頁數:121﹣165
探索2012年台灣總統大選之社交媒體浮現社群:鉅量資料分析取徑
Emerging Communities in Social Media During the 2012 Taiwanese Presidential Elections: A Big-Data Analysis Approach
2014/
120
作者(中) 鄭宇君、陳百齡
作者(英) Yu-Chung Cheng, Pai-Lin Chen
關鍵詞(中) 台灣總統選舉、社交媒體、鉅量資料、網絡分析、網路社群、Twitter
關鍵詞(英) Big Data, network analysis, online community, social media, Taiwanese presidential elections, Twitter
中文摘要 即時性社交媒體的出現與普及促使全球化與在地化的界線模糊,然而不同社群參與同一事件的討論,仍有全球觀點與在地觀點的差異與交融。研究者嘗試透過社交媒體鉅量資料分析取徑,探索在全球社交媒體中不同形式網路社群的浮現方式。

本研究選擇2012年台灣總統大選為關鍵個案,透過Twitter API搜集中文使用者在Twitter上關於台灣總統大選的討論資料,藉由tweets使用的主要語言類別區分出不同語言社群,探討這些不同語言社群對台灣總統大選的關注程度,進而比較Twitter繁體中文與簡體中文社群在大選前後傳播模式的動態變化。研究發現,Twitter做為全球社交媒體,使用者傳播模式深受在地脈絡影響,包括使用者與事件位置的鄰近性、使用者與社群關係的緊密程度。
英文摘要 The widespread use of social media has promoted the blurring of geographical boundaries in recent years. Users from various countries can discuss events and topics that occur in any location. However, discussions of the same event or topic may still differ between communities because conformity to the global viewpoint varies based on local political and cultural backgrounds. Distinguishing the contents and modes of communication of various global social media communities is a major challenge in communication research. To address this concern, we investigated the 2012 Taiwanese presidential election. This election was both a local event and a global issue of discussion, both among Twitter users from Taiwan and in several foreign Twitter communities. We applied a Big-Data approach for analyzing the difference in the interests of different communities with respect to this election and the dynamics in their modes of communication. Local Taiwanese Twitter users engaged in heavy discussion before, during, and after the election. However, users from China mostly disclosed their concerns by retweeting and began discussing the election only once it was completed. By contrast, Japanese users “broadcasted” the news and only retweeted content published by news agencies. Thus, the results of this study indicated that the different patterns and modes of communication of social media communities that use different language codes can be identified.
 
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