Identification and Synthesis of Unstructured Data of Violence on Facebook Using a Mood and Emotion AnalysisSystem

Master of computer Application

Abstract—Abstract— Hate speech is a type of expression that targets an individual or a group based on their race, ethnicity, religion, sexual orientation, or other characteristics. Although it may be conveyed in a variety of ways, both online and offline, the growing popularity of social media has expanded both its usage and intensity significantly. As a result, the goal of this study is to find and analyse unstructured data from chosen social media posts that attempt to promote hatred in the comment sections. To address this problem, we offer FADOHS, a novel framework that combines data analysis and natural language processing methodologies to alert all social media providers to the prevalence of hatred on social media. To be more specific, we employ sentiment and emotion analysis algorithms to analyse recent postings and comments. Posts suspected of having dehumanising language will be screened before being submitted into the clustering algorithm for further analysis. According to the experimental results, the suggested FADOHS framework outperforms the state-of-the-art technique by around 10Social media allows users to freely express themselves online; yet, when individuals post harsh and opinionated comments that target specific persons or communities, this may lead to animosity against them. Because of the widespread criticism of obesity (fatness), a great deal of fat-shaming material has been made available online. The project ”Framework for Detection and Integration of Unstructured Data of Hate Speech on Facebook Using Sentiment and Emotion Analysis” intends to create a software framework in Java for detecting and integrating hate speech on Facebook.

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