Abstract
Everyday, social media usage particularly Facebook usage are growing exponentially. Simply, inspecting Facebook usage provides meaningful information concerning users’ daily interactions and hence about their personality traits. Numerous studies have been done to harness such streams of Facebook data to obtain accurate prediction of human behavior, social interactions, and personality. The aim of this study is to build a neural network–based predictive model that uses Facebook user’s data and activity to predict the Big 5 personalities. This study combines the inference features highlighted in three different relevant studies which are; number of likes, events, groups, tags, updates, network size, relationship status, age, and gender. The study was conducted on 7,438 unique Facebook participants obtained from the myPersonality database. The findings of this study showed how much a person’s personality can be predicted only by analyzing their Facebook activity. The proposed artificial neural network model was able to correctly classify an individual’s personality at an 85% prediction accuracy.
Highlights
BackgroundOver the last two decades, social media has rapidly become an integral part of our lives
This study aims to use Artificial Neural Network (ANN) to predict personality with the dataset derived from Facebook
The purpose of this study was to explore the performance of ANN in classifying and predicting the big five personality based on the data derived from a user’s Facebook data
Summary
BackgroundOver the last two decades, social media has rapidly become an integral part of our lives. A voluminous amount of data is constantly being emerged from these social media sites based upon user generated interactions. Such massive information has caught the attention of many researchers who thrive to predict human behavior from those interaction data. Today Facebook has more than 2.8 billion active subscribers (Statista, 2020) Accommodating such immense and diverse personal information, mining and harnessing Facebook data has been the attention of many academic and business endeavors (Wilson et al, 2012). The user interaction data can be used to extract meaningful information regarding real-life behaviors of users Analyzing such acquired data can be used to discover more about users’ future actions
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