Proceedings ArticleDOI
Information credibility on twitter
Carlos Castillo,Marcelo Mendoza,Barbara Poblete +2 more
- pp 675-684
TLDR
There are measurable differences in the way messages propagate, that can be used to classify them automatically as credible or not credible, with precision and recall in the range of 70% to 80%.Abstract:
We analyze the information credibility of news propagated through Twitter, a popular microblogging service. Previous research has shown that most of the messages posted on Twitter are truthful, but the service is also used to spread misinformation and false rumors, often unintentionally.On this paper we focus on automatic methods for assessing the credibility of a given set of tweets. Specifically, we analyze microblog postings related to "trending" topics, and classify them as credible or not credible, based on features extracted from them. We use features from users' posting and re-posting ("re-tweeting") behavior, from the text of the posts, and from citations to external sources.We evaluate our methods using a significant number of human assessments about the credibility of items on a recent sample of Twitter postings. Our results shows that there are measurable differences in the way messages propagate, that can be used to classify them automatically as credible or not credible, with precision and recall in the range of 70% to 80%.read more
Citations
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Journal ArticleDOI
Impact of information timeliness and richness on public engagement on social media during COVID-19 pandemic: An empirical investigation based on NLP and machine learning
TL;DR: Wang et al. as discussed by the authors investigated how information timeliness and richness affect public engagement using text data from China's largest social media platform during times of the COVID-19 pandemic.
Proceedings ArticleDOI
Towards a truthful world wide web from a humanitarian perspective
Vishnu Pendyala,Silvia Figueira +1 more
TL;DR: The role that a truthful World Wide Web can play in achieving humanitarian goals is discussed and what is currently available is surveyed and some of the own ideas on making the Web more robust and truthful in order to meet the humanitarian challenge are discussed.
Proceedings ArticleDOI
Does Being Verified Make You More Credible?: Account Verification's Effect on Tweet Credibility
TL;DR: Surprisingly, across both studies, it is found that most users can effectively distinguish between authenticity and credibility, and the presence or absence of an authenticity indicator has no significant effect on willingness to share a tweet or take action based on its contents.
Proceedings Article
Finding true and credible information on Twitter
Sujoy Sikdar,Sibel Adali,Md. Tanvir Al Amin,Tarek Abdelzaher,Kevin S. Chan,Jin-Hee Cho,Byungkyu Kang,John O'Donovan +7 more
TL;DR: This paper presents a unique study of two successful methods for computing message reliability based on machine learning and attempts to find a predictive model based on network features and illustrates how they can be fused to capture the trade off between favoring true versus credible messages.
Journal ArticleDOI
Rumormongering of genetically modified (GM) food on Chinese social network
TL;DR: Results revealed that people who hold negative attitudes towards GM food and who are social media extraverts are more likely to spread rumors, while social reputation did not influence the spread of rumors.
References
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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