An IBM Watson Analysis of Twitter Followers and Influencers

In this paper, the authors examined the structure and relationship between followers and leaders in Twitter followership to find similarities in personality. Specifically, they focused on the relationships between Twitter (now X) influencers and their followers through an extensive analysis of milli...

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Published inInternational journal of technology and human interaction Vol. 21; no. 1; pp. 1 - 17
Main Authors Palvia, Prashant, Uppala, Vishal, Ankem, Kalyani
Format Journal Article
LanguageEnglish
Published Hershey IGI Global 05.03.2025
Subjects
Communication
Consumer behavior
Consumers
Digital media
Influencer marketing
Leadership
Marketing
Personality
Purchase intention
Social networks
Online AccessGet full text
ISSN1548-3908
1548-3916
DOI10.4018/IJTHI.370599

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Abstract In this paper, the authors examined the structure and relationship between followers and leaders in Twitter followership to find similarities in personality. Specifically, they focused on the relationships between Twitter (now X) influencers and their followers through an extensive analysis of millions of tweets using IBM Watson Personality Insights. The results are founded on the relationships between two major social media influencers and their respective followers. The present research informs marketing practitioners on using IBM Watson to find congruence between social media influencers and followers for the most effective and compelling marketing strategies to sell products.
AbstractList In this paper, the authors examined the structure and relationship between followers and leaders in Twitter followership to find similarities in personality. Specifically, they focused on the relationships between Twitter (now X) influencers and their followers through an extensive analysis of millions of tweets using IBM Watson Personality Insights. The results are founded on the relationships between two major social media influencers and their respective followers. The present research informs marketing practitioners on using IBM Watson to find congruence between social media influencers and followers for the most effective and compelling marketing strategies to sell products.
Author Uppala, Vishal
Ankem, Kalyani
Palvia, Prashant
AuthorAffiliation North Dakota State University, USA
Northern Kentucky University, USA
University of North Carolina at Greensboro, USA
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  fullname: Uppala, Vishal
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  surname: Ankem
  fullname: Ankem, Kalyani
  organization: Northern Kentucky University, USA
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SubjectTerms Communication
Consumer behavior
Consumers
Digital media
Influencer marketing
Leadership
Marketing
Personality
Purchase intention
Social networks
Title An IBM Watson Analysis of Twitter Followers and Influencers
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