How We Express Ourselves Freely: Censorship, Self-censorship, and Anti-censorship on a Chinese Social Media

Censorship, anti-censorship, and self-censorship in an authoritarian regime have been extensively studies, yet the relationship between these intertwined factors is not well understood. In this paper, we report results of a large-scale survey study (N = 526) with Sina Weibo users toward bridging this research gap. Through descriptive statistics, correlation analysis, and regression analysis, we uncover how users are being censored, how and why they conduct self-censorship on different topics and in different scenarios (i.e., post, repost, and comment), and their various anti-censorship strategies. We further identify the metrics of censorship and self-censorship, find the influence factors, and construct a mediation model to measure their relationship. Based on these findings, we discuss implications for democratic social media design and future censorship research.Comment: iConference 2023 has accepte

Linguistic Characteristics of Censorable Language on SinaWeibo

This paper investigates censorship from a linguistic perspective. We collect a corpus of censored and uncensored posts on a number of topics, build a classifier that predicts censorship decisions independent of discussion topics. Our investigation reveals that the strongest linguistic indicator of censored content of our corpus is its readability

Apollo: A System for Tracking Internet Censorship

If it remains debatable whether the Internet has surpassed print media in making information accessible to the public, then it must nevertheless be conceded that the Internet makes the manipulation and censorship of information easier than had been on the printed page. In coming years and in an increasing number of countries, everyday producers and consumers of online information will likely have to cultivate a sense of censorship. It behooves the online community to learn how to detect and evade interference by governments, regimes, corporations, con-artists, and vandals. The contribution of this research is to describe a method and platform to study Internet censorship detection and evasion. This paper presents the concepts, initial theories, and future work

Circumvention of censorship of internet access and publication

Internet censorship of one form or another affects on the order of half of all internet users. Previous work has studied this censorship, and proposed techniques for circumventing it, ranging from making proxy servers available to censored users, to tunneling internet connections through services such as voice or video chat, to embedding censorship circumvention in cloud platforms' front-end servers or even in ISP's routers. This dissertation describes a set of techniques for circumventing internet censorship building on and surpassing prior efforts. As is always the case, there are tradeoffs to be made: some of this work emphasizes deployability, and some aims for unstoppable circumvention with the assumption of significant resources. However, the latter techniques are not merely academic thought experiments: this dissertation also describes the experience of successfully deploying such a technique, which served tens of thousands of users. While the solid majority of previous work, as well as much of the work presented here, is focused on governments blocking access to sites and services hosted outside of their country, the rise of social media has created a new form of internet censorship. A country may block a social media platform, but have its own domestic version, on which it tightly controls what can be said. This dissertation describes a system for enabling users of such a platform to monitor for post deletions, and distribute the contents to other users

Algorithmically Bypassing Censorship on Sina Weibo with Nondeterministic Homophone Substitutions

Like traditional media, social media in China is subject to censorship. However, in limited cases, activists have employed homophones of censored keywords to avoid detection by keyword matching algorithms. In this paper, we show that it is possible to scale this idea up in ways that make it difficult to defend against. Specifically, we present a non-deterministic algorithm for generating homophones that create large numbers of false positives for censors, making it difficult to locate banned conversations. In two experiments, we show that 1) homophone-transformed weibos posted to Sina Weibo remain on-site three times longer than their previously censored counterparts, and 2) native Chinese speakers can recover the original intent behind the homophone-transformed messages, with 99% of our posts understood by the majority of our participants. Finally, we find that coping with homophone transformations is likely to cost the Sina Weibo censorship apparatus an additional 15 hours of human labor per day, per censored keyword. To conclude, we reflect briefly on the opportunities presented by this algorithm to build interactive, client-side tools that promote free speech

A critical examination of incitement to terrorism laws and speech regulatory practices in the post-9/11-7/7 continuum

PhD ThesisThe preponderance of thinking in UK counterterrorism circles is that speech that incites terrorism (at least online) is not only a contributor to terrorism but it is also a form of terrorism/radicalisation/extremism in and of itself. Thus, there is a perceived need to preemptively suppress such speech. Accordingly, counterterrorism laws and regimes in the post 9/11-7/7 era are marked with a distinct urgency or vigilance that seeks to pre-empt speech that incites terrorism. However, inasmuch as these incitement to terrorism legal and regulatory regimes (e.g., the incitement to terrorism provisions under the Terrorism Act 2000, the Terrorism Act 2006 and the Public Order Act 1986) appear to be stable, they are still marked with traces of indeterminability or undecidability that not only expand law’s exclusionary violence but also makes law self-inadequating. Such traces of undecidability are reflected in the opacity of the law and its overlaps with other criminal laws such as soliciting murder, malicious communications and incitement to racial hatred. Another key trace of undecidability is evident in the arena of online regulation, which seems to flounder in the sense that it struggles to contain the cross-territorial ephemerality and polyphony of online speech. Consequently, this thesis seeks to examine and verify two hypothetical claims, that: 1) speech that incites terrorism cannot be contained because speech is inherently divergent and iterable. In this sense, regulating speech is thus inescapably confusing, mistake-laden (e.g. with false positives online) and inoperable at times; and 2) incitement to terrorism legal provisions and policies as well as the fair balancing principles of human rights law are undecidable and self-inadequating because they are irretrievably troubled by aporetic conceptual operations. In an attempt to destabilise the calculability and stability that pervades much of contemporary thinking on incitement to terrorism regulation enforcement and criminalisation in the UK. These claims are critically unpacked through the concept of hauntology, a deconstructive concept derived from critically engaging with Jacques Derrida’s scholarship on spectres, différance, dissemination, autoimmunity and undecidability. By showing that incitement to terrorism laws and practices bear the deep imprint of a pervasive lack of definitive determinability, this thesis allows for the tentative ethical possibility of reconfiguring what calculable absolutist frames of “incitement to terrorism”, law enforcement, and regulation currently disavow

The laws of "LOL": Computational approaches to sociolinguistic variation in online discussions

When speaking or writing, a person often chooses one form of language over another based on social constraints, including expectations in a conversation, participation in a global change, or expression of underlying attitudes. Sociolinguistic variation (e.g. choosing "going" versus "goin'") can reveal consistent social differences such as dialects and consistent social motivations such as audience design. While traditional sociolinguistics studies variation in spoken communication, computational sociolinguistics investigates written communication on social media. The structured nature of online discussions and the diversity of language patterns allow computational sociolinguists to test highly specific hypotheses about communication, such different configurations of listener "audience." Studying communication choices in online discussions sheds light on long-standing sociolinguistic questions that are hard to tackle, and helps social media platforms anticipate their members' complicated patterns of participation in conversations. To that end, this thesis explores open questions in sociolinguistic research by quantifying language variation patterns in online discussions. I leverage the "birds-eye" view of social media to focus on three major questions in sociolinguistics research relating to authors' participation in online discussions. First, I test the role of conversation expectations in the context of content bans and crisis events, and I show that authors vary their language to adjust to audience expectations in line with community standards and shared knowledge. Next, I investigate language change in online discussions and show that language structure, more than social context, explains word adoption. Lastly, I investigate the expression of social attitudes among multilingual speakers, and I find that such attitudes can explain language choice when the attitudes have a clear social meaning based on the discussion context. This thesis demonstrates the rich opportunities that social media provides for addressing sociolinguistic questions and provides insight into how people adapt to the communication affordances in online platforms.Ph.D