Claim Behavior over Time in Twitter

Fernanda Weiss, Ignacio Espinoza, Julio Hurtado, Marcelo Mendoza

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

© 2019, Springer Nature Switzerland AG. Social media is the primary source of information for many people around the world, not only to know about their families and friends but also to read about news and trends in different areas of interest. Fake News or rumors can generate big problems of misinformation, being able to change the mindset of a large group of people concerning a specific topic. Many companies and researchers have put their efforts into detecting these rumors with machine learning algorithms creating reports of the influence of these “news” in social media (https://www.knightfoundation.org/reports/disinformation-fake-news-and-influence-campaigns-on-twitter ). Only a few studies have been made in detecting rumors in real-time, considering the first hours of propagation. In this work, we study the spread of a claim, analyzing different characteristics and how propagation patterns behave in time. Experiments show that rumors have different behaviours that can be used to classify them within the first hours of propagation.
Original languageEnglish
Title of host publicationClaim Behavior over Time in Twitter
Pages468-479
Number of pages12
ISBN (Electronic)9783030219017
DOIs
Publication statusPublished - 1 Jan 2019
EventLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duration: 1 Jan 2019 → …

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11578 LNCS
ISSN (Print)0302-9743

Conference

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Period1/01/19 → …

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  • Cite this

    Weiss, F., Espinoza, I., Hurtado, J., & Mendoza, M. (2019). Claim Behavior over Time in Twitter. In Claim Behavior over Time in Twitter (pp. 468-479). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11578 LNCS). https://doi.org/10.1007/978-3-030-21902-4_33