Personality Prediction Based on Tweets of Russo-Ukrainian Conflict in Social Networks

The Russo-Ukrainian conflict has been a highly contentious and protracted geopolitical issue that has garnered significant attention on various social media platforms, particularly in Twitter. Online discussion on Twitter has been the main platform for the protracted and polarizing geopolitical conflict between Russia and Ukraine. As the platform generates a lot of user-generated information and allows us to investigate the prospect of using tweets related to the dispute as a method to predict people’s personality traits using Twitter posts. To extract and analyse textual information from tweets on the conflict, we used machine learning methods and natural language processing (NLP) approaches in this work. Based on the data that Twitter users shared during the conflict, the main objective of this study is to forecast the personalities of those people. The linguistic and psycholinguistic characteristics were obtained from the preprocessed data and for understanding the personalities we applied Big five factor model (BFFM) on the dataset. With the help of these characteristics and features, the Big Five scores and personality traits are predicted. The machine learning and deep learning algorithms such as Support vector machine (SVM), MLP (Multilayer Perceptron), and RCNN (Region based convolutional neural network) are used to achieve personalities.