Social media connect individuals in different geographical location and allow people of different political and cultural backgrounds to discuss and participate in events that occur in distant corners of the globe. But, this does not suggest that social media promote homogeneous globalization. Rather, the local and its interactions with the global or regional views remain a powerful force in the realm of social media. The purpose of this paper is to take on the local/global factors in the social media service Twitter and analyzed the keyword-captured Chinese language tweets relating to the 2012 presidential election in Taiwan.
Language code usage was used to sort out the community origins of Chinese language tweets relating to the election, given that distinct types and codes of Chinese characters are used within each political border. Community-specific patterns of communication were identified by cross-correlating language styles, tweeting frequency and participating users. Social network analysis was used to further characterize the local factors in the global social media.
The authors found that the language styles and character types can be used to identify the regions to which the users belong. The authors were able to identify community-specific patterns of communication and reconstruct a social network that exhibits local characteristics.
The results demonstrate that language code can be used to identify the community origin of Chinese tweets. This will enable fine-grain content-based analysis of the Chinese language social media.
The authors would like to thank Dr Tsai-Yen Li (Professor, Department of Computer Science, NCCU, Taiwan), Shiuh-Feng Shih (Department of Computer Science, NCCU, Taiwan) and Yuxian Eugene Liang (Department of Management Information Systems, NCCU, Taiwan) for their contributions to data collection and analysis.
Cheng, Y.-C. and Chen, P.-L. (2014), "Global social media, local context: A case study of Chinese-language tweets about the 2012 presidential election in Taiwan", Aslib Journal of Information Management, Vol. 66 No. 3, pp. 342-356. https://doi.org/10.1108/AJIM-09-2013-0092
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