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Your search keyword '"Ma, Xiaojuan"' showing total 17 results
Start Over Author "Ma, Xiaojuan" Journal proceedings of the acm on human-computer interaction
17 results on '"Ma, Xiaojuan"'

5. Persua: A Visual Interactive System to Enhance the Persuasiveness of Arguments in Online Discussion

Author

Xia, Meng, Zhu, Qian, Wang, Xingbo, Nie, Fei, Qu, Huamin, and Ma, Xiaojuan

Subjects
FOS: Computer and information sciences, Human-Computer Interaction, Computer Science - Machine Learning, Computer Science - Computation and Language, Computer Networks and Communications, Computer Science - Human-Computer Interaction, Computation and Language (cs.CL), Social Sciences (miscellaneous), Human-Computer Interaction (cs.HC), Machine Learning (cs.LG)
Abstract

Persuading people to change their opinions is a common practice in online discussion forums on topics ranging from political campaigns to relationship consultation. Enhancing people's ability to write persuasive arguments could not only practice their critical thinking and reasoning but also contribute to the effectiveness and civility in online communication. It is, however, not an easy task in online discussion settings where written words are the primary communication channel. In this paper, we derived four design goals for a tool that helps users improve the persuasiveness of arguments in online discussions through a survey with 123 online forum users and interviews with five debating experts. To satisfy these design goals, we analyzed and built a labeled dataset of fine-grained persuasive strategies (i.e., logos, pathos, ethos, and evidence) in 164 arguments with high ratings on persuasiveness from ChangeMyView, a popular online discussion forum. We then designed an interactive visual system, Persua, which provides example-based guidance on persuasive strategies to enhance the persuasiveness of arguments. In particular, the system constructs portfolios of arguments based on different persuasive strategies applied to a given discussion topic. It then presents concrete examples based on the difference between the portfolios of user input and high-quality arguments in the dataset. A between-subjects study shows suggestive evidence that Persua encourages users to submit more times for feedback and helps users improve more on the persuasiveness of their arguments than a baseline system. Finally, a set of design considerations was summarized to guide future intelligent systems that improve the persuasiveness in text., Comment: This paper will appear in CSCW 2022

Published
2022
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7. PlanHelper

Author

Liu, Chengzhong, primary, Huang, Zeyu, additional, Liu, Dingdong, additional, Zhou, Shixu, additional, Peng, Zhenhui, additional, and Ma, Xiaojuan, additional

Published
2022
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14. CASS

Author

Wang, Liuping, primary, Wang, Dakuo, additional, Tian, Feng, additional, Peng, Zhenhui, additional, Fan, Xiangmin, additional, Zhang, Zhan, additional, Yu, Mo, additional, Ma, Xiaojuan, additional, and Wang, Hongan, additional

Published
2021
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15. Love in Lyrics

Author

Kim, Taewook, primary, Lee, Jung Soo, additional, Peng, Zhenhui, additional, and Ma, Xiaojuan, additional

Published
2019
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