Study of the viability of using twitter sentiment analysis in the hotel industry

Abstract:

Twitter is a form of microblogging that is a very popular way of communication nowadays. The authors of these messages usually share thoughts, emotions and different types of subjective and objective data. Hence, microblogging has become a great source for opinion mining. However, is there enough relevant data to the hotel industry in Twitter? In this paper we focus on search and analyze sentiments from Twitter data. This analysis aims to know whether Twitter data is a useful source for generating hotel rankings or not. Our contribution is in regards the public opinion of the best hotels in the city of Melbourne, Australia. For this purpose, we did the experiment over 53 million tweets collected for 3 months.

Año de publicación:

2016

Keywords:

• Machine learning
• Twitter
• Hotels rankings
• sentiment analysis
• Elasticsearch

Fuente:

scopus