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
Multi-Modal Meta Multi-Task Learning for Social Media Rumor Detection
TL;DR: Zhang et al. as mentioned in this paper designed a multi-modal meta multi-task learning (MM-MTL) framework for social media rumor detection, which considers both textual and visual content.
Journal ArticleDOI
IFND: a benchmark dataset for fake news detection
Dilip Kumar Sharma,Sonal Garg +1 more
TL;DR: In this paper, a large-scale dataset named Indian fake news dataset (IFND) is presented, which consists of both text and images and the majority of the content in the dataset is about events from the year 2013 to the year 2021.
Journal ArticleDOI
The Influence of Collective Opinion on True-False Judgment and Information-Sharing Decision
Huaye Li,Yasuaki Sakamoto +1 more
TL;DR: The results of Experiment 1 revealed that the crowd adopted the collective credibility judgment when evaluating the credibility of a statement and the crowd followed the collective sharing likelihood when rating the likelihood of sharing a statement.
Journal Article
TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter
Katrin Hartwig,Christian Reuter +1 more
TL;DR: The browser-plugin TrusyTweet is designed and implemented, which assists users on Twitter in assessing tweets by showing politically neutral and intuitive warnings without creating reactance, and leads to further design implications for approachesto assist users in dealing with fake news.
Journal ArticleDOI
Getting their Voice Heard: Chinese Environmental NGO’s Weibo Activity and Information Sharing
Nan Zhang,Marko M. Skoric +1 more
TL;DR: This article examined Chinese environmental nongovernmental organizations' use of a microblogging platform Weibo and the factors that contribute to sharing of their messages by employing the Weibo platform.
References
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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.