- Celebrity Profiling: Influencer Edition
- Cross-Domain Authorship Verification
- Profiling Fake News Spreaders on Twitter
- Style Change Detection
- March 18, 2020: Early bird software submission
- April 15, 2020: TIRA evaluation phase opens
- May 13, 2020: TIRA evaluation phase deadline
- May 29, 2020: Participant paper submission [template] [guidelines] [submission]
- TBD: Peer review notification
- TBD: Camery-ready participant papers submission
- TBD: Early bird conference registration
- September 22-25, 2020: Conference
The timezone of all deadlines is Anywhere on Earth.
Julio GonzaloNatural Language Processing and Information Retrieval Group, UNED, Spain
Bias in Information
Anastasia GiachanouPRHLT Research Center, Universitat Politècnica de València (UPV), Spain
Anastasia Giachanou is a Research Fellow at the Pattern Recognition and Human Language Technologies (PRHLT) Research Center at the Universitat Politècnica de València (UPV) and a member of the Natural Language Engineering Lab headed by Prof. Paolo Rosso. She received her PhD from the Faculty of Informatics at the University of Lugano, in Switzerland working on the topic of “Tracking Opinion Evolution on Social Media”. Her research interests include fake news detection, credibility in news, bot detection, sentiment and emotion analysis, temporal opinion mining and information retrieval. She serves on the editorial board of Information Processing & Management Journal and as a PC member for well-established conferences such as SIGIR, ECIR, CIKM, and ECAI. She is a recipient of an Swiss National Foundation (SNF) early post-doc grant on the project "Early Detection of Fake News on Social Media".
Misinformation Detection in Online Social Networks
Misinformation is one of the most critical challenges of recent years. Despite all the attempts, the automatic detection of misinformation still remains an open problem. Although misinformation and fake news exist for a long period of time, the ubiquitousness of social media has facilitated their propagation with severe consequences for the society. This talk will focus on the topic of misinformation detection. First, I will introduce the concept and characteristics of the different types of misinformation and disinformation such as fake news, satire, rumours that go viral in online social networks. Then, I will present some of the most recent detection approaches with a particular focus on approaches that exploit psycho-linguistic information (i.e., emotion, sentiment, informal language). Also, I will present approaches that exploit information extracted from user profiles and user interactions. Finally, I will discuss challenges and open issues in the field of misinformation detection.