DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-3,Issue-1 ( Jan, 2016 ) | |||||||||
Paper Title |
Sentiment Analysis On Twitter | |||||||||
Author Name |
Ananth Nath, Anirudh Sudan, Gautam Kumar, Saurabh Bhosale | |||||||||
Affilition |
Department Of Computer Engineering, MIT Academy Of Engineering, Alandi(D), Pune. | |||||||||
Pages |
106-109 | |||||||||
Abstract |
Twitter is a well-known micro-blogging website which allows millions of users to share their views and opinions on various matters. These tweets are displayed on the twitter UI and various users can interact with each other by using the @redirection to include another username. The trending topics are displayed on the UI. A trending topic is one which is currently the most popular. In this day and age where nearly a billion people have access to the internet to express their views on their day to day activities, data mining and analyzing data from social networks can be difficult because of the large amounts of data involved. Sentiment analysis, which is also called opinion mining is the field of study which analyzes peoples opinions, sentiments, evaluations, appraisals, attributes and emotions towards entities such as products services, organizations, individuals, issues, events, topics, and their attributes through twitter. Sentiment analysis on a website like twitter can play a vital role in helping advertisers and market strategists. A sentiment analysis machine is a type of AI which receives the tweets as its input and after evaluating the input, it will display the sentiment of the user. If implemented properly sentiment analysis can be useful in predicting trends in the market as it provides an insight into the minds of users and potential customers. Index Terms—Sentiment, Analysis, Trending, Data Mining, Ar-tificial Intelligence. | |||||||||
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