Affiliation:
1. Ramrao Adik Institute of Technolgy, India
Abstract
The expeditious increase in the adoption of social media over the last decade, determining and analyzing the attitude and opinion of masses related to a particular entity, has gained quite an importance. With the landing of the Web 2.0, many internet products like blogs, community chatrooms, forums, microblog are serving as a platform for people to express themselves. Such opinion is found in the form of messages, user-comments, news articles, personal blogs, tweets, surveys, status updates, etc. With sentiment analysis, it is possible to eliminate the need to manually going through each and every user comment by focusing on the contextual polarity of the text. Analyzing the sentiments could serve a number of applications like advertisements, recommendations, quality analysis, monetization provided on the web services, real-time analysis of data, analyzing notions related to candidates during election campaign, etc.
Reference17 articles.
1. Sentiment analysis in multiple languages
2. Cambridge University Press. (2008). Cambridge online dictionary. Author.
3. Challenges of Sentiment Analysis for Dynamic Events
4. Feature Analysis for Fake Review Detection through Supervised Classification
5. Go, A., Bhayani, R., & Huang, L. (2009). Twitter sentiment classification using distant supervision.CS224N Project Report, 1(12).