Social nEtwork And ScientOmetric aNalysis (SEASON)
Social Network and Scientometric Analysis in Collaborative Research Publications between India and Germany
- Pondicherry University - Department of Library and Information Science - India
- GESIS - Leibniz Institute for the Social Sciences - Knowledge Technologies for the Social Sciences - Cologne, Germany
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Dr Jeyshankar Ramalingam (Pondicherry University)
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Aasif Ahmad Mir (Pondicherry University)
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Dr Philipp Mayr (GESIS)
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Nina Smirnova (GESIS)
- Paper: The rise of Indo-German collaborative research: 1990–2022. Global Knowledge, Memory and Communication. http://arxiv.org/abs/2404.17171
- Dataset: Indo-German Literature Dataset [dataset] Published: https://doi.org/10.5281/ZENODO.10607234
- Paper: The Emergence of Preprints: Comparing Publishing Behaviour in the Global South and the Global North. Online Information Review. https://doi.org/10.1108/OIR-04-2023-0181
- Paper: Embedding Models for Supervised Automatic Extraction and Classification of Named Entities in Scientific Acknowledgements. https://doi.org/10.1007/s11192-023-04806-2
- First stay of the Indian team in Cologne. March 6 - 28, 2023
- First stay of the German team in Pondicherry completed. Nov. 24 - Dec. 16, 2022
Scientists and organizations should consider the benefits and costs of collaboration before deciding to collaborate. Collaboration for its individual sake does not seem to be warranted, given the number of critical success factors that should be taken into account before and during collaboration. Collaboration persuades the establishment of effectual communication and partnerships and also recommends equivalent chances among the team members. It tributes and respects each member's individual and organizational technique. It also augments the ethical demeanor, maintains sincerity, simplicity, secrecy, reliability, and righteousness.
Scientometric and social network indicators are used to appraise the quantitative and qualitative published scientific literature in any given subject field of study, countries, institutions, sources and also enable to analyse assists to study the past, present and forecast the future, features of theories, laws, and models linked to scientific developments and its research collaboration with the society. This study will draw several empirical analyses intended to measure the effects of Indo-German collaboration on research performance and, indirectly, to verify the legitimacy of policies that support such collaboration. Our study superimposes the Indo - German research trends system, using a scientometric and social network-type approach in which collaboration and co-authorship, and institutions of scientific publications are treated on a par, and is aimed at assessing the impact of collaboration intensity on scientific productivity. This study aims to investigate the influence of different patterns of collaboration on the citation impact among the Indo - German researchers.
More precisely the project will have following components: The researcher will collect data from Web of Science, SCOPUS, and Pub Med databases. The aggregated data can be analyzed by various software like Hiscite, Bibexcel, Biblioshiny, and SPSS to determine diverse scientometric measures. Social network analysis software Pajek and visualization software VOS Viewer will be utilized to present better visualization of networks for data interpretation and presentation of research work. This research project will be providing the following expected outcomes and benefits to India and Germany.
The project will involve close collaboration and joint work between Indian and German sides. While, the Indian side has experience of working on Text Analytics of scholarly articles and Social Media analytics, the German side has sufficient expertise of applying the Scientometrics and natural language processing techniques for Information retrieval in Scholarly article domain. It is necessary to bring together methodologies from Information Retrieval, NLP and Scientometrics and fuse them together to design a suitable retrieval and recommendation system as proposed in the project. The collaboration is expected to from a long term association among the two research groups and to promote bilateral research cooperation among the two countries by exchange of ideas, know-how, research staff and sharing of resources. In due course academic collaboration agreements, involving joint research projects and other collaborative activities, between participating Indian and German institutions will be explored.
- Mir, A. A., Smirnova, N., Ramalingam, J., & Mayr, P. (2023). The rise of Indo-German collaborative research: 1990–2022. Global Knowledge, Memory and Communication. https://doi.org/10.1108/GKMC-09-2023-0328 preprint: http://arxiv.org/abs/2404.17171
- Smirnova, N., Culbert, J. H., & Mayr, P. (2024). Indo-German Literature Dataset [dataset]. Zenodo. https://doi.org/10.5281/ZENODO.10607234
- Biesenbender, K., Smirnova, N., Mayr, P., & Peters, I. (2024). The Emergence of Preprints: Comparing Publishing Behaviour in the Global South and the Global North. Online Information Review. https://doi.org/10.1108/OIR-04-2023-0181
- Smirnova, N., & Mayr, P. (2023). Embedding Models for Supervised Automatic Extraction and Classification of Named Entities in Scientific Acknowledgements. Scientometrics. https://doi.org/10.1007/s11192-023-04806-2
- Smirnova, N., & Mayr, P. (2022). A Comprehensive Analysis of Acknowledgement Texts in Web of Science: A case study on four scientific domains. Scientometrics. https://doi.org/10.1007/s11192-022-04554-9
- Nishavathi, E., & Jeyshankar, R. (2020). A Scientometric Social Network Analysis of International Collaborative Publications of All India Institute of Medical Sciences, India. Journal of Information Science Theory and Practice, 8(3), 64–76. https://doi.org/10.1633/JISTAP.2020.8.3.5
2022-2024
DAAD–UGC Project-based Personnel Exchange Programme (PPP 2022)
- DAAD project number: 57608852
- UGC project number: 1-10/2020(IC)