FACT EXTRACTION AND VERIFICATION PIPELINE FOR COVID-19 RELATED USER POSTS IN SOCIAL MEDIA

Download
2022-6-29
Temiz, Orkun
Social media has become a prevalent platform for consuming and sharing information online. The vast amounts of information, shared easily and rapidly by social media, have increased the demand for fact-checking. Misinformation threatens not only the reputation of individuals and organizations but also society. When the COVID-19 pandemic broke out, the concerns around misinformation, which threatens public health and society, have significantly increased. In this thesis, a new zero-shot fact extraction and verification pipeline for user posts related to COVID-19 against the medical articles is proposed. The pipeline comprises preprocessing of user posts, claim extraction, document retrieval, evidence selection, and verdict assignment components. The proposed pipeline not only labels the claim but also presents the related evidence set extracted from the pipeline regarding the claim, which gives interpretable results for the society about the claim. Also, it does not need to see previously labeled posts unlike numerous supervised studies in the literature instead; it uses the zero-shot capabilities of existing models. The proposed pipeline obtains on-par and stable performance compared with the state-of-art supervised techniques for classifying raw user posts (CoAID) and rumors collected from social media (COVID-19 Rumors Dataset). On the other hand, it achieves superior performance in detecting new emerging misinformation topics.

Suggestions

Sentiment Enhanced Hybrid TF-IDF for Microblogs
Simsek, Atakan; Karagöz, Pınar (2014-12-05)
As the usage of social networks grows day by day, a single person can reach hundreds or thousands of people in a minute. Microblogging is the new era of social communication, which can be used anywhere thanks to mobile phones. People spend hours and use social networks extensively, expressing their feelings, interests and dislikes. If this data can be extracted and analyzed effectively; useful items, news or people can be recommended. There are high number of studies that extract keywords from texts in orde...
Combining topology-based & content-based analysis for followee recommendation on Twitter
Yanar, Aysu; Karagöz, Pınar; Taşkaya Temizel, Tuğba; Department of Information Systems (2015)
Twitter has become an important social platform for individuals and people share a high number of information about their personal lives, interests and viral news during emergencies. As of 2014, Twitter has 240 million active users and approximately 500 million tweets are shared every day. This information overload in Twitter has become a serious problem due to the growing volume of messages and increasing number of users. Recommender systems help to overcome this challenge. Finding interesting users and ge...
Context Based Semantic Relations in Tweets
Özer, Özdikiş; Karagöz, Pınar; Oğuztüzün, Mehmet Halit Seyfullah (Springer, 2014-01-01)
Twitter, a popular social networking platform, provides a medium for people to share information and opinions with their followers. In such a medium, a flash event finds an immediate response. However, one concept may be expressed in many different ways. Because of users’ different writing conventions, acronym usages, language differences, and spelling mistakes, there may be variations in the content of postings even if they are about the same event. Analyzing semantic relationships and detecting these vari...
SOCIAL MEDIA FOR HIGHER EDUCATION FROM STUDENTS' PERSPECTIVES
Celik, Ilknur (2015-07-08)
Social media has received a worldwide adoption over the last decade for various purposes from communication to exchange of ideas, marketing, networking, following news or celebrities, and even to utilization as a trigger for social movements. Hence, the potential use of this medium for education needs exploration. This study presents Turkish higher education students' current practices and perceptions towards social media, and its potential use for learning in higher education. An online survey was administ...
INVESTIGATING THE INDIVIDUALS' PERCEPTION ABOUT SOCIAL MEDIA INFLUENCERS: A SURVEY STUDY ON UNIVERSITY STUDENTS
Yüksel, Umutcan Sümeyye; Özdemir, Özlem; Department of Business Administration (2022-9)
Internet and social media have become integral to our lives, creating social media celebrities or influencer terms. This thesis explores social media influencers' effects on social media users. Perceived similarity by the user to the influencer, wishful identification by the user with the influencer, perceived credibility of the influencer, and parasocial identification between the user and the influencer are investigated. This thesis aims to contribute to the literature by simultaneously analyzing perceive...
Citation Formats
O. Temiz, “FACT EXTRACTION AND VERIFICATION PIPELINE FOR COVID-19 RELATED USER POSTS IN SOCIAL MEDIA,” M.S. - Master of Science, Middle East Technical University, 2022.