Abstract
Nowadays social media like Twitter and Facebook etc. is one of the key players. Twitters are micro blogging sites by which users sent their opinions and views in brief. The information generated by one user can be seen by everyone. Therefore to analyze twitter sentiment can be a crucial task. For this task, we have used various approaches like novel based approach and machine learning and many other rules like context awareness are used for the detection of public opinion and prediction of results. We are studying the user tweets during elections. Meaningful tweets are collected on a definite period.The feasibility of the developed classification model is identified by our proposed work to identify the political orientation on the tweets and other user-based features. The technique for the collection of tweets in time has played an important role. When the outcome of applied technique competes with survey agencies result was published before elections result.
Highlights
Nowadays almost every person expresses their sentiments on online social sites like blogs, websites, microblogs etc.Twitter is a popular microblogging site.People can give their ideas or views about these sites.Tweets have very short length they are mainly used in analysis of sentiments
Our proposed work is on topic extraction related with real time events. 2019 legislative assembly elections of states in India.Twitter analyzation was done on a data set containing(1000) of tweets.These tools are designed for elections based on Community based recommendation system.It works as a channel for user communication system
Microblog(Twitter) can help in the prediction of elections result before the actual declaration date
Summary
Nowadays almost every person expresses their sentiments on online social sites like blogs, websites, microblogs etc.Twitter is a popular microblogging site.People can give their ideas or views about these sites.Tweets have very short length they are mainly used in analysis of sentiments. Tools that work on mines and customs are not used in micro-posts due to lack of context [8]ssss This information is meaningful in many subjects where context is large. In brief sentiment analysis is opinion mining It has three different levels: Document Level Sentence Level Aspect Level In Document Level complete document is used to express Sentiments. Sentiment analysis is done only on That sentences which gives personal facts subjective sentences because the objective sentence does not hold subjective information It reduces the accuracy of the result
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