Abstract
Abstract: Research into cyberbullying detection has increased in recent years, due in part to the proliferation of cyberbullying across social media and its detrimental effect on young people. Cyber bullying is one of the most common problems faced by the internet users making internet a vulnerable space hence there has to be some detection that is needed on the social media platforms. Detecting the bullies online at the earliest makes sure that these platforms are safer for the user and internet indeed becomes a platform to share information and use it for other leisure activities. Even though there has been some research going on implementing detection and prevention of cyber bullying, it is not completely feasible due to certain limitations imposed. In this paper lexicon-based approach of the NLTK sentiwordnetis used to differentiate the positive and negative words and produce results. These words are given negative and positive values greater than or less than zero for positive and negative words respectively. Lexicon based systems utilize word lists and use the presence of words within the lists to detect cyberbullying. Lemmatization is used to find the root word. This paper essentially maps out the state-of-the-art in cyberbullying detection research and serves as a resource for researchers to determine where to best direct their future research efforts in thisfield. Keywords: Abuse and crime involving computers, natural language processing, sentiment analysis, social networking
Published Version
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