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Proceedings ArticleDOI

Information credibility on twitter

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%.

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Journal ArticleDOI

Extending the knowledge base of foresight: The contribution of text mining

TL;DR: Exploring the potential of text mining for foresight by considering different data sources, text mining approaches, and foresight methods shows that text mining facilitates the detection and examination of emerging topics and technologies by extending the knowledge base of foresight.
Posted Content

Predicting Factuality of Reporting and Bias of News Media Sources

TL;DR: In this paper, the authors present a study on predicting the factuality of reporting and bias of news media using a set of features derived from a sample of articles from the target news medium, including Wikipedia page, Twitter account, and the structure of its URL.
Journal ArticleDOI

Good Enough is Good Enough: Overcoming Disaster Response Organizations' Slow Social Media Data Adoption

TL;DR: It is found that emergency responders already operate with less than reliable, or “good enough,” information in offline practice, and that social media data are useful to responders, but only in specific crisis situations, shows that trust first begins with people and not data.
Posted Content

Integrating Stance Detection and Fact Checking in a Unified Corpus

TL;DR: This paper supports the interdependencies between fact checking, document retrieval, source credibility, stance detection and rationale extraction as annotations in the same corpus and implements this setup on an Arabic fact checking corpus, the first of its kind.
Proceedings ArticleDOI

Combating Rumor Spread on Social Media: The Effectiveness of Refutation and Warning

TL;DR: Results have shown that exposing people to information that refutes rumors or warns that the statement has appeared on rumor websites could reduce the spread of rumors, and suggest that social media technologies can be designed such that users can self correct and inactivate potentially inaccurate information in their environment.
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.
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