Document Type : Articles


1 Assistant Prof., Computer Engineering Department, C. K. Pithawala College of Engineering and Technology, Surat-07, Gujarat, India.

2 Associate Prof., Computer Engineering Department, Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat-07, Gujarat, India.

3 Assistant Prof., Computer Engineering Department, Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat-07, Gujarat, India.


Influence identification, one of the compelling applications of Social Network Analysis (SNA) is gaining immense attention in scientific literature analytics. Existing influence identification techniques in the scientific domain majorly explore scientific collaborations (co-author and co-citation networks) of researchers. Standard centrality algorithms are widely applied for this purpose. The emergence of digital scholarly platforms allows researchers to build their social community in the scientific environment. Few scholarly platforms maintain social media like follower and following relations apart from co-authorships and co-citations of researchers. This research examines the impact of followers and followings on influence identification in the scientific domain. The real scientific information from widely utilized digital scholarly platforms: ResearchGate (RG) and Academia is extracted. From the collected information, scholarly networks are constructed based on follower-following relations. Standard centrality algorithms are implemented to identify the influence of these networks. The results are compared with i) the researcher’s influence scores provided by RG and Academia ii) three legitimate global ranking lists of researchers. The outcome suggested that, like SNA, social collaborations among researchers in terms of followers and followings significantly impact influence identification in the scientific domain.


Alizade Zowj, H., Ghane, M.R. & Ehsanifar, F. (2019). Identifying information retrieval research trends using author co-citation network. International Journal of Information Science and Management, 17(2), 99-117. Retrieved from
Amjad, T., Daud, A. & Aljohani, N. R. (2018). Ranking authors in academic social networks: A survey. Library Hi Tech, 36(1), 97-128.
Amjad, T., Daud, A., Akram, A. & Muhammed, F. (2016). Impact of mutual influence while ranking authors in a co-authorship network. Kuwait Journal of Science, 43(3), 100-109. Retrieved from
Amjad, T., Daud, A., Che, D. & Akram, A. (2016). MuICE: mutual influence and citation exclusivity author rank. Information Processing & Management, 52(3), 374-386.
Ansari, J. A. N. & Khan, N. A. (2020). Exploring the role of social media in collaborative learning the new domain of learning. Smart Learning Environments, 7(9).
Bai, X., Zhang, F., Hou, J., Lee, I., Kong, X., Tolba, A. & Xia, F. (2018). Quantifying the impact of scholarly papers based on higher-order weighted citations. PLoS ONE, 13(3), e0193192.
Bhattacharya, S., & Sarkar, D. (2021). Study on information diffusion in online social network. In Proceedings of International Conference on Frontiers in Computing and Systems (pp. 279-288). Springer, Singapore.
Bibi, F., Khan, H. U., Iqbal, T., Farooq, M., Mehmood, I. & Nam, Y. (2018). Ranking authors in an academic network using social network measures. Applied Sciences, 8(10), 1824.
Desai, M., Mehta, R. G. & Rana, D. P. (2019). An empirical analysis to identify the effect of indexing on influence detection using graph databases. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(9S), 414-421. Retrieved from file:///C:/Users/drghane/Downloads/An_Empirical_Analysis_to_Identify_the_Ef.pdf
Desai, M., Mehta, R. G. & Rana, D. P. (2021). RGNet: The novel framework to model linked ResearchGate information into network using hierarchical data rendering. In Advances in Machine Learning and Computational Intelligence (pp. 37-45). Springer, Singapore.
Desai, M., Mehta, R. G. & Rana, D. P. (2022a). Anatomising the impact of ResearchGate followers and followings on influence identification. Journal of Information Science.
Desai, M., Mehta, R. G. & Rana, D. P. (2022b). ScholarRec: A scholars’ recommender system that combines scholastic influence and social collaborations in academic social networks. International Journal of Data Science and Analytics, 16, 203–216.
Desai, M., Mehta, R. G., & Rana, D. P. (2023). Contextual analysis of scholarly communications to identify the source of disinformation on digital scholarly platforms. Kybernetes. (in print)
Ding, Y. (2011). Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks. Journal of Informetrics, 5(1), 187-203.
Espinoza Vasquez, F. K., & Caicedo Bastidas, C. E. (2015). Academic social networking sites: A comparative analysis of their services and tools. IConference 2015 proceedings.
Gasparyan, A. Y., Nurmashev, B., Yessirkepov, M., Endovitskiy, D. A., Voronov, A. A. & Kitas, G. D. (2017). Researcher and author profiles: Opportunities, advantages, and limitations. Journal of Korean Medical Science, 32(11), 1749-1756.
Hashmi, H. B. U. H., Kayani, H. U. R., Toor, S. K., Mansoor, A., & Raheem, A. (2020). The Impact of social media: A Survey. International Journal of Scientific & Technology Research, 9(12), 341-348. Retrieved from
Jordan, K. (2019). From social networks to publishing platforms: A review of the history and scholarship of academic social network sites. Frontiers in Digital Humanities, 6, 5.
Keller, R. C. A. (2019). Information and tips related to search engines like Google Scholar and other ways your work is and can be more visible on the net. A personal perspective. Retrieved from file:///C:/Users/drghane/Downloads/Search%20enginescomparison.pdf
Kesht-Karan, S., Ghane, M. R., & Danesh, F. (2021). Dimensions of the Scientific Collaborations of the Researchers Affiliated with Shiraz University of Medical Sciences. International Journal of Information Science and Management (IJISM), 19(2), 31-48. Retrieved from
Khvatova, T., Dushina, S. & Nikolaenko, G. (2017, December). Do the online activities of scientists in social professional networks influence their academic achievements? In European Conference on Management, Leadership & Governance (pp. 217-226). Academic Conferences International Limited.
Liang, Z., Mao, J., Lu, K., Ba, Z. & Li, G. (2021). Combining deep neural network and bibliometric indicator for emerging research topic prediction. Information Processing & Management, 58(5), 102611.   
Maia, L. F. M. P., Lenzi, M., Rabello, E. T. & Oliveira, J. (2019). Scientific collaboration in Zika: identification of the leading research groups and researchers via social network analysis. Colaborações científicas em Zika: identificação dos principais grupos e pesquisadores através da análise de redes sociais. Cadernos de saude publica, 35(3), e00220217. 
Makkizadeh, F., Dehghan, A. & Mostafavi, E. (2020). Investigating association between social influence, productivity, and performance in co-author network of researchers in medical ethics. Iranian Journal of Medical Ethics and History of Medicine, 13(1), 240-252. Retrieved from [in Persian]
Malinen, S. & Koivula, A. (2020). Influencers and targets on social media: Investigating the impact of network homogeneity and group identification on online influence. First Monday, 25(4).
Ortega, J. L. (2017). Toward a homogenization of academic social sites: A longitudinal study of profiles in Academia. edu, Google Scholar Citations and ResearchGate. Online Information Review, 41(6), 812-825.
Samie, M. E., Biranvand, A., Rahmaniyan, S. & Varnamkhasti, E. M. (2022). The impact of the activity of industrial engineering researchers in various scientific-citation networks on improving their scientific authority status. International Journal of Information Science and Management (IJISM), 20(1), 257-271.
Savov, P., Jatowt, A. & Nielek, R. (2020). Identifying breakthrough scientific papers. Information Processing & Management, 57(2), 102168.
Valsesia, F., Proserpio, D. & Nunes, J. C. (2020). The positive effect of not following others on social media. Journal of Marketing Research, 57(6), 1152-1168.
Wan, Z., Mahajan, Y., Kang, B. W., Moore, T. J. & Cho, J. H. (2020). A Survey on Centrality Metrics and Their Network Resilience Analysis. IEEE Access, 9, 104773-104819.
Wang, Y., Ding, Z., Wei, X. X. & Long, J. (2021). Scholars influence evaluation based on time series heterogeneous network. In 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) (pp. 868-871). IEEE.
Wu, D., Fan, S. & Yuan, F. (2021). Research on pathways of expert finding on academic social networking sites. Information Processing & Management, 58(2), 102475.
Wu, X. & Zhang, C. (2019). Finding high-impact interdisciplinary users based on friend discipline distribution in academic social networking sites. Scientometrics, 119(2), 1017-1035.
Yaghtin, M., Sotudeh, H., Mohammadi, M., Mirzabeigi, M. & Fakhrahmad, S. M. (2019). A correlation study of co-opinion and co-citation similarity measures. International Journal of Information Science and Management (IJISM), 17(2),
Zhang, S., Zhao, D., Cheng, R., Cheng, J. & Wang, H. (2016). Finding influential papers in citation networks. In 2016 IEEE First International Conference on Data Science in Cyberspace (DSC) (pp. 658-662). IEEE.