Journal of Neurodevelopmental Cognition
Quarterly Publication

Psychological and Demographic Determinants of Social Media Influence: Developing Predictive Models to Identify Influencers

https://doi.org/10.48308/jncog.2024.105194
Volume 5, Issue 1
December 2024
Pages 48-58
Journal of Neurodevelopmental Cognition

Document Type : Original Article

Authors

S. M Mahdi Firouzabadi 1
G. Reza Jafari 2
Reza Khosrowabadi 1

1 Institute for Cognitive and Brain Science, Shahid Beheshti University, Tehran, Iran

2 Department of Physics, Shahid Beheshti University, Tehran, Iran

Abstract
This study explores psychological and demographic characteristics distinguishing social media influencers from non-influencers and investigates the predictive potential of psychological features for influence. Using a diverse dataset containing age, gender, NEO personality scores, and a revised active/passive engagement scale of 1,214 Iranian participants, we aim to uncover significant feature differences and construct a predictive model for influence classification. Our statistical analyses reveal significant differences between influencers and non-influencers in key variables, including age and active/passive engagement and Neuroticism. However, machine learning models indicate that while distinct psychological characteristics are associated with influence, their predictive power shows promise but may be limited without additional behavioral or content-based metrics. This study contributes to the understanding of psychological factors in social influence and the feasibility of machine learning models for influencer identification.

Keywords

Social Network
Social influence
Machine Learning
Social Cognition
  • Receive Date 23 October 2024
  • Revise Date 04 December 2024
  • Accept Date 05 December 2024

Home

Guide for Authors

Submit Manuscript

Guide for Reviewers

Contact Us

Open Access Statement

Copyright Policy

Licensing Policy

Plagiarism Policy

Self-archiving policies for authors