The Emotion Analysis of Indian Political Tweets using Machine Learning
DOI:
https://doi.org/10.32628/CSEIT2410255Keywords:
Sentiment Analysis, Machine Learning, Twitter Data Analysis, Classification, Political Analysis, Emotion AnalysisAbstract
In this day and age web-based entertainment is a major region for information examination and exploration work. For Feeling Examination, I select Tweeter handle. I use Tweepy for getting to tweeter information. I perform opinion examination on Indian Political information. I got 117545 tweets of 2019 Indian Political race. I use SVM (Backing Vector Machine) Classifier for feeling Examination. Feeling assessment oversees recognizing and portraying evaluations or sentiments conveyed in source message. Electronic diversion is creating an enormous proportion of feeling rich data as tweets, sees, blog sections, etc. Feeling examination of this client made data is especially useful in knowing the appraisal of the gathering. Twitter feeling assessment is problematic stood out from general assessment examination on account of the presence of work related conversation words and erroneous spellings. The most outrageous limitation of characters that are allowed in Twitter is 140. Data base philosophy and AI approach are the two frameworks used for separating suppositions from the text. In this paper, we endeavor to analyze the twitter posts about electronic things like mobiles, workstations, etc using AI approach.
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