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https://nccur.lib.nccu.edu.tw/handle/140.119/137753
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| Title: | 社交媒體還能做為公共領域嗎？從情感動員看假資訊操弄對社交媒體公共意見表達與公民參與之影響(3/4)
Can Social Media Still Be a Public Sphere? How Sentimental Mobilization by Disinformation Operation Affects Public Opinion and Civic Engagement on Social Media |
| Authors: | 鄭宇君
Cheng, Yu-Chung
黃瀚萱 |
| Contributors: | 傳播學院 |
| Keywords: | 社交媒體;運算宣傳;假資訊;大數據分析;公共意見;情感動員
social media;computational propaganda;disinformation;big data analysis;public opinion;sentimental mobilization |
| Date: | 2023-07 |
| Issue Date: | 2021-11-11 13:38:09 (UTC+8) |
| Abstract: | 社交媒體曾被視為網絡化公共領域的實踐，如今運算宣傳成為常態，假資訊操弄的目的在於擾亂社交平台訊息擴散，並影響公共意見表達與公民參與集體行動，特別是散佈焦慮、憤怒、恐懼等負面情緒進行動員。因此，本計畫的核心關懷是社交媒體還能做為公共領域嗎？研究問題意識是從情感動員看假資訊操弄對社交媒體上的公共意見表達與公民參與之影響，以華人地區重大政治事件為關鍵個案，從訊息來源、社交平台、閱聽人、政府機關及事實查核組織等多重面向探討社交媒體假資訊擴散與操弄的途徑，並分析文字、影音、圖像與政治迷因等不同類型訊息內容的情感動員模式，分別以四個子題進行四年期計畫，四個子題包括（1）重大政治事件之新聞與假資訊來源；（2）社交平台的能供性與假資訊操弄；（3）假資訊內容對閱聽人之情緒感染；（4）澄清更正訊息的擴散效果。本地社會鮮少有系統性、大規模方式收集與分析假資訊在社交平台流通之整體概況，故很難衡量假訊息對公共意見表達之影響。本計畫將從台灣在地脈絡來探討此議題，以大數據方法收集Facebook與Twitter討論台灣與香港重要政治事件之相關貼文，研究設計將以機器學習結合質化分析來處理大量資訊，從中挖掘不同類型的訊息內容與閱聽人情緒反應之關係，進而瞭解社交媒體的假資訊操弄對公民意見表達與情緒動員之影響，重新探詢社交媒體做為公共領域之可能條件。
Social media were once considered as a realization of networked public spheres. However, computational propaganda, in which disinformation is distributed to disrupt the flow of information and distort the expression of public opinion on social media, is becoming prevalent. A major outcome of disinformation campaign on social media is to turn the social media into a platform of sentimental mobilization, using negative sentiments such as anxious, anger, and fear. Therefore, this project aims to study if the social media can still be a public sphere. Research proposed in this project will characterize how the disinformation operation affects the public opinion and civic engagement on social media in major political events in the Chinese-speaking societies. The dissemination of disinformation will be examined from the perspectives of the source of disinformation, the social media platforms, the audience, the government and the fact-checking organizations to entail the process of disinformation and its effects. Furthermore, the text, image, and video contents will be analyzed to understand how these information contents sentimentally mobilize the public via social media. The four specific aims are to identify and characterize (1) the sources of disinformation in these major political events, (2) the affordance of social media for disinformation operation, (3) the contagious sentiments aroused by the disinformation contents among the audience, and (4) the efficiency of counter-disinformation efforts such as fact-checking and clarification.There are few large-scale studies on the dissemination and effects of disinformation on social media in a local setting. This project will focus on local events in Taiwan but will also study political events in Hong Kong since the two societies have significant mutual influences on each other. Big-data approach will be used to study the posts containing keywords related to specific political events in Taiwan and Hong Kong on the major social media platforms in these two societies, namely Facebook and Twitter. Machine learning will be used in combination with qualitative analyses to categorize and characterize the collected data in order to identify the emotional responses to different types of posts among the audience. From there, this project will trace the effects of disinformation operation and sentimental mobilization on the expression of public opinion. Understanding these issues will allow us to reevaluate the place of the social media in the public sphere. |
| Relation: | 科技部, MOST109-2628-H004-001-MY4 , 11108-11207 |
| Data Type: | report |
| Appears in Collections: | [傳播學院] 國科會研究計畫
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