Sentiment Analysis of Twitter User Data on Punjab Legislative Assembly Election, 2017
Akhilesh Kumar Singh, Deepak Kumar Gupta, Raj Mohan Singh · International Journal of Modern Education and Computer Science · 2017
SentimentAnalysis is the way of gathering and inspecting data based on the personal emotions, reviews, and contemplations.The sentimental analysis is also recognized as opinion mining since it mines the major feature from people opinions.There are various social networking platforms, out of which Twitter is praised by lawmakers, academicians, and journalists for its potential political values.In literature, numerous studies have been performed on the data ecstatic to elections on Twitter.The greater part of them has been on the U.S Presidential Elections where there are two main applicants who fight it out.Since individuals discuss so many political parties and candidates and their prospects too in rendered messages, the issues of distinguishing their political feeling become extensive and fascinating.Consideration of all these aspects along with a sheer volume of data propelled us to look into the data and find interesting inferences in it.To select the 117 members of the Punjab Legislative Assembly, Legislative Assembly election was held in Punjab, the State of India on 4 February 2017.As per the Election Commission, a total of 1.9 crore voters is eligible for voting in August 2016 in Punjab.The data set that is collected with the help of Twython was analyzed to find out trivial things and interesting patterns in the data.The central idea of this research paper is to carry out the sentiment analysis on Legislative Assembly election 2017 that was held in the Punjab, a state of India for the Political Parties like BJP, INC, and AAP.We have analyzed and fetch significant implications from the tweets gathered over the whole period of elections.