Mirela Riveni

Mirela Riveni is an Assistant Professor at the University of Groningen, working within the Information Systems Group at the Bernoulli Institute, Faculty of Science and Engineering. Her research focuses on network science, social computing, and crowdsourcing, with particular expertise in large-scale network analysis using graph-based algorithms, machine learning, and natural language processing techniques.

Dr. Riveni earned her PhD from the Distributed Systems Group at the Institute of Information Systems, Vienna University of Technology, and completed her M.Sc. in Computer Networks at KTH - The Royal Institute of Technology in Sweden. Her doctoral research focused on provisioning and management mechanisms for automating human computation processes in adaptive systems with humans-in-the-loop.

Her current research interests span several interconnected domains in network science and social computing. She investigates disinformation detection and analysis of (dis)information spreading patterns, particularly focusing on polarization and echo chambers in social networks. A significant portion of her recent work examines information dynamics in decentralized social platforms like Mastodon (the fediverse). She also explores provenance in large-scale network analysis, including code and workflow provenance. Additionally, she studies bias and discrimination issues in recommender systems, with a special emphasis on privacy and ethical considerations in all her research areas.

Dr. Riveni's publication record demonstrates a clear evolution from foundational work in human computation and social computing to her current focus on misinformation analysis and decentralized networks. Her recent publications (2023-2025) show a strong emphasis on analyzing misinformation spread on platforms like Twitter (now X) and Mastodon, with several papers examining echo chambers, adoption dynamics, and growth patterns in decentralized social networks. Her work consistently applies network science metrics, graph-based algorithms, machine learning, and NLP techniques to address these challenges.

Dr. Riveni actively contributes to the academic community through peer review and conference organization. She has served on program committees for conferences including DAIS 2024, ASONAM 2023, and the Workshop on Recommender Systems in Fashion. She has also reviewed for journals such as ACM Computing Surveys, IEEE Internet Transactions on Services Computing, and IEEE Internet Computing.

As an educator, Dr. Riveni teaches courses at both undergraduate and graduate levels, including Introduction to Computing Science, Network Centric Systems, Introduction to Information Systems, Enterprise Application Integration, and Social Network Analysis. She mentors students interested in her research areas and has served as co-supervisor for PhD students.