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All Journal International Journal of Advances in Applied Sciences
Zulfatun Sofiyani
Universitas Airlangga
Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Predicting perceived information overload from social media use: a machine learning approach Mohamad Noorman Masrek; Endang Fitriyah Mannan; Zulfatun Sofiyani; Atiqa Nur Latifa Hanum
International Journal of Advances in Applied Sciences Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i3.pp1147-1154

Abstract

The rapid growth of social media has intensified users’ exposure to large volumes of information, increasing the risk of perceived information overload. While prior studies have primarily examined this phenomenon using explanatory models, limited attention has been given to its prediction. This study aims to predict perceived information overload from social media use using a machine learning approach. Data were collected through a survey of 349 university students in Malaysian higher education institutions. Social media use across multiple platforms was used as input features, while perceived information overload was treated as a binary target variable. Several machine learning algorithms were evaluated, including decision tree, random forest, k-nearest neighbor, support vector machine, neural network, naïve Bayes, and logistic regression. The results indicate that social media usage patterns contain predictive value for identifying information overload, with the support vector machine demonstrating the strongest discriminative performance. The study contributes to the literature by complementing existing explanatory research with a predictive perspective and highlights the potential of machine learning techniques for early identification of information overload in social media environments.
Co-Authors Atiqa Nur Latifa Hanum Endang Fitriyah Mannan Mohamad Noorman Masrek