Social media is an area where users often experience censorship through a variety of means such as the restriction of search terms or active and retroactive deletion of messages. In this paper we examine the feasibility of automatically detecting censorship of microblogs. We use a network growing model to simulate discussion over a microblog follow network and compare two censorship strategies to simulate varying levels of message deletion. Using topological features extracted from the resulting graphs, a classifier is trained to detect whether or not a given communication graph has been censored. The results show that censorship detection is feasible under empirically measured levels of message deletion. The proposed framework can enable automated censorship measurement and tracking, which, when combined with aggregated citizen reports of censorship, can allow users to make informed decisions about online communication habits.
Despite these important works, no research to date has explored the effects of censorship on the underlying structure of the network and furthermore no research exists that attempts to automatically detect and classify censorship in these networks. Given that online social networks have certain universal properties @cite_8 , it is likely that common strategies of censorship such as limiting or deleting content or users from the network would have measurable effects on these properties. This research constitutes a first step to fill this gap by studying these effects.
@cite_8
1830741683
Over the years, the Internet has democratized the flow of information. Unfortunately, in parallel, authoritarian regimes and other entities (such as ISPs) for their vested interests have curtailed this flow by partially or fully censoring the web. The policy, mechanism, and extent of this censorship varies from country to country. We present the first study of the cause, effect, and mechanism of web censorship in Pakistan. Specifically, we use a publicly available list of blocked websites and check their accessibility from multiple networks within the country. Our results indicate that the censorship mechanism varies across websites: some are blocked at the DNS level while others at the HTTP level. Interestingly, the government shifted to a centralized, Internet exchange level censorship system during the course of our study, enabling our findings to compare two generations of blocking systems. Furthermore, we report the outcome of a controlled survey to ascertain the mechanisms that are being actively employed by people to circumvent censorship. Finally, we discuss some simple but surprisingly unexplored methods of bypassing restrictions.