Exploring Homophily in Research Collaboration: A Dynamic Centrality Analysis Approach
DOI:
https://doi.org/10.13052/jgeu0975-1416.1224Keywords:
Co-authorship network, dynamic centrality, homophily, social networkAbstract
Homophily is the phenomenon of individuals seeking others who are similar to themselves. Homophily influences the formation of co-authorship networks. In our study, we measure the homophily of the authors based on their affiliation using the co-authorship network. The main contribution of our study is that we test homophily with a dynamic centrality analysis algorithm and find that homophily exists when we measure the authors’ degree within and outside their network. However, homophily does not exist when we use the dynamic centrality analysis algorithm for the same co-authorship network.
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References
A. A. Stoica, Homophily in co-authorship networks, Int. Rev. Soc. Res, 8.2 (2018), 119–128.
H. Bisgin, N. Agarwal, X. Xu, A study of homophily on social media, World Wide Web, 15.2 (2012), 213–232.
K. Z. Khanam, G. Srivastava, V. Mago, The homophily principle in social network analysis, (2020), arXiv preprint arXiv:2008.10383.
N. E. D. Ferreyra, T. Hecking, E. Aïmeur, M. Heisel, H. U. Hoppe, Community Detection for Access-Control Decisions: Analysing the Role of Homophily and Information Diffusion in Online Social Networks, (2021) arXiv preprint arXiv:2104.09137.
H. Lu, Y. Feng, A measure of authors’ centrality in co-authorship networks based on the distribution of collaborative relationships, Scientometrics, 81.2 (2009), 499–511.
M. G. Hâncean, M. Perc, Homophily in coauthorship networks of East European sociologists, Scientific reports, 6.1 (2016), 1–12.
M. Kwiek, W. Roszka, Gender-based homophily in research: A large-scale study of man-woman collaboration, Journal of Informetrics, 15.3 (2021), 101171.
K. Das, S. Samanta, M. Pal, Study on centrality measures in social networks: a survey, Social network analysis and mining, 8.1 (2018), 1–11.
F. Bloch, M. O. Jackson, P. Tebaldi, Centrality measures in networks, arXiv preprint arXiv:1608.05845, (2016).
M. McPherson, L. Smith-Lovin, J. M. Cook, Birds of a feather: Homophily in social networks, Annual review of sociology, (2001), 415–444.
B. S. Lawrence, N. P. Shah, Homophily: Measures and meaning. Academy of Management Annals, 14.2 (2020), 513–597.
R. Dwivedi, S. P. Nerur, Analyzing Co-authorship Network for Homophily-Evidence from IS senior Scholar’s Basket of Eight Journals for Business Analytics Research. In AMCIS, (2020).
M. Gallivan, M. Ahuja, Co-authorship, homophily, and scholarly influence in information systems research. Journal of the Association for Information Systems, 16.12(2015), 2.
M. Cristani, D. Fogoroasi, C. Tomazzoli, Measuring Homophily. In KDWeb, (2016).
V. Umadevi, Case study–centrality measure analysis on co-authorship network. Journal of Global Research in Computer Science, 4.1 (2013), 67–70.
A. Dias, S. Ruthes, L. Lima, E. Campra, M. Silva, M. Bragança de Sousa, and G. Porto, Network centrality analysis in management and accounting sciences. RAUSP Management Journal, 55(2020), 207–226.
P. Hage, F. Harary, Eccentricity and centrality in networks. Social networks, 17.1 (1995), 57–63.
L. Holman, C. Morandin, Researchers collaborate with same-gendered colleagues more often than expected across the life sciences, PloS one, 14.4(2019), e0216128.
J. Fagan, K. S. Eddens, J. Dolly, N. L. Vanderford, H. Weiss, & J. S. Levens, Assessing research collaboration through co-authorship network analysis. The journal of research administration, 49.1(2018), 76.
M. H. Jones, T. S. Hackel, and R. A. Gross, The homophily and centrality of LGBQ youth: A new story?, Social Psychology of Education, 25.5(2022), 1157–1175.
R. Mahapatra, S. Samanta, and M. Pal, Detecting influential node in a network using neutrosophic graph and its application. Soft Computing, 27(14), 9247–9260 (2023).
S. Samanta, V. K. Dubey, and B. Sarkar, Measure of influences in social networks. Applied Soft Computing, 99, 106858 (2021).
G. Muhiuddin, S. Samanta, A. F. Aljohani, and A. M. Alkhaibari, A study on graph centrality measures of different diseases due to DNA sequencing. Mathematics, 11(14), 3166 (2023).
S. D. Pandey, A. S. Ranadive, S. Samanta, & B. Sarkar, Bipolar-Valued Fuzzy Social Network and Centrality Measures. Discrete Dynamics in Nature and Society, 2022(1), 9713575.