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    政大機構典藏 > 傳播學院 > 新聞學系 > 期刊論文 >  Item 140.119/71628


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/71628


    Title: Global social media, local context: A case study of Chinese-language tweets about the 2012 presidential election in Taiwan
    Authors: 鄭宇君;陳百齡
    Cheng, Yu-chung;Chen, Pai-lin
    Contributors: 新聞系
    Keywords: Social network;Twitter;Social media;Big data;Chinese tweets;Taiwan presidential election
    Date: 2014-02
    Issue Date: 2014-11-24 15:00:58 (UTC+8)
    Abstract: Purpose-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. Design/methodology/approach-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. Findings-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. Originality/value-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.
    Relation: Aslib Journal of Information Management, 66(3), 342-356
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1108/AJIM-09-2013-0092
    DOI: 10.1108/AJIM-09-2013-0092
    Appears in Collections:[新聞學系] 期刊論文

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