Building Community Resources for Censorship Measurement Research

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Building Community Resources for Censorship Measurement Research
Presenter(s) Adam Sent, Maria Xynou
Title(s) Building Community Resources for Censorship Measurement Research
Organization(s) Citizen Lab, OONI
Project(s)
Country(ies)
Social media
2017 theme Tools & Technology

Conducting network measurement research into online information controls (such as censorship) requires an understanding of what types of content are most likely to be blocked in a given jurisdiction. Such knowledge is highly contextual, frequently changing and benefits greatly from local expertise. As a result, it is difficult for any single researcher to have sufficient expertise to inform research conducted across multiple jurisdictions.

In response to this problem, we have created a public repository of country-specific lists of sensitive or potentially censored content, intended for use by the wider information controls research community. This repo (https://github.com/citizenlab/test-lists) is hosted by the Citizen Lab and is based on their work as a part of the OpenNet Initiative project. Alongside researchers from the OONI project, we have been developing these lists for use as a shared resource for the research community.

During this session, we would like to discuss two aspects of this repository. First, we will discuss the practical issues of compiling, organizing, maintaining and using these testing lists in our collective work. Second, we would like to have a broader discussion about best practices, and ways in which we can minimize harm for censorship researchers and those participating in it - particularly those engaged in research in high risk contexts.

We invite information controls researchers, those who use this research as a part of their work, or those with local expertise who wish to contribute to this shared resource to attend our session.

Format Workshop
Target Groups Software Developers, Advocacy/Policy Professional, Academia, Front Line Activists
Length 1 hour
Skill Level Novice
Language English


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