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Srividhya, V.
- Sentiment Analysis on Good Service Tax (GST) Using Twitter Data
Authors
1 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore-43, IN
Source
Software Engineering, Vol 10, No 3 (2018), Pagination: 57-60Abstract
The social media has increased the opportunity to explore and track the response of new reforms and policies in India. Social Media helps in the analysis of stock market data, new product launch and movie release. One of the social networking websites is Twitter and it is the ninth largest website.
With Twitter, the registered users can search for the latest information on the topics of their interest. Since lakhs of tweets are shared on a real-time basis by the members every day, it has got more than 328 million active users a month. Twitter is the best source for the analysis of opinion and sentiment on movie reviews, product reviews and current issues in the world. Twitter is used widely as a forum for understanding the sentiments of Indians towards recently launched Goods and Services Tax by the Indian Government on 1st July 2017.
Sentiment analysis extracts positive and negative opinions from the twitter dataset and R Studio provides the best environment for this Twitter sentiment analysis. Data is written into text files as the input dataset so that Twitter data could be accessed from Twitter API. Sentiment analysis is performed on the input dataset that initially performs data cleaning by removing the stop words and then by classifying the tweets as positive and negative by considering the polarity of words. Finally, positive, negative and neutral is generated, comparing the polarity of the tweets.
Keywords
Twitter Data, Word Cloud, Sentiment Analysis, Social Media R-Studio.
- Emotion Classification of Twitter Data Using Lexicon Based Approach
Authors
1 Department of Computer Applications, K.S Rangasamy College of Arts & Science for Women, Tiruchengode - 637215, IN
2 Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore - 43, IN
Source
Software Engineering, Vol 10, No 4 (2018), Pagination: 69-71Abstract
The main aim of sentiment analysis is to determine the attitude of a speaker or a writer with respect to some topic. The sentiment classification has been classified into two types which are emotional classification and polarity classification. This research work has been done by using emotional classification, which is used to classify the emotions such as joy, fear, disgust, anger, sad and surprise. These six types of emotions are classified using twitter dataset. The classified emotions are visualized using graph. The work is focused on analyzing the tweets of people for Donald Trump and Hillary Clinton and classifies the sentiment from tweets.