=\"width: 297px;padding: inherit;border: inherit;height: 48px\"><\/td>\r\n<td style=\"width: 177px;padding: inherit;border: inherit;height: 48px\"><\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n&nbsp;"}],"msr_startdate":"2020-08-24","msr_enddate":"2020-08-24","msr_event_time":"","msr_location":"Virtual\/Online","msr_event_link":"","msr_event_recording_link":"","msr_startdate_formatted":"August 24, 2020","msr_register_text":"Watch now","msr_cta_link":"","msr_cta_text":"","msr_cta_bi_name":"","featured_image_thumbnail":null,"event_excerpt":"The second international TrueFact Workshop: Making a Credible Web for Tomorrow will provide a forum where researchers and practitioners from academia, government and industry can share insights and identify new challenges and opportunities in resolving conflicts, fact-checking and ascertaining credibility of claims. 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