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
Proceedings ArticleDOI
SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours
Genevieve Gorrell,Elena Kochkina,Maria Liakata,Ahmet Aker,Arkaitz Zubiaga,Kalina Bontcheva,Leon Derczynski +6 more
TL;DR: The second edition of the RumourEval shared task as discussed by the authors focused on stance prediction and veracity assessment of rumours on Twitter and Reddit, with a dataset of dubious posts and ensuing conversations.
Journal ArticleDOI
Rumor Gauge: Predicting the Veracity of Rumors on Twitter
TL;DR: The ability to track rumors and predict their outcomes may have practical applications for news consumers, financial markets, journalists, and emergency services, and more generally to help minimize the impact of false information on Twitter.
Journal ArticleDOI
Sentiment analysis during Hurricane Sandy in emergency response
TL;DR: It is found that extracting sentiments during a disaster may help emergency responders develop stronger situational awareness of the disaster zone itself and help them understand the dynamics of the network.
Book
Social Sensing: Building Reliable Systems on Unreliable Data
TL;DR: Social Sensing: Building Reliable Systems on Unreliable Data looks at recent advances in the emerging field of social sensing, emphasizing the key problem faced by application designers: how to extract reliable information from data collected from largely unknown and possibly unreliable sources.
Proceedings ArticleDOI
$1.00 per RT #BostonMarathon #PrayForBoston: Analyzing fake content on Twitter
TL;DR: The aim of this work is to perform in-depth characterization of what factors influenced in malicious content and profiles becoming viral on Twitter, and found that large number of users with high social reputation and verified accounts were responsible for spreading the fake content.
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.