A Twitter Sentiment Analysis Model for Measuring Security and Educational Challenges: A Case Study in Saudi Arabia

Abstract

Ensuring the good psychological health of the community is one of the highest priorities in modern societies. Therefore, having a sense of the community’s rhythm and mood is a very important factor in understanding what challenges it may be facing. Psychological challenges differ from one society to another. Hence every community has its own specific psychological scales. In the context of present-day Saudi Arabia and many other countries, the measuring of educational and security challenges is critical as it can enable decision-makers to avoid anticipated risks. Traditional psychological scales in the form of questionnaires are time consuming to administer and analyze, especially where data need to be collected from a massive sample distributed over a wide geographical area. Such scales are impractical and ineffective in terms of providing critical results especially in today’s rapidly changing environment. Therefore this research proposes an approach to identify and measure the educational and security challenges facing Saudi society through Twitter sentiment analysis. The psychological measurement standards of three key categories of education and security challenges were identified and broken down into selected keywords that best identified these challenges. Then Arabic tweets that contained those keywords were analyzed in order to develop a model that could classify new tweets into one of the three types of challenges. The proposed model was better able to predict tweets belonging to the cross-cultural and ethics of dialogue and rules of difference challenges than those for the dominant negative social values challenge. The results of this research show that the sentiment analysis of tweets could provide a faster and cheaper alternative to the use of traditional psychological scales.