Mining and Understanding Arabic Tweets Related to Cognitive Disabilities

Social media has become an important part of everyday life for all segments of a society. Twitter is one of the leading platforms, where people can freely express their opinions and tweet about different topics to a large audience. Due to the core nature of tweets exchange on Twitter, text mining is essential to understand how a topic is discussed and perceived within society. We utilized text mining approaches, including sentiment and temporal analyses, to examine and understand how Arab users engage with Twitter to discuss cognitive disabilities. Content volume, temporal evolution, users, and sentiment were analyzed. We applied Valence Aware Dictionary and sEntiment Reasoner (VADER) for sentiment analysis to identify the overall opinions and attitudes toward the researched neurological conditions. The results provide new insights into public perspectives, which may assist interested entities to form and distribute appropriate resources and information. We discussed our findings, provided recommendations to interested stakeholders, and introduced potential opportunities and future directions.