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What Motivates You? Benchmarking Automatic Detection of Basic Needs from Short Posts ...
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On the Detection of False Information: From Rumors to Fake News
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Irony Detection in a Multilingual Context
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In: ECIR ; https://hal.archives-ouvertes.fr/hal-02889008 ; ECIR, Apr 2020, online, Portugal (2020)
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The Role of Personality and Linguistic Patterns in Discriminating Between Fake News Spreaders and Fact Checkers
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In: Natural Language Processing and Information Systems (2020)
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Abstract:
Users play a critical role in the creation and propagation of fake news online by consuming and sharing articles with inaccurate information either intentionally or unintentionally. Fake news are written in a way to confuse readers and therefore understanding which articles contain fabricated information is very challenging for non-experts. Given the difficulty of the task, several fact checking websites have been developed to raise awareness about which articles contain fabricated information. As a result of those platforms, several users are interested to share posts that cite evidence with the aim to refute fake news and warn other users. These users are known as fact checkers. However, there are users who tend to share false information, who can be characterised as potential fake news spreaders. In this paper, we propose the CheckerOrSpreader model that can classify a user as a potential fact checker or a potential fake news spreader. Our model is based on a Convolutional Neural Network (CNN) and combines word embeddings with features that represent users’ personality traits and linguistic patterns used in their tweets. Experimental results show that leveraging linguistic patterns and personality traits can improve the performance in differentiating between checkers and spreaders.
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URL: https://doi.org/10.1007/978-3-030-51310-8_17 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298180/
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An Emotional Analysis of False Information in Social Media and News Articles
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Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection
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The Role of Personality and Linguistic Patterns in Discriminating Between Fake News Spreaders and Fact Checkers
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IDAT@FIRE2019: Overview of the Track on Irony Detection in Arabic Tweets
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Online Hate Speech against Women: Automatic Identification of Misogyny and Sexism on Twitter
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