Emoke-Agnes Horvat

  • 209 Citations
20102020
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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 University

Fingerprint Fingerprint is based on mining the text of the experts' scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

Throughput Chemical Compounds
MicroRNAs Medicine & Life Sciences
social networks Agriculture & Biology
microRNA Agriculture & Biology
Social Support Medicine & Life Sciences
Benchmarking Medicine & Life Sciences
Cell Cycle Proteins Medicine & Life Sciences
Systems Biology Medicine & Life Sciences

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Grants 2018 2020

Learning systems
Students
Economics
Online systems
Complex networks

Research Output 2010 2019

  • 209 Citations
  • 12 Article
  • 7 Conference contribution
  • 1 Entry for encyclopedia/dictionary

Networking strategies and efficiency in human communication networks

Tanaka, K. & Horvat, E-A., Jan 1 2019, Complex Networks and Their Applications VII - Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018. Aiello, L. M., Cherifi, H., Lió, P., Rocha, L. M., Cherifi, C. & Lambiotte, R. (eds.). Springer Verlag, p. 258-270 13 p. (Studies in Computational Intelligence; vol. 813).

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

Telecommunication networks
Information theory
Heterogeneous networks
Communication
Computer simulation
1 Citation (Scopus)

Network signatures of success: Emulating expert and crowd assessment in science, art, and technology

Zakhlebin, I. & Horvat, E-A., Jan 1 2018, Complex Networks and Their Applications VI - Proceedings of Complex Networks 2017 (The 6th International Conference on Complex Networks and Their Applications). Cherifi, H., Cherifi, C., Musolesi, M. & Karsai, M. (eds.). Springer Verlag, p. 437-449 13 p. (Studies in Computational Intelligence; vol. 689).

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

Availability
Experiments

Peer-to-peer lending and bias in crowd decision-making

Singh, P., Uparna, J., Karampourniotis, P., Horvat, E-A., Szymanski, B., Korniss, G., Bakdash, J. Z. & Uzzi, B., Mar 1 2018, In : PloS one. 13, 3, e0193007.

Research output: Contribution to journalArticle

peers
decision making
Shock
Decision Making
Decision making
3 Citations (Scopus)

Assessing low-intensity relationships in complex networks

Spitz, A., Gimmler, A., Stoeck, T., Zweig, K. A. & Horvat, E-A., Apr 1 2016, In : PLoS One. 11, 4, e0152536.

Research output: Contribution to journalArticle

Benchmarking
Systems Biology
Complex networks
Plankton
Social Media
10 Citations (Scopus)

Different flavors of randomness: comparing random graph models with fixed degree sequences

Schlauch, W. E., Horvat, E-A. & Zweig, K. A., Jan 1 2015, In : Social Network Analysis and Mining. 5, 1, p. 1-14 14 p., 36.

Research output: Contribution to journalArticle

Flavors
statistical significance