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Detection of Inappropriate Anonymous Comments Using NLP and Sentiment Analysis

  • N. Sai NikhitaEmail author
  • V. Hyndavi
  • M. Trupthi
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 3)

Abstract

The world became interactive and socially active now-a-days because of the increase in different types of content sharing applications. These content sharing applications are social media platforms which provide various features so that users can effectively interact and share their thoughts and ideology. One such platform is a discussion forum which promises the anonymous posting of user’s views and complaints. The spammers target the forums as the craze of the forums increase. Though these platforms act as medium of knowledge sharing, all of the users don’t use these platforms for a positive cause. They are also being used to abuse or bully targeted people taking advantage of their anonymous feature. Spamming and cyber bullying has grown rapidly to a limit that social media is being termed harmful. By reading spam and vulgar comments, readers will be diverted. Main aim is to detect these bad comments which are vulgar, inappropriate or not related to the specific context. The research is not based on the static contents but it live streams the comments and the entire research is being done. The research is based on NLP, Sentiment calculation and topic detection.

Keywords

PPM algorithm TEM algorithm SAM algorithm Latent Dirichlet Allocation (LDA) Natural Language Processing (NLP) Machine learning Topic extraction 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Chaitanya Bharathi Institute of TechnologyHyderabadIndia

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