Psychological and Demographic Determinants of Social Media Influence: Developing Predictive Models to Identify Influencers
محل انتشار: مجله شناخت عصبی تکاملی، دوره: 5، شماره: 1
سال انتشار: 1403
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 49
فایل این مقاله در 11 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JNCOG-5-1_003
تاریخ نمایه سازی: 19 دی 1403
چکیده مقاله:
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 ۱,۲۱۴ 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.
کلیدواژه ها:
نویسندگان
S. M Mahdi Firouzabadi
Institute for Cognitive and Brain Science, Shahid Beheshti University, Tehran, Iran
G. Reza Jafari
Department of Physics, Shahid Beheshti University, Tehran, Iran. & Center for Communications Technology, London Metropolitan University, London, UK.
Reza Khosrowabadi
Institute for Cognitive and Brain Science, Shahid Beheshti University, Tehran, Iran