Online Library

In the context of far-right terrorism, memes on 4chan play a fundamental role. These memes not only serve as a form of propaganda but also as a tool to radicalize and mobilize users. On 4chan, a site known for its lack of moderation and anonymity, memes are used to spread extremist ideologies in a viral and accessible manner. Memes can destabilize and trivialize serious issues, normalizing hate and violence among users. Furthermore, their humorous and accessible format facilitates the spread of radical ideas, making them more appealing and less confrontational. By becoming an integral part of 4chan’s online culture, these memes not only reinforce extremist ideology but also foster a community where violence and hate become acceptable and common topics. This dynamic highlights the importance of addressing the role of memes in the spread of extremism and the need for strategies to counteract their impact.

VOX-Pol Blog post.

We are on the cusp of a “Big Data” Revolution, in which increasingly large datasets are mined for important predictions and often surprising insights. The predictions and decisions this revolution will enable will transform our society in ways comparable to the Industrial Revolution. We are now at a critical moment; big data uses today will be sticky and will settle both default norms and public notions of what is “no big deal” regarding big data predictions for years to come.
This paper argues that big data, broadly defined, is producing increased powers of institutional awareness and power that require the development of a Big Data Ethics. We are building a new digital society, and the values we build or fail to build into our new digital structures will define us. Critically, if we fail to balance the human values that we care about, like privacy, confidentiality, transparency, identity and free choice with the compelling uses of big data, our Big Data Society risks abandoning these values for the sake of innovation and expediency.

VOX-Pol Blog Post.

VOX-Pol Blog Post.

Algorithms and especially recommendation algorithms play an important role online, most notably on YouTube. Yet, little is known about the network communities that these algorithms form. We analyzed the channel recommendations on YouTube to map the communities that the social network is creating through its algorithms and to test the network for homophily, that is, the connectedness between communities. We find that YouTube’s channel recommendation algorithm fosters the creation of highly homophilous communities in the United States (n = 13,529 channels) and in Germany (n = 8,000 channels). Factors that seem to drive YouTube’s recommendations are topics, language, and location. We highlight the issue of homophilous communities in the context of politics where YouTube’s algorithms create far-right communities in both countries.