printHyperlink Network Analysis:
Methodological Possibilities for Studying AI Partnerships
Barkhatova L.A.
Cand. Sci. (Sociol.), Assoc. Prof. of the Department of Sociological Research Methods, School of Sociology, Faculty of Social Sciences, HSE University, Moscow, Russia lbarhatova@hse.ru
Barkhatova L.A. Hyperlink Network Analysis: Methodological Possibilities for Studying AI Partnerships. Sotsiologicheskie issledovaniya [Sociological Studies]. 2026. No 5. P. 71-83
The article conceptualizes the methodological potential of hyperlink network analysis as a tool of empirical reconstruction of social interaction through digital traces. Using the partnership network of Russia’s artificial intelligence (AI) ecosystem as a case, the paper presents an original analytical framework for translating technical hyperlink data into sociological categories. The study describes a full data processing cycle, including a contextualization stage through manual verification of hyperlink content. A combination of network analysis techniques (density, centrality, clustering) enables a “dual optics” approach to measuring partnerships: through institutional prestige (in-degree) and network activity (outdegree) of actors. The identified structure of 18 clusters demonstrates a distributed model of the AI ecosystem, where low network density is counterbalanced by the specialization of autonomous niches. Particular emphasis is placed on interpreting micro-clusters as “weak signals” of new market trends. The proposed instrumentation ensures the replicability of the analysis for various types of institutionalized digital communications.
Бархатова Л. А. От изучения виртуального к цифровому: методологические возможности и ограничения подходов // Социологические исследования. 2023. № 1. С. 62–70. DOI: 10.31857/S013216250020183-4; EDN: TZRVPA. [Barkhatova L. A. (2023) From Virtual to Digital Research: Methodological Promises and Limitations of Approaches. Sotsiologicheskie issledovaniya [Sociological Studies]. No. 1: 62–70. (In Russ.)]
Дудина В. И. Цифровые данные – потенциал развития социологического знания // Социологические исследования. 2016. № 9. С. 21–30. EDN: WMAEHT. [Dudina V. I. (2016) Digital Data Potentialities for Development of Sociological Knowledge. Sotsiologicheskie issledovaniya [Sociological Studies]. No. 9: 21–30. (In Russ.)]
Мальцева Д. В., Романовский Н. В. О современных сетевых теориях в социологии // Социологические исследования. 2011. № 8. С. 28–37. EDN: ODSAIL. [Maltseva D. V., Romanovskiy N. V. (2011) On Modern Network Theories in Sociology. Sotsiologicheskie issledovaniya [Sociological Studies]. No. 8: 28–-37. (In Russ.)]
Резаев А. В., Стариков В. С., Трегубова Н. Д. Социология в эпоху «искусственной социальности»: поиск новых оснований // Социологические исследования. 2020. № 2. С. 3–12. DOI: 10.31857/S013216250008489-0; EDN: ZMUOZB. [Rezaev А. V., Starikov V. S., Tregubova N. D. (2020) Sociologyin the Age of ‘Artificial Sociality’: Search of New Bases. Sotsiologicheskie issledovaniya [Sociological Studies]. No. 2: 3–12. (In Russ.)]
Ackland R., O’Neil M. (2011) Online Collective Identity: The Case of the Environmental Movement. Social Networks. Vol. 33. No. 3: 177–190. DOI: 10.1016/j.socnet.2011.03.001.
Ackland R., Gibson R. (2013) Hyperlinks and Networked Communication: A Comparative Study of Political Parties Online. International Journal of Social Research Methodology. Vol. 16. No. 3: 231–244. DOI: 10.1080/13645579.2013.774179.
Arifi D., Resch B. et al. (2023) Innovation in Hyperlink and Social Media Networks: Comparing Connection Strategies of Innovative Companies in Hyperlink and Social Media Networks. PLoS ONE. Vol. 18. No. 3. DOI: 10.1371/journal.pone.0283372.
Arya V., Saraf A. et al. (2025) AI-Enhanced Competency Transfer Hubs: A Conceptual Framework for University-Industry Engagement and Knowledge Sharing. The Journal of Technology Transfer. DOI: 10.1007/s10961-025-10233-7.
Barabási A. L., Albert R. (1999) Emergence of Scaling in Random Networks. Science. Vol. 286. No. 5439: 509–512. DOI: 10.1126/science.286.5439.509.
Blondel V., Guillaume J. L., Lambiotte R. (2024) Fast Unfolding of Communities in Large Networks: 15 Years Later. Journal of Statistical Mechanics: Theory and Experiment. DOI: 10.1088/1742–5468/ad6139.
Bychkova O. (2016) Innovation by Coercion: Emerging Institutionalization of University–Industry Collaborations in Russia. Social Studies of Science. Vol. 46. No. 4: 511–535. DOI: 10.1177/0306312716654768.
Chung C. J., Barnett G. A., Park H. W. (2014) Inferring International Dotcom Web Communities by Link and Content Analysis. Quality & Quantity. Vol. 48: 1117–1133. DOI: 10.1007/s11135-013-9847‑z.
Halavais A. (2000) National Borders on the World Wide Web. New Media & Society. Vol. 2. No. 1: 7–28. DOI: 10.1177/14614440022225689.
Liu L., Wang X., Miao W., Wang X. (2025) What Factors Enable Sustainable University-Industry Collaboration Communities? Evidence from a Symbiosis Theory Perspective. Sustainable Futures. Vol. 10. DOI: 10.1016/j.sftr.2025.101166.
de Maeyer J. (2013) Towards a Hyperlinked Society: A Critical Review of Link Studies. New Media & Society. Vol. 15. No. 5: 737–751. DOI: 10.1177/1461444812462851.
Maier D., Waldherr A. et al. (2018) Exploring Issues in a Networked Public Sphere: Combining Hyperlink Network Analysis and Topic Modeling: Social Science Computer Review. Vol. 36. No. 1: 3–20. DOI: 10.1177/0894439317690337.
Park H. W., Thelwall M. (2003) Hyperlink Analyses of the World Wide Web: a Review. Journal of Computer-Mediated Communication. Vol. 8. No. 4. July 1: JCMC843. DOI: 10.1111/j.1083-6101.2003.tb00223.x.
Rogers R. (2002) Operating Issue Networks on the Web. Science as Culture. Vol. 11. No. 2: 191–213. DOI: 10.1080/09505430220137243.
Rogers R. (2013) Digital Methods. Cambridge, MA: MIT.
Schmid-Petri H., Adam S. et al. (2018) Homophily and Prestige: An Assessment of their Relative Strength to Explain Link Formation in the Online Climate Change Debate. Social Networks. Vol. 55: 47–54. DOI: 10.1016/j.socnet.2018.05.001.
Taneja H. (2017) Mapping an Audience-Centric World Wide Web: A Departure from Hyperlink Analysis. New Media & Society. Vol. 19. No. 9: 1331–1348. DOI: 10.1177/1461444816642172.
Törnberg A., Vallström V. (2025) Asymmetric Alliances in Climate Misinformation: A Network Analysis of the Swedish Climate Change Countermovement. Socius: Sociological Research for a Dynamic World. Vol. 11: 11–23. DOI: 10.1177/23780231251360822.
Waldherr A., Maier D. et al. (2016) Big Data, Big Noise: The Challenge of Finding Issue Networks on the Web: The Challenge of Finding Issue Networks on the Web. Social Science Computer Review. Vol. 35. No. 4: 427–443. DOI: 10.1177/0894439316643050.