Ben Thies

Humboldt-Universität zu Berlin | HU Berlin · Department of Economics

Twitter continuously tightens the access to its data via the publicly accessible, cost-free standard APIs. This especially applies to the follow network. In light of this, we successfully modified a network sampling method to work efficiently with the Twitter standard API in order to retrieve the most central and influential accounts of a language-...

The prerequisite of many approaches to authorship analysis is a representation of writing style. But despite decades of research, it still remains unclear to what extent commonly used and widely accepted representations like character trigram frequencies actually represent an author's writing style, in contrast to more domain-specific style compone...

Social bots are undermining trust in social media. They spread low-credibility content, fake news, and spam. However, most research is based on bots that actively share links or keywords, rather than assessing the longer-term presence of bots as an integral part of platforms. To address this gap, we present what to our knowledge is the first study...

https://arxiv.org/abs/1908.07788 Twitter continuously tightens the access to its data via the publicly accessible, cost-free standard APIs. This especially applies to the follow network. In light of this, we successfully modified a network sampling method to work efficiently with the Twitter standard API in order to retrieve the most central and...

Rank Degree Influencer Core Sampler (RaDICeS). Project prototype to create sparsified sample follow networks of Twitter Users via the Twitter standard API.

Zur Erklärung der Dynamik öffentlicher Diskurse im digitalen Zeitalter muss immer häufiger der Begriff „Filter Bubble“ herhalten. Dem Theorem, mehr eine Chiffre für die subtilen Machtstrukturen im Internet, fehlt jedoch die empirische Fundierung.