output
19982026
most citedLearning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle

200 citations

Showing cs.SIShow all

13 papers · 1 filter

cs.SI2024

Recommendation Fairness in Social Networks Over Time

Meng Cao, Hussain Hussain, Sandipan Sikdar +3

In social recommender systems, it is crucial that the recommendation models provide equitable visibility for different demographic groups, such as gender or race. Most existing res…

cs.SI2022

Fast generation of simple directed social network graphs with reciprocal edges and high clustering

Christoph Schweimer

Online social networks have emerged as useful tools to communicate or share information and news on a daily basis. One of the most popular networks is Twitter, where users connect…

cs.SI2022★ 22 cited

Generating Simple Directed Social Network Graphs for Information Spreading

Christoph Schweimer, Christine Gfrerer, Florian Lugstein +4

Online social networks are a dominant medium in everyday life to stay in contact with friends and to share information. In Twitter, users can connect with other users by following…

cs.SI2021★ 9 cited

My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music

Tomislav Duricic, Dominik Kowald, Markus Schedl +1

Homophily describes the phenomenon that similarity breeds connection, i.e., individuals tend to form ties with other people who are similar to themselves in some aspect(s). The sim…

cs.SI2021★ 1 cited

Cross-platform analysis of user comments in YouTube videos linked on Reddit conspiracy theory forum

Tomislav Duricic, Volker Seiser, Elisabeth Lex

We perform a cross-platform analysis in which we study how does linking YouTube content on Reddit conspiracy forum impact language used in user comments on YouTube. Our findings sh…

cs.SI2021★ 10 cited

Studying Moral-based Differences in the Framing of Political Tweets

Markus Reiter-Haas, Simone Kopeinik, Elisabeth Lex

In this paper, we study the moral framing of political content on Twitter. Specifically, we examine differences in moral framing in two datasets: (i) tweets from US-based politicia…