Spatiotemporal analysis of censored content on Twitter
Onur Varol · 2016
Social media have become vehicles for instantly disseminating and accessing information on a global scale. Beside such positive contributions, social media also enable malicious activities such as recruitment for terrorist groups or coordinate orchestrated campaigns. Censorship is one way of limiting user activities, but applying it fairly is not easy, as exemplified by site-blocking censorship by governments. To avoid complete site-blocking, some social media sites have complied with requests by governments for content removal or partial censorship. In this study, we analyzed our collection of more than 100,000 tweets that were either censored tweets or retweeted censored content. We showed variability in audience location using time zone and language preferences as proxies, which is not bounded by geographic location of the censorship. We show that most of the time content find its way to disseminate and reach broader audience even with the censorship.