Social media have become part of modern news reporting, used by journalists to spread information and find sources, or as a news source by individuals. The quest for prominence and recognition on social media sites like Twitter can sometimes eclipse accuracy and lead to the spread of false information. As a way to study and react to this trend, we introduce TwitterTrails , an interactive, web-based tool ( twittertrails.com ) that allows users to investigate the origin and propagation characteristics of a rumor and its refutation, if any, on Twitter. Visualizations of burst activity, propagation timeline, retweet and co-retweeted networks help its users trace the spread of a story. Within minutes TwitterTrails will collect relevant tweets and automatically answer several important questions regarding a rumor: its originator, burst characteristics, propagators and main actors according to the audience. In addition, it will compute and report the rumor's level of visibility and, as an example of the power of crowdsourcing, the audience's skepticism towards it which correlates with the rumor's credibility. We envision TwitterTrails as valuable tool for individual use, but we especially for amateur and professional journalists investigating recent and breaking stories. Further, its expanding collection of investigated rumors can be used to answer questions regarding the amount and success of misinformation on Twitter.
One of the earliest systems that focused on studying patterns of information propagation in online social networks like Twitter is Truthy @cite_19 . Truthy is based on the concept of memes that spread in the network. Such memes are detected and followed over time to capture their diffusion patterns. Truthy is a more general-purpose system than the ones we mentioned previously in this section, which, despite its name, it doesn't provide explicit assessment of the veracity of the tracked memes. However, through visualizations of propagation patterns and other metrics (e.g., sentiment analysis), Truthy can enable a user to come to a certain conclusion on her own.
@cite_19
2100974526
Online social media are complementing and in some cases replacing person-to-person social interaction and redefining the diffusion of information. In particular, microblogs have become crucial grounds on which public relations, marketing, and political battles are fought. We demonstrate a web service that tracks political memes in Twitter and helps detect astroturfing, smear campaigns, and other misinformation in the context of U.S. political elections. We also present some cases of abusive behaviors uncovered by our service. Our web service is based on an extensible framework that will enable the real-time analysis of meme diffusion in social media by mining, visualizing, mapping, classifying, and modeling massive streams of public microblogging events.