Towards Understanding Cross-Cultural Crowd Sentiment Using Social Media
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.
KeywordsCrowd sentiment analysis Similar but sentimentally different Cross-cultural studies
This work was partially supported by MIC SCOPE (#171507010), and JSPS KAKENHI Grant Numbers 16H01722, 17K12686, 17H01822.
- 2.Go, A., Bhayani, R., Huang, L.: Twitter sentiment classification using distant supervision. CS224N Project Report, Stanford 1, 12 (2009)Google Scholar
- 4.McCollister, C.: Predicting author traits through topic modeling of multilingual social media text. Ph.D. thesis, University of Kansas (2016)Google Scholar
- 5.Mohd Pozi, M.S., Kawai, Y., Jatowt, A., Akiyama, T.: Sketching linguistic borders: mobility analysis on multilingual microbloggers. In: WWW 2017, pp. 825–826 (2017)Google Scholar
- 7.Rudra, K., Rijhwani, S., Begum, R., Bali, K., Choudhury, M.: Understanding language preference for expression of opinion and sentiment: what do Hindi-English speakers do on twitter? In: EMNLP 2016, pp. 1131–1141 (2016)Google Scholar
- 8.Silva, T.H., de Melo, P.O.S.V., Almeida, J., Musolesi, M., Loureiro, A.: You are what you eat (and drink): identifying cultural boundaries by analyzing food and drink habits in foursquare. In: ICWSM 2014, (2014)Google Scholar