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題名 降低多人遊戲中惡毒言論行為之探討與設計: 運用貼圖機制緩解惡毒言論攻擊
Discussion and Design to Reduce Toxic Language Behavior in Multiplayer Games: Use the Emoji Mechanism to Ease Toxic Language Attacks.
作者 陳彥廷
Chen, Yian-Ting
貢獻者 劉昭麟<br>許志堅
Liu, Chao-Lin<br>Sheu, Jyh-Jian
陳彥廷
Chen, Yian-Ting
關鍵詞 惡毒行為
表情貼圖
遊戲
Toxic behavior
Emojis
Game
日期 2022
上傳時間 2-Dec-2022 15:20:06 (UTC+8)
摘要 隨著網際網路及各種科技的進步,線上遊戲已成為現今大多數人休閒活動的主要選擇之一。然而線上遊戲的通訊功能因為不受距離限制和匿名的方式衍伸出一個問題「惡毒言論」,這種負面行為除了影響人們對於網路的使用,更可能在現實生活中造成受害者的負面情緒。目前業界雖然已提出幾種解決方案,但都未有明確的研究表明其成效。

本研究提供一種緩和惡毒言論攻擊的方式,利用表情貼圖結合文字探勘嘗試降低使用者遭受惡毒言論攻擊時的負面影響,並實作一款模擬多人遊戲檢測實驗效果。實驗過程中包括三個部分,分別為純文字惡毒言論、表情貼圖輔助緩解惡毒語句模組以及表情貼圖取代惡毒關鍵字模組,根據不同表情貼圖的使用方式和原始的惡毒言論攻擊作對比,最後利用問卷及遊戲內的數據分析表情貼圖系統是否達到研究預期的效果。

實驗結果顯示,表情貼圖確實能夠降低惡毒言論攻擊帶來的負面影響,並且表情貼圖取代惡毒關鍵字模組的緩和效果最為顯著。除了表情貼圖的活潑與正向性降低惡毒言論的負面情緒外,將惡毒關鍵字轉換為表情貼圖,避免使用者直接看到惡毒文字也是降低其負面情緒的主要原因之一。此外,實驗結果也發現使用者的貼圖使用經驗及表情貼圖的好感度對於是否能夠緩解惡毒言論攻擊具有一定程度的影響。
With the advancement of the Internet and various technologies, online games has become one of the main choices for most people`s leisure activities today. However, the communication function of online games has created a problem "toxic language" because of its unrestricted and anonymity. In addition to affecting people’s use of the network, this negative online influence is more likely to cause them negative emotions in real life. At present, although several solutions have been proposed in the industry, there is no clear research to show their effectiveness.

The purpose of this research is to provide a way of mitigating toxic language attacks, using emojis system combined with text mining to try to reduce the negative impact of the abused. And a simulated multiplayer game was implemented to detect the effect of the experiment. The experiment includes three parts, namely, the text of sheer malicious speech, the sentence module with emojis to help alleviate toxic speech, and the module using emojis to replace toxic word. A comparison was made between different ways of using emojis with the original text of toxic speech. In the end, the questionnaire and game data were analyzed to show whether the emojis system had the expected effect of the research.

The result of the experiment has shown that emojis can indeed reduce the negative impact of toxic speech, and the module replacing toxic word with emojis has the most significant mitigating effect. For one thing, the liveliness and positiveness of emojis reduce the negative emotions of malicious speeches. For another, converting toxic word into emojis prevents the abused from reading the malicious text and thus reduces the negative emotions. Furthermore, the result of the experiment also indicated that the user`s experience in using emojis and his favorability of emojis have a certain degree of influence on the alleviating effect.
參考文獻 陳祈年(2005)。動機、可玩性與社交性對於多人線上角色扮演遊戲玩家沉浸經驗之影響。國立交通大學傳播研究所碩士論文。

陳智先(2008)。線上遊戲社交性研究:玩家社交活動與第三場域的觀點。國立交通大學傳播研究所碩士論文。

潘育絜(2007)。遊戲社群網路之社交性設計準則研究:角色扮演與互惠觀點。國立交通大學傳播研究所碩士論文。

張瓊怡(2014)。即時通訊APP貼圖訊息之持續使用意圖。國立中央大學資訊管理所碩士論文。

Adinolf, S., & Turkay, S. (2018, October). Toxic behaviors in Esports games: player perceptions and coping strategies. In Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts (pp. 365-372).

Brown, B., & Bell, M. 2004. CSCW at play: ‘there’ as a collaborative virtual environment. In Proceedings of the 2004 ACM conference on Computer supported cooperative work (pp. 350-359).

Blackburn, J., & Kwak, H. (2014, April). STFU NOOB! predicting crowdsourced decisions on toxic behavior in online games. In Proceedings of the 23rd International Conference on World Wide Web (pp. 877-888).

Bai, Q., Dan, Q., Mu, Z., & Yang, M. (2019). A systematic review of emoji: Current research and future perspectives. Frontiers in Psychology, 10, 2221.

Buckels, E. E., Trapnell, P. D., & Paulhus, D. L. (2014). Trolls just want to have fun. Personality and Individual Differences, 67, 97-102.

Barlett, C., Chamberlin, K., & Witkower, Z. (2017). Predicting cyberbullying perpetration in emerging adults: A theoretical test of the Barlett Gentile Cyberbullying Model. Aggressive Behavior, 43(2), 147-154.

Cook, C., Schaafsma, J., & Antheunis, M. (2018). Under the bridge: An in-depth examination of online trolling in the gaming context. New Media & Society, 20(9), 3323-3340.

Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98.

Choi, D., & Kim, J. (2004). Why people continue to play online games: In search of critical design factors to increase customer loyalty to online contents. CyberPsychology & Behavior, 7(1), 11-24.

Ducheneaut, N., Moore, R. J., & Nickell, E. (2004, December). Designing for sociability in massively multiplayer games: an examination of the “third places” of SWG. In Conference Proceedings for Other Players, Center for Computer Games Research, IT University of Copenhagen, DK.

Ducheneaut, N., & Moore, R. J. (2004, November). The social side of gaming: a study of interaction patterns in a massively multiplayer online game. In Proceedings of the 2004 ACM Conference on Computer Supported Cooperative Work (pp. 360-369).

de Mesquita Neto, J. A., & Becker, K. (2018). Relating conversational topics and toxic behavior effects in a MOBA game. Entertainment Computing, 26, 10-29.

Das, G., Wiener, H. J., & Kareklas, I. (2019). To emoji or not to emoji? Examining the influence of emoji on consumer reactions to advertising. Journal of Business Research, 96, 147-156.

Dürscheid, C., & Siever, C. M. (2017). Beyond the alphabet–communcataion of emojis. Kurzfassung eines (auf Deutsch) zur Publikation Eingereichten Manuskripts.

Emmerich, K., Krekhov, A., & Krüger, J. (2020, November). " Pls Uninstall" On the Interplay of the COVID-19 Pandemic and Toxic Player Behavior in Competitive Gaming. In Extended Abstracts of the 2020 Annual Symposium on Computer Human Interaction in Play (pp. 224-228).

Grandprey-Shores, K., He, Y., Swanenburg, K. L., Kraut, R., & Riedl, J. (2014, February). The identification of deviance and its impact on retention in a multiplayer game. In Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp.1356-1365).

Ganster, T., Eimler, S. C., & Krämer, N. C. (2012). Same same but different!? The differential influence of smilies and emoticons on person perception. Cyberpsychology, Behavior, and Social Networking, 15(4), 226-230.

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描述 碩士
國立政治大學
資訊科學系
108753142
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0108753142
資料類型 thesis
dc.contributor.advisor 劉昭麟<br>許志堅zh_TW
dc.contributor.advisor Liu, Chao-Lin<br>Sheu, Jyh-Jianen_US
dc.contributor.author (Authors) 陳彥廷zh_TW
dc.contributor.author (Authors) Chen, Yian-Tingen_US
dc.creator (作者) 陳彥廷zh_TW
dc.creator (作者) Chen, Yian-Tingen_US
dc.date (日期) 2022en_US
dc.date.accessioned 2-Dec-2022 15:20:06 (UTC+8)-
dc.date.available 2-Dec-2022 15:20:06 (UTC+8)-
dc.date.issued (上傳時間) 2-Dec-2022 15:20:06 (UTC+8)-
dc.identifier (Other Identifiers) G0108753142en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/142639-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學系zh_TW
dc.description (描述) 108753142zh_TW
dc.description.abstract (摘要) 隨著網際網路及各種科技的進步,線上遊戲已成為現今大多數人休閒活動的主要選擇之一。然而線上遊戲的通訊功能因為不受距離限制和匿名的方式衍伸出一個問題「惡毒言論」,這種負面行為除了影響人們對於網路的使用,更可能在現實生活中造成受害者的負面情緒。目前業界雖然已提出幾種解決方案,但都未有明確的研究表明其成效。

本研究提供一種緩和惡毒言論攻擊的方式,利用表情貼圖結合文字探勘嘗試降低使用者遭受惡毒言論攻擊時的負面影響,並實作一款模擬多人遊戲檢測實驗效果。實驗過程中包括三個部分,分別為純文字惡毒言論、表情貼圖輔助緩解惡毒語句模組以及表情貼圖取代惡毒關鍵字模組,根據不同表情貼圖的使用方式和原始的惡毒言論攻擊作對比,最後利用問卷及遊戲內的數據分析表情貼圖系統是否達到研究預期的效果。

實驗結果顯示,表情貼圖確實能夠降低惡毒言論攻擊帶來的負面影響,並且表情貼圖取代惡毒關鍵字模組的緩和效果最為顯著。除了表情貼圖的活潑與正向性降低惡毒言論的負面情緒外,將惡毒關鍵字轉換為表情貼圖,避免使用者直接看到惡毒文字也是降低其負面情緒的主要原因之一。此外,實驗結果也發現使用者的貼圖使用經驗及表情貼圖的好感度對於是否能夠緩解惡毒言論攻擊具有一定程度的影響。
zh_TW
dc.description.abstract (摘要) With the advancement of the Internet and various technologies, online games has become one of the main choices for most people`s leisure activities today. However, the communication function of online games has created a problem "toxic language" because of its unrestricted and anonymity. In addition to affecting people’s use of the network, this negative online influence is more likely to cause them negative emotions in real life. At present, although several solutions have been proposed in the industry, there is no clear research to show their effectiveness.

The purpose of this research is to provide a way of mitigating toxic language attacks, using emojis system combined with text mining to try to reduce the negative impact of the abused. And a simulated multiplayer game was implemented to detect the effect of the experiment. The experiment includes three parts, namely, the text of sheer malicious speech, the sentence module with emojis to help alleviate toxic speech, and the module using emojis to replace toxic word. A comparison was made between different ways of using emojis with the original text of toxic speech. In the end, the questionnaire and game data were analyzed to show whether the emojis system had the expected effect of the research.

The result of the experiment has shown that emojis can indeed reduce the negative impact of toxic speech, and the module replacing toxic word with emojis has the most significant mitigating effect. For one thing, the liveliness and positiveness of emojis reduce the negative emotions of malicious speeches. For another, converting toxic word into emojis prevents the abused from reading the malicious text and thus reduces the negative emotions. Furthermore, the result of the experiment also indicated that the user`s experience in using emojis and his favorability of emojis have a certain degree of influence on the alleviating effect.
en_US
dc.description.tableofcontents 第一章 緒論 10
1.1研究背景 10
1.2研究目的 13
第二章 文獻回顧 18
2.1遊戲載體 18
2.2線上多人遊戲類型 23
2.3社交性與惡毒行為 27
2.4表情貼圖 32
第三章 研究方法 37
3.1研究架構 38
3.2研究對象 39
3.3研究流程 39
3.4研究工具 41
3.5遊戲介紹 41
3.5.1遊戲流程 43
3.6對話機制設計 47
3.7文字探勘設計 55
3.8問卷設計 56
3.9.1問卷內容 59
第四章 實驗結果 62
4.1描述性統計 62
4.2信度分析 64
4.3問卷數據分析 66
4.3.1遊戲易用性 66
4.3.2表情貼圖使用情況 67
4.3.3受測者對於惡毒言論攻擊的負面效果感受度 72
4.3.4貼圖系統的緩解效果 78
4.3.5性別對於貼圖系統的感受差異性 80
4.3.6貼圖使用習慣與實際效果 81
第五章 結論與未來工作 85
5.1實驗效果詮釋 85
5.2 研究限制與未來建議 90
參考文獻 92
zh_TW
dc.format.extent 4090081 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0108753142en_US
dc.subject (關鍵詞) 惡毒行為zh_TW
dc.subject (關鍵詞) 表情貼圖zh_TW
dc.subject (關鍵詞) 遊戲zh_TW
dc.subject (關鍵詞) Toxic behavioren_US
dc.subject (關鍵詞) Emojisen_US
dc.subject (關鍵詞) Gameen_US
dc.title (題名) 降低多人遊戲中惡毒言論行為之探討與設計: 運用貼圖機制緩解惡毒言論攻擊zh_TW
dc.title (題名) Discussion and Design to Reduce Toxic Language Behavior in Multiplayer Games: Use the Emoji Mechanism to Ease Toxic Language Attacks.en_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 陳祈年(2005)。動機、可玩性與社交性對於多人線上角色扮演遊戲玩家沉浸經驗之影響。國立交通大學傳播研究所碩士論文。

陳智先(2008)。線上遊戲社交性研究:玩家社交活動與第三場域的觀點。國立交通大學傳播研究所碩士論文。

潘育絜(2007)。遊戲社群網路之社交性設計準則研究:角色扮演與互惠觀點。國立交通大學傳播研究所碩士論文。

張瓊怡(2014)。即時通訊APP貼圖訊息之持續使用意圖。國立中央大學資訊管理所碩士論文。

Adinolf, S., & Turkay, S. (2018, October). Toxic behaviors in Esports games: player perceptions and coping strategies. In Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts (pp. 365-372).

Brown, B., & Bell, M. 2004. CSCW at play: ‘there’ as a collaborative virtual environment. In Proceedings of the 2004 ACM conference on Computer supported cooperative work (pp. 350-359).

Blackburn, J., & Kwak, H. (2014, April). STFU NOOB! predicting crowdsourced decisions on toxic behavior in online games. In Proceedings of the 23rd International Conference on World Wide Web (pp. 877-888).

Bai, Q., Dan, Q., Mu, Z., & Yang, M. (2019). A systematic review of emoji: Current research and future perspectives. Frontiers in Psychology, 10, 2221.

Buckels, E. E., Trapnell, P. D., & Paulhus, D. L. (2014). Trolls just want to have fun. Personality and Individual Differences, 67, 97-102.

Barlett, C., Chamberlin, K., & Witkower, Z. (2017). Predicting cyberbullying perpetration in emerging adults: A theoretical test of the Barlett Gentile Cyberbullying Model. Aggressive Behavior, 43(2), 147-154.

Cook, C., Schaafsma, J., & Antheunis, M. (2018). Under the bridge: An in-depth examination of online trolling in the gaming context. New Media & Society, 20(9), 3323-3340.

Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98.

Choi, D., & Kim, J. (2004). Why people continue to play online games: In search of critical design factors to increase customer loyalty to online contents. CyberPsychology & Behavior, 7(1), 11-24.

Ducheneaut, N., Moore, R. J., & Nickell, E. (2004, December). Designing for sociability in massively multiplayer games: an examination of the “third places” of SWG. In Conference Proceedings for Other Players, Center for Computer Games Research, IT University of Copenhagen, DK.

Ducheneaut, N., & Moore, R. J. (2004, November). The social side of gaming: a study of interaction patterns in a massively multiplayer online game. In Proceedings of the 2004 ACM Conference on Computer Supported Cooperative Work (pp. 360-369).

de Mesquita Neto, J. A., & Becker, K. (2018). Relating conversational topics and toxic behavior effects in a MOBA game. Entertainment Computing, 26, 10-29.

Das, G., Wiener, H. J., & Kareklas, I. (2019). To emoji or not to emoji? Examining the influence of emoji on consumer reactions to advertising. Journal of Business Research, 96, 147-156.

Dürscheid, C., & Siever, C. M. (2017). Beyond the alphabet–communcataion of emojis. Kurzfassung eines (auf Deutsch) zur Publikation Eingereichten Manuskripts.

Emmerich, K., Krekhov, A., & Krüger, J. (2020, November). " Pls Uninstall" On the Interplay of the COVID-19 Pandemic and Toxic Player Behavior in Competitive Gaming. In Extended Abstracts of the 2020 Annual Symposium on Computer Human Interaction in Play (pp. 224-228).

Grandprey-Shores, K., He, Y., Swanenburg, K. L., Kraut, R., & Riedl, J. (2014, February). The identification of deviance and its impact on retention in a multiplayer game. In Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp.1356-1365).

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dc.identifier.doi (DOI) 10.6814/NCCU202201699en_US