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
A Hybrid Linguistic and Knowledge-Based Analysis Approach for Fake News Detection on Social Media
TL;DR: Wang et al. as mentioned in this paper proposed a hybrid fake news detection system that combines linguistic and knowledge-based approaches and inherits their advantages, by employing two different sets of features: (1) linguistic features (i.e., title, number of words, reading ease, lexical diversity, and sentiment), and (2) a novel set of knowledgebased features, called fact-verification features that comprise three types of information namely, (i>reputation of the website where the news is published, (ii) coverage, and (iii) fact-check), i.e.
Proceedings ArticleDOI
Towards a social media analytics platform: event detection and user profiling for twitter
TL;DR: The proposed tutorial on social analytics for Twitter will discuss research efforts towards detection of events from Twitter using both the tweet content as well as other external sources, and focus on describing events using the best phrase, event type, event timespan, and credibility.
Journal ArticleDOI
Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learning
TL;DR: This paper proposes an adversarial contrastive learning framework to detect rumors by adapting the features learned from well-resourced rumor data to that of the low- Resourced regime, and develops a adversarial augmentation mechanism to further enhance the robustness of low-resource rumor representation.
Dissertation
The credibility of the news on social networking sites among Jordanian journalists
TL;DR: This article examined the relationship between traditional factors in media, acceptance to use of technology, interactive media, quality of news source, exposure to SNS, and scoop with the credibility of news.
Book ChapterDOI
On Rumor Source Detection and Its Experimental Verification on Twitter
Dariusz Król,Karolina Wiśniewska +1 more
TL;DR: An empirical investigation of finding the position of the rumor-teller, calculating the length of propagation path and using statistical methods to interpret and then report basic results showed that the initial rumor users are not able to separate the most influential spreaders in the small networks.
References
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Proceedings ArticleDOI
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