The emergence of online widescale interaction in unexpected events: assistance, alliance & retreat
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Detecting spammers and content promoters in online video social networks
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 2009 International Workshop on Location Based Social Networks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
Proceedings of the 2010 ACM-BCS Visions of Computer Science Conference
WOSN'10 Proceedings of the 3rd conference on Online social networks
@spam: the underground on 140 characters or less
Proceedings of the 17th ACM conference on Computer and communications security
Truthy: mapping the spread of astroturf in microblog streams
Proceedings of the 20th international conference companion on World wide web
Information credibility on twitter
Proceedings of the 20th international conference on World wide web
Twitter under crisis: can we trust what we RT?
Proceedings of the First Workshop on Social Media Analytics
Information control and terrorism: Tracking the Mumbai terrorist attack through twitter
Information Systems Frontiers
Phi.sh/$oCiaL: the phishing landscape through short URLs
Proceedings of the 8th Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference
Tweet trend analysis in an emergency situation
Proceedings of the Special Workshop on Internet and Disasters
Tweeting is believing?: understanding microblog credibility perceptions
Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work
Credibility ranking of tweets during high impact events
Proceedings of the 1st Workshop on Privacy and Security in Online Social Media
Understanding and combating link farming in the twitter social network
Proceedings of the 21st international conference on World Wide Web
Proceedings of the 21st international conference on World Wide Web
Information credibility on twitter in emergency situation
PAISI'12 Proceedings of the 2012 Pacific Asia conference on Intelligence and Security Informatics
Cognos: crowdsourcing search for topic experts in microblogs
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Credibility in Context: An Analysis of Feature Distributions in Twitter
SOCIALCOM-PASSAT '12 Proceedings of the 2012 ASE/IEEE International Conference on Social Computing and 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust
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In today's world, online social media plays a vital role during real world events, especially crisis events. There are both positive and negative effects of social media coverage of events, it can be used by authorities for effective disaster management or by malicious entities to spread rumors and fake news. The aim of this paper, is to highlight the role of Twitter, during Hurricane Sandy (2012) to spread fake images about the disaster. We identified 10,350 unique tweets containing fake images that were circulated on Twitter, during Hurricane Sandy. We performed a characterization analysis, to understand the temporal, social reputation and influence patterns for the spread of fake images. Eighty six percent of tweets spreading the fake images were retweets, hence very few were original tweets. Our results showed that top thirty users out of 10,215 users (0.3%) resulted in 90% of the retweets of fake images; also network links such as follower relationships of Twitter, contributed very less (only 11%) to the spread of these fake photos URLs. Next, we used classification models, to distinguish fake images from real images of Hurricane Sandy. Best results were obtained from Decision Tree classifier, we got 97% accuracy in predicting fake images from real. Also, tweet based features were very effective in distinguishing fake images tweets from real, while the performance of user based features was very poor. Our results, showed that, automated techniques can be used in identifying real images from fake images posted on Twitter.