Towards understanding cross-cultural crowd sentiment using social media

Abstract

Social media such as Twitter has been frequently used for expressing personal opinions and sentiments at different places. In this paper, we propose a novel crowd sentiment analysis for fostering cross-cultural studies. In particular, we aim to find similar meanings but different sentiments between tweets collected over geographical areas. For this, we detect sentiments and topics of each tweet by applying neural network based approaches, and we assign sentiments to each topic based on the sentiments of the corresponding tweets. This permits finding cross-cultural patterns by computing topic and sentiment correspondence. The proposed methods enable to analyze tweets from diverse geographical areas sentimentally in order to explore cross-cultural differences.