Sentiment Analysis From Facebook Comments

Abstract

Social Network Sites are an excellent location for Internet users to stay in contact, share data about their day to day exercises and interests, distributing and getting reports, photographs and recordings. Social Network Sites like Facebook, Twitter and Google+ provide the capacity to make profiles, to have a rundown of friends to collaborate with and to post and peruse what others have posted. Sadly, Social Network Sites are likewise the best spot for expansion of harmful information. Cyberbullying, sexual predation, self-harm rehearses induction are a portion of the viable consequences of the spread of vindictive information on Social Network Sites. We detect the comments, Is it in position, positive or neutral way? For this task we divided the complete work into two sections: sentiment detection and analyzing the ability to detect sentiment from such a special category of texts. For visualization here we use Matplotlib, Seaborn, NumPy. For graph visualization we use scatterplot, word cloud and for visualization we bring word cloud from monkey learning website. For overall tasks we have utilized Natural Language Toolkit (NLTK) and TextBlob, which are publicly available python packages.