Classification Aware Neural Topic Model and its Application on a New COVID-19 Disinformation Corpus
The explosion of disinformation accompanying the COVID-19 pandemic has overloaded fact-checkers and media worldwide, and brought a new major challenge to government responses worldwide. Not only is disinformation creating confusion about medical science amongst citizens, but it is also amplifying distrust in policy makers and governments. To help tackle this, we developed computational methods to categorise COVID-19 disinformation. The COVID-19 disinformation categories could be used for a) focusing fact-checking efforts on the most damaging kinds of COVID-19 disinformation; b) guiding policy makers who are trying to deliver effective public health messages and counter effectively COVID-19 disinformation. This paper presents: 1) a corpus containing what is currently the largest available set of manually annotated COVID-19 disinformation categories; 2) a classification-aware neural topic model (CANTM) designed for COVID-19 disinformation category classification and topic discovery; 3) an extensive analysis of COVID-19 disinformation categories with respect to time, volume, false type, media type and origin source.
Code (0)
등록된 구현이 없습니다.
Tasks
Fact CheckingGeneral ClassificationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Human-in-the-Loop Disinformation Detection: Stance, Sentiment, or Something Else?
Both politics and pandemics have recently provided ample motivation for the development of machine learning-enabled disinformation (a.k.a. fake news) detection algorithms. Existing literature has focused primarily on the…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Fake News DetectionSentiment Analysis+1A Cross-Domain Study of the Use of Persuasion Techniques in Online Disinformation
Disinformation, irrespective of domain or language, aims to deceive or manipulate public opinion, typically through employing advanced persuasion techniques. Qualitative and quantitative research on the weaponisation of …
Persuasion StrategiesDisinfoMeme: A Multimodal Dataset for Detecting Meme Intentionally Spreading Out Disinformation
Disinformation has become a serious problem on social media. In particular, given their short format, visual attraction, and humorous nature, memes have a significant advantage in dissemination among online communities, …
Multimodal ReasoningOptical Character Recognition (OCR)Examining European Press Coverage of the Covid-19 No-Vax Movement: An NLP Framework
This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement. Using a curated dataset of 1786 articles from 19 Euro…
ArticlesMisinformationnamed-entity-recognitionNamed Entity Recognition+2EUvsDisinfo: A Dataset for Multilingual Detection of Pro-Kremlin Disinformation in News Articles
This work introduces EUvsDisinfo, a multilingual dataset of disinformation articles originating from pro-Kremlin outlets, along with trustworthy articles from credible / less biased sources. It is sourced directly from t…
Articles