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Finding Context-Based Influencers on Twitter

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Abstract

With the vast number of people present on online social network platforms like Twitter, Instagram, Facebook, etc., many business people looked into this number as a business opportunity. Thus, they started converting this number to business with the help of influencer marketing. An influencer is a person who can change the opinion or purchase behavior of people who are following them. Marketing that relies on individuals with strong social media presence to promote brands is called influence marketing. Due to their authority in a specific field or industry, influencers influence their fans’ buying habits and beliefs through their persuasive powers. Thus, determining influencers in the network is currently a popular research topic. The influence score of a person has been calculated in two ways: one based on the structure of the network and the user’s connectivity in the network, and another based on the user’s activity in the network. Research has been going on to find the influence of the user on social networks based on the user’s behavior and engagement ratio. This work focuses on finding the influencer who positively influences the given context. This paper proposes a method to find the context-based positive influence. We also need to consider the user’s sentiment before finding the list of influential users. The result shows that even if we find the influential user if the influence isn’t positive, the influence marketing may have a negative effect.

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Data Availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors acknowledged their respective institution for extended the facilities to conduct the research.

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Authors and Affiliations

  1. Department of Information Science and Engineering, Sri Krishna Institute of Technology, Bangalore, Karnataka, 560090, India

    Ragini Krishna

  2. Mangalore Institute of Technology and Engineering, Moodabidre, Karnataka, 574225, India

    C. M. Prashanth

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  1. Ragini Krishna
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  2. C. M. Prashanth
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Contributions

RK: conceptualization, investigation, writing—original draft, writing—review and editing, analysis and interpretation, and study. CMP: editing, analysis and interpretation, investigation on challenges and supervision. All authors have approved the final version.

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Correspondence to Ragini Krishna.

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This article is part of the topical collection “Advances in Computational Approaches for Image Processing, Wireless Networks, Cloud Applications and Network Security” guest edited by P. Raviraj, Maode Ma and Roopashree H R.

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Krishna, R., Prashanth, C.M. Finding Context-Based Influencers on Twitter. SN COMPUT. SCI. 5, 177 (2024). https://doi.org/10.1007/s42979-023-02470-0

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