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
More filters
Journal ArticleDOI
Automatic controversy detection in social media: A content-independent motif-based approach
TL;DR: It is shown that it is possible to detect controversy in social media by exploiting network motifs, i.e., local patterns of user interaction, which allows for a language-independent and fine-grained analysis of user discussions and their evolution over time.
Book ChapterDOI
Extreme User and Political Rumor Detection on Twitter
TL;DR: This paper proposes a rule-based method for detecting political rumors on Twitter based on identifying extreme users, and employs clustering methods to identify news tweets and unsupervised classification methods for the detection of extreme users.
Proceedings ArticleDOI
On the subjectivity and bias of web content credibility evaluations
TL;DR: It is found that evaluations of Web content credibility are slightly subjective and on the other hand, the evaluations exhibit a strong acquiescence bias.
Posted Content
Fact Checking in Community Forums
Tsvetomila Mihaylova,Preslav Nakov,Lluís Màrquez,Alberto Barrón-Cedeño,Mitra Mohtarami,Georgi Karadzhov,James Glass +6 more
TL;DR: A novel multi-faceted model is proposed, which captures information from the answer content (what is said and how), from the author profile, from the rest of the community forum (where it is said), and from external authoritative sources of information (external support).
Journal ArticleDOI
A model for recalibrating credibility in different contexts and languages - a twitter case study
TL;DR: A general model to assess information credibility on UGC different platforms, including Twitter, is proposed, which employs a contextual credibility approach that examines the effect of culture, situation, topic variations, and languages on assessing credibility, using Arabic context as an example.
References
More filters
Proceedings ArticleDOI
What is Twitter, a social network or a news media?
TL;DR: In this paper, the authors have crawled the entire Twittersphere and found a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks.
Proceedings ArticleDOI
Earthquake shakes Twitter users: real-time event detection by social sensors
TL;DR: This paper investigates the real-time interaction of events such as earthquakes in Twitter and proposes an algorithm to monitor tweets and to detect a target event and produces a probabilistic spatiotemporal model for the target event that can find the center and the trajectory of the event location.
Proceedings ArticleDOI
Why we twitter: understanding microblogging usage and communities
TL;DR: It is found that people use microblogging to talk about their daily activities and to seek or share information and the user intentions associated at a community level are analyzed to show how users with similar intentions connect with each other.
Proceedings ArticleDOI
Microblogging during two natural hazards events: what twitter may contribute to situational awareness
TL;DR: Analysis of microblog posts generated during two recent, concurrent emergency events in North America via Twitter, a popular microblogging service, aims to inform next steps for extracting useful, relevant information during emergencies using information extraction (IE) techniques.
Proceedings ArticleDOI
Finding high-quality content in social media
TL;DR: This paper introduces a general classification framework for combining the evidence from different sources of information, that can be tuned automatically for a given social media type and quality definition, and shows that its system is able to separate high-quality items from the rest with an accuracy close to that of humans.