1. Sentiment analysis based on comments from online social network
Authors : Vedant Patil, Jayesh Thakurand, Kapildev Yadav
Pages : 49-51
DOI : http://dx.doi.org/10.21172/1.132.08
Keywords : Sentiment Analysis, Plutchik’s Wheel, Machine Learning, Data Mining. Abstract :Internet is the platform where most of us share our happiness or other feelings. Recent years are devoted in studying and mining the data which is on social platform. This task includes understanding explicit and implicit information conveyed by sentiments. It can be extracted from the comments on social media using dictionary-based sentiment analysis or Review-Seer. Comments of the person are important to analyze the sentiments of the person at the time of writing the comment. The task is to classify the comments into positive, negative and neutral sentiments further into different emotions, for which it uses the concept of Plutchik’s wheel of emotions and further makes a dictionary. The system will take input from user to classify and predict the emotions and strength of that emotion (Negative Emotions). There are basic eight emotions and system will primarily focus on negative emotions. Plutchik’s wheel of emotion gives joy and sadness, anger and fear, trust and disgust, surprise and anticipation. The use of Plutchik’s wheel of emotions will provide the real emotional view of comments. The confidence of the will be given which will indicate the strength of feeling. It uses fuzzy logic approach using Naïve Bayes or decision tree algorithm for prediction and generates output.
Citing this Journal Article :Vedant Patil, Jayesh Thakurand, Kapildev Yadav, "Sentiment analysis based on comments from online social network", Volume 13 Issue 2 - April 2019, 49-51
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