Real-time Lexicon-based sentiment analysis experiments on Twitter with a mild (more information, less data) approach
5th IEEE International Conference on Big Data, Big Data 2017, Massachusetts, United States Of America, 11 - 14 December 2017, vol.2018-January, pp.1892-1897, (Full Text)
- Publication Type: Conference Paper / Full Text
- Volume: 2018-January
- Doi Number: 10.1109/bigdata.2017.8258134
- City: Massachusetts
- Country: United States Of America
- Page Numbers: pp.1892-1897
- Keywords: data mining, sentiment analysis, social media
- TED University Affiliated: No
Abstract
Sentiment analysis of Twitter data is a well studied area, however, there is a need for exploring the effectiveness of real-time approaches on small data sets that only include popular and targeted tweets. In this paper, we have employed several sentiment analysis techniques by using dynamic dictionaries and models, and performed some experiments on limited but relevant datasets to understand the popularity of some terms and the opinion of users about them. The results of our experiments are promising.