Damian Trilling

According to our database, Damian Trilling authored at least 16 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Network toxicity analysis: an information-theoretic approach to studying the social dynamics of online toxicity.

Rupert Kiddle, Petter Törnberg, Damian Trilling

J. Comput. Soc. Sci., April, 2024

Searching differently? How political attitudes impact search queries about political issues.

Marieke van Hoof, Corine S. Meppelink, Judith Möller, Damian Trilling

New Media Soc., 2024

Contextualized Word Embeddings Expose Ethnic Biases in News.

Guusje Thijs, Damian Trilling, Anne C. Kroon

Proceedings of the 16th ACM Web Science Conference, 2024

Perception versus Reality: Evaluating User Awareness of Political Selective Exposure in News Recommender Systems.

Alain Starke, Anders Sandvik Bremnes, Erik Knudsen, Damian Trilling, Christoph Trattner

Proceedings of the Adjunct Proceedings of the 32nd ACM Conference on User Modeling, 2024

2023

Effects of an issue-based microtargeting campaign: A small-scale field experiment in a multi-party setting.

Tom Dobber, Damian Trilling, Natali Helberger, Claes H. de Vreese

Inf. Soc., 2023

Refining Deliberative Standards for Online Political Communication: Introducing a Summative Approach to Designing Deliberative Recommender Systems.

Sjoerd B. Stolwijk, Corinna Oschatz, Michael Heseltine, Damian Trilling

Proceedings of the First Workshop on the Normative Design and Evaluation of Recommender Systems (NORMalize 2023) co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

Enabling Serendipitous News Discovery Experiences by Designing for Navigable Surprise.

Rupert Kiddle, Kasper Welbers, Anne C. Kroon, Damian Trilling

Proceedings of the First Workshop on the Normative Design and Evaluation of Recommender Systems (NORMalize 2023) co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

Beyond Discrete Genres: Mapping News Items onto a Multidimensional Framework of Genre Cues.

Zilin Lin, Kasper Welbers, Susan Vermeer, Damian Trilling

Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, 2023

Understanding How News Recommender Systems Influence Selective Exposure.

Khadiga M. A. Seddik, Erik Knudsen, Damian Trilling, Christoph Trattner

Proceedings of the International Workshop on Behavior Change and Persuasive Recommender Systems co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

2021

Understanding the link between audience engagement metrics and the perceived quality of online news using machine learning.

Catherine Sotirakou, Damian Trilling, Panagiotis Germanakos, Dimitrios Alexandros Sinis, Constantinos Mourlas

Web Intell., 2021

Is this a click towards diversity? Explaining when and why news users make diverse choices.

Felicia Loecherbach, Kasper Welbers, Judith Möller, Damian Trilling, Wouter van Atteveldt

Proceedings of the WebSci '21: 13th ACM Web Science Conference 2021, 2021

2019

Spiraling downward: The reciprocal relation between attitude toward political behavioral targeting and privacy concerns.

Tom Dobber, Damian Trilling, Natali Helberger, Claes H. de Vreese

New Media Soc., 2019

Opening the black box of perceived quality: Predicting endorsement on a blog site.

Catherine Sotirakou, Damian Trilling, Panagiotis Germanakos, Constantinos Mourlas

Proceedings of the 2019 IEEE/WIC/ACM International Conference on Web Intelligence, 2019

2018

INCA: Infrastructure for Content Analysis.

Damian Trilling, Bob van de Velde, Anne C. Kroon, Felicia Löcherbach, Theo B. Araujo, Joanna Strycharz, Tamara Raats, Lisa De Klerk, Jeroen G. F. Jonkman

Proceedings of the 14th IEEE International Conference on e-Science, 2018

3bij3: A Framework for Testing Effects of Recommender Systems on News Exposure.

Felicia Löcherbach, Damian Trilling

Proceedings of the 14th IEEE International Conference on e-Science, 2018

2017

Political relevance in the eye of the beholder: Determining the substantiveness of TV shows and political debates with Twitter data.

Mark Boukes, Damian Trilling

First Monday, 2017