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https://ah.lib.nccu.edu.tw/handle/140.119/138982| 題名: | COVID-19期間對非援助網絡輿情分析：以Twitter為研究標的 Analysis of Public Opinion of the Aid to Africa During COVID-19 Era on Twitter |
作者: | 陳妍如 Chen, Yen-Ju |
貢獻者: | 李明 Lee, Ming 陳妍如 Chen, Yen-Ju |
關鍵詞: | 對非援助 新古典現實主義 民意 R語言 文字探勘 情感分析 Aid to African Neoliberalism public opinion R programming text-mining sentimental analysis |
日期: | 2021 | 上傳時間: | 10-Feb-2022 | 摘要: | 本研究使用R語言撈取Twitter平台上3000筆關於對非援助相關推文，使用情感分析、主題模型分析以及論述分析的方式，一步步剖析探討疫情期間網絡民意在對非援助議題上，所關注的方向及對非援助的成效和立場，並和文獻回顧結果做比較，以完善對非援助議題的研究。\n研究成果分成技術上及文字探勘兩層面來探討，在技術層次上，本研究發現情感分析及主題模型分析在對非援助議題的局限性，在文字探勘的部分，發現學者和網絡民意在對非援助議題上的見解相似，但網絡民意又多了非洲地區的聲量，這部分的意見不但可作為援助系統調整的參考方向，也是學術上可以深入探討的地方。\n社群媒體的發達以及文字探勘技術的進步，亦使得援助國更可取得在地聲音，援助國不應忽視這些聲量，否則會落入投入許多資源、精力，但援助行為非但無法達到促進非洲地區國家發展的良善目的，反而引來接受國的反彈及不諒解。 This study utilizes the “R language” mining tweets regarding aid to Africa on Twitter, using the sentimental, model and discourse analysis to analyze public opinion towards aid issues during the COVID-19 era. The purpose of the study is to find out the aspects that netizens would discuss when they mention aid to African as well as their thoughts regarding the effects of it.\nThe results could be divided into two areas, one is how technology applies to the topic and the other one is the finding of text mining. First, the study found out that sentimental analysis and model analysis on the aid issue have their limitations, and discourse analysis could improve it. On the other hand, the scholars and opinions on Twitter have similar views on problems of aid to Africa. Furthermore, the public opinion on the Internet could let voices from Africa be heard by the world. Opinions could not only be referred to the donor countries for their aid policies, but also be used for further academic research.\nThe development of social media and text mining let the donors get access to more voices from African local people. It is better for the donors to take it seriously, or they would end up involving a lot of resources and energy but receiving rebound and mistrust from recipients. |
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資料來源: | http://thesis.lib.nccu.edu.tw/record/#G0108253009 | 資料類型: | thesis |
| Appears in Collections: | 學位論文 |
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