The DOI matches its Crossref record; 93 of the 93 references it cites were found in a registry or an index.
Measuring social media influencer index- insights from facebook, Twitter and Instagram
Abstract
Abstract The growth of social media has completely revamped the way people interact, communicate and engage. These platforms play a key role in facilitating greater outreach and influence. This study proposes a mechanism for measuring the influencer index across popular social media platforms including Facebook, Twitter, and Instagram. A set of features that determine the impact on the consumers are modelled using a regression approach. The underlying machine learning algorithms including Ordinary Least Squares (OLS), K-NN Regression (KNN), Support Vector Regression (SVR), and Lasso Regression models are adapted to compute a cumulative score in terms of influencer index. Findings indicate that engagement, outreach, sentiment, and growth play a key role in determining the influencers. Further, the ensemble of the four models resulted in the highest accuracy of 93.7% followed by the KNN regression with 93.6%. The study has implications across various domains of e-commerce, viral marketing, social media marketing and brand management wherein identification of key information propagators is essential. These influencer indices may further be utilized by e-commerce portals and brands for the purpose of social media promotion and engagement for larger outreach.
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Cites
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Cited by
Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., Jain, V., Karjaluoto, H., Kefi, H., Krishen, A. S., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102168 · Cited by 4,608
Self-citationBelanche, D., Casaló, L. V., Flavián, M., & Ibáñez-Sánchez, S. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.03.067 · Cited by 659
Masuda, H., Han, S. H., & Lee, J. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121246 · Cited by 576
Ladhari, R., Massa, E., & Skandrani, H. (2020) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2019.102027 · Cited by 557
Jiménez-Castillo, D., & Sánchez-Fernández, R. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.07.009 · Cited by 528
Metadata
- Authors
- Arora, A., Bansal, S., Kandpal, C., Aswani, R., & Dwivedi, Y.
- Venue
- Journal of Retailing and Consumer Services
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 49
- Pages
- 86-101
- ISSN
- 0969-6989 (ISSN-L)
- OpenAlex
- W2922826082
- Cited by
- 601
- References
- 93
- FWCI
- 142.89
- Type
- journal article
- Language
- en
- Open access
- closed
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- Arora, A., Bansal, S., Kandpal, C., Aswani, R., & Dwivedi, Y. (2019). Measuring social media influencer index- insights from facebook, Twitter and Instagram. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2019.03.012
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