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Personal profile

Research Interests

Ágnes Horvát seeks to measure, understand, and forecast the collective behavior of networked crowds in large-scale sociotechnical systems like peer-to-peer platforms. Her current research develops empirical and theoretical methods to support creativity and predict success in culture industries, identify expressions of collective intelligence and opportunities for innovation in crowdsourcing communities, as well as detect shared misconceptions and biases in online capital markets. Her work work at the intersection of computational social science and social computing uses an interdisciplinary data-driven approach and builds on techniques from network science, machine learning, statistics, and exploratory visualization.

Education/Academic qualification

Physics and Computer Science, BSc, Babes-Bolyai University

Interdisciplinary Physics, PhD, Heidelberg University 

Photography, Film, and Media, BA, Sapientia Hungarian University of Transylvania

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Grants

  • Research Output

    • 246 Citations
    • 13 Article
    • 12 Conference contribution
    • 1 Entry for encyclopedia/dictionary
    • 1 Paper

    (Un)intended consequences of networking on individual and network-level efficiency

    Tanaka, K. & Horvát, E. Á., Dec 1 2019, In : Applied Network Science. 4, 1, 77.

    Research output: Contribution to journalArticle

    Open Access
  • Airbnb’s Reputation System and Gender Differences Among Guests: Evidence from Large-Scale Data Analysis and a Controlled Experiment

    Choi, E. & Horvát, E. Á., Jan 1 2019, Social Informatics - 11th International Conference, SocInfo 2019, Proceedings. Weber, I., Darwish, K. M., Wagner, C., Wagner, C., Flöck, F., Zagheni, E., Aref, S. & Nelson, L. (eds.). Springer, p. 3-17 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11864 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Gender differences in the global music industry: Evidence from MusicBrainz and the Echo Nest

    Wang, Y. & Horvat, E-A., Jan 1 2019, p. 517-526. 10 p.

    Research output: Contribution to conferencePaper

  • Harnessing collective intelligence in P2P lending

    Dambanemuya, H. K. & Horvat, E-A., Jun 26 2019, WebSci 2019 - Proceedings of the 11th ACM Conference on Web Science. Association for Computing Machinery, Inc, p. 57-64 8 p. (WebSci 2019 - Proceedings of the 11th ACM Conference on Web Science).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
  • 1 Scopus citations

    Investor retention in equity crowdfunding

    Zakhlebin, I. & Horvat, E-A., Jun 26 2019, WebSci 2019 - Proceedings of the 11th ACM Conference on Web Science. Association for Computing Machinery, Inc, p. 343-351 9 p. (WebSci 2019 - Proceedings of the 11th ACM Conference on Web Science).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access