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    題名: 社交媒體上的華語新詞分析：以COVID-19為例
    Analysis of Mandarin Chinese Neologisms on Social Media: Take COVID-19 as an Example
    作者: 何孟青
    Ho, Meng-Ching
    貢獻者: 張瑜芸
    Chang, Yu-Yun
    何孟青
    Ho, Meng-Ching
    關鍵詞: 新詞
    COVID-19
    準則分析
    Neologism
    COVID-19
    Criteria analysis
    日期: 2024
    上傳時間: 2024-12-02 11:26:49 (UTC+8)
    摘要: 現代社會事件由於社交媒體的龐大用戶群體與便利性，迅速在各大平台上分享與討論。在討論和交流社會事件的過程中，新詞應運而生，以滿足溝通和信息傳遞的需求。本研究旨在識別和分析突發事件中新詞的共同模式和特徵。通過應用包含多個面向的五項標準，本研究對COVID-19 大流行期間出現的新詞進行了分析，試圖揭示這些新詞的特性，從而有助於識別與突發事件相關的關鍵詞。
    結果顯示，大多數COVID-19 新詞在2020 年之後出現，與事件的爆發及進程相符，而另一些新詞則顯示出其意義因疫情而產生變化。新詞同樣可以在研究論文中和像PTT 這樣的社交媒體平台上見到，用以探討各種與新冠肺炎相關的議題。本研究還指出，複合詞和熟悉的詞素單位在新詞的創造和傳播中扮演著關鍵作用，而統計方法如KL 散度及構詞規則可以應用於未來突發事件的關鍵詞識別。本研究運用五個準則分析COVID-19 期間所產生的新詞，並找出其共同的特徵，有益於未來運用於偵測突發事件中的關鍵字詞。
    Modern social events are quickly shared and debated on social media platforms because of their large audiences and ease of use. During discussions and communication about social events, neologisms emerge to meet the need to communicate and transfer information. The study aims to identify and analyze the common patterns and characteristics of the neologisms that emerge during sudden events. Neologisms that appeared during COVID-19 pandemic are analyzed by applying the five criteria that include multiple aspects. The study attempts to discover the properties of such neologisms, and in turn help identify keywords relevant to sudden events.
    The results reveal that most COVID-19 neologisms appeared after 2020, aligning with the novelty of the event, while others show changes in meaning. Neologisms can also be seen in research papers and social media platforms like PTT, addressing diverse topics related to the pandemic. The study also points out that compounding and familiar word units being key in coining and disseminating neologisms. Statistical methods like KL divergence and word formation rules can be employed to help identify keywords of a sudden event in the future. To conclude, this study employs five criteria to analyze the neologisms appeared during the COVID-19 period and identifies their common characteristics, which can be beneficial for detecting keywords related to sudden events in the future.
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    描述: 碩士
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    語言學研究所
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