Real-Time Lexicon-Based Sentiment Analysis Experiments On Twitter With A Mild (More Information, Less Data)


Arslan Y., Birturk A. , Djumabaev B., Kucuk D.

IEEE International Conference on Big Data (IEEE Big Data), Massachusetts, United States Of America, 11 - 14 December 2017, pp.1892-1897 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Massachusetts
  • Country: United States Of America
  • Page Numbers: pp.1892-1897
  • Keywords: sentiment analysis, social media, data mining

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.