A Study on Social Media Sentiment Classification: An Analysis of Reddit Posts about Body Dysmorphic Disorder

The growth of the internet in recent years has brought forward chances of connecting with other users on a markedly large scale. Moreover, the comfort of interacting with a diverse audience on social media allows users to create and publish original content without many restrictions and in a liberated space. To understand this magnitude, it was estimated in April 2024 that X ( formerly known as Twitter) has 611 million monthly active users, as a result of which, we now have access to an enormous amount of textual data produced by an incredibly diverse population of internet users, providing us with opportunities to observe their interactions and self-expressions for a variety of scientific purposes. The analysis of such data can be contextualized in detail to fit our project's needs, which will focus on the issue of medical informatics and texts containing symptoms of Body Dysmorphic Disorder (BDD) extracted from users’ posts on X (Twitter) through sentiment classification task. A sentiment classification task computes people's opinions, evaluations, and emotions regarding entities, events, and their attributes. Through this study, we aim to see a correlation between negative or positive sentiment present in tweets as signs of BDD symptoms discussed in the same tweet. Since body dysmorphic disorder seems to be less investigated than other types of well-known mental disorders, especially depression or general psychiatric symptoms, this study focuses on one under-investigated mental disorder, allowing us to thoroughly consider the signs, linguistic features, and unpredicted factors with more focused attention, in comparison to a more general study of multiple disorders or analysis of multiple social media platforms. Our results can contribute to extending the framework of textual data analysis for mental health through utilizing efficient computational methods that have proven to benefit research access fields.