Identification of Key Opinion Leaders in Pharmaceutics Using Network Analysis

Authors

  • Sarthak Kulkarni  B.E., Information Technology Department, AISSMS Institute of Information technology, Pune, Maharashtra, India
  • Pritam Bagad  B.E., Information Technology Department, AISSMS Institute of Information technology, Pune, Maharashtra, India
  • Hrishikesh Joshi  B.E., Information Technology Department, AISSMS Institute of Information technology, Pune, Maharashtra, India
  • Himanshu Randad  B.E., Information Technology Department, AISSMS Institute of Information technology, Pune, Maharashtra, India
  • Prof. Anuja Phapale  Assistant Professor at Information Technology Department, AISSMS Institute of Information technology, Pune, Maharashtra, India

DOI:

https://doi.org/10.32628/IJSRST21831

Keywords:

Network Analysis, Centrality algorithms, web scraping, network analysis, key opinion leaders, pharmaceutics

Abstract

The term Key Opinion Leader in marketing is not new. Key Opinion Leaders (KOLs) commonly known as thought leaders who play a crucial role in the life science industry. We through this project intend to implement the concept of identifying key opinion leaders using weighted Social Network Analysis (SNA). We intend to use European PubMed Central dataset for creating a weighted social Network of authors who have healthcare and medicine related publications and apply different centrality measures on it. In order to collect the data, we will be using one of the web scraping methods and predefined libraries like scrapy. After fetching and processing the data we intend to form a network of authors using python’s NetworkX library. This network will then be subjected to various centrality measures which in turn will give prominent opinion leaders as the output.

References

  1. Hengmin Zhou, Daniel Zeng and Changli Zhang, "Finding leaders from opinion networks," 2009 IEEE International Conference on Intelligence and Security Informatics, Richardson, TX, USA, 2009, pp. 266-268, doi: 10.1109/ISI.2009.5137323.
  2. Yu, Xiaoqing & Lu, Jing & Liu, Huanhuan. (2013). Identifying top-N opinion leaders on local social network. IET Conference Publications. 2013. 268-271.10.1049/cp.2013.1970.
  3. Identifying Key opinion leaders using social network analysis. Cognizant System Private Limited’s White Paper in June 2015.
  4. Network Analysis algorithms: Network analysis algorithm, Closeness centrality.
  5. Python NetworkX - https://networkx.github.io/
  6. Europe PubMed Central - https://europepmc.org/
  7. ReactJS - Overview - Tutorialspoint
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International Journal of Scientific Research in Science and Technology

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Published

2021-06-30

Issue

Volume 8, Issue 3, May-June-2021

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Sarthak Kulkarni, Pritam Bagad, Hrishikesh Joshi, Himanshu Randad, Prof. Anuja Phapale "Identification of Key Opinion Leaders in Pharmaceutics Using Network Analysis " International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 8, Issue 3, pp.01-05, May-June-2021. Available at doi : https://doi.org/10.32628/IJSRST21831