A Novel of Sentimental Analysis of Twitter Data for Political Party Using Machine Learning Techniques
Keywords:
Sentiment analysis, data mining, social media, machine learning, Positive/Negative aspects of dataAbstract
Sentiment analysis is that the mathematical study of people’s opinions, sentiments, attitudes, and emotions expressed in written communication. It’s one of the foremost active research areas in NLP and text mining in recent years. Its popularity is especially thanks to two reasons. First, it is a good range of applications because opinions are central to most human activities and are key influencers of our behaviours. Whenever we'd wish to form a choice, we might wish to hear others’ opinions. Second, it presents many challenging research problems, which had never been attempted before the year 2000. it's thus no surprise that the inception and thus the rapid growth of the world coincide with those of the social media on the web. The research has also spread outside of computing to management sciences and social sciences because of its importance to business and society as a whole to implement an algorithm for automatic classification of text into positive, negative, and neutral. Sentimental analysis to work out the attitude of the mass is positive, negative, and neutral towards the topic of interest. We make a Graphical representation of the sentiment within a sort of pie-chart. In this analysis, we will extract 500 tweets and Analyse that all data set and will show the result in the form of a graph which will be following (Pie-chart, Bar graph, and Scatter Plot) and will also show some data table in which Subjectivity and polarity of tweets will show. This proposed system will be used to understand the winning chances of the political party and to analyses the response of the public on the particular political decision during the election campaign.
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Copyright (c) 2024 L.Vetrivendan, Arjun K P, Anandhan K, V. Arul (Author)
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