Naoki Osaka
Daisuke Sakamoto
Tetsuo Ono
ABSTRACT
A variety of chatbots were developed to elicit people’s emotional responses and manage the emotions of people. These chatbots often use text-based emotional sentences. However, there are few studies that chatbots use extremely simplified communications to induce some emotional responses. We investigated the effect of mood contagion and tried to induce positive or negative words from people on our web-based ”word chain game” system as the most simplified conversational style. We also defined the system’s emotion as making the system use words that have polarity, which means each word’s strength of positive or negative emotion. The result shows that users of the system using positive words were slightly influenced to use more positive words than the neutral or negative system.
- Ivo Benke, Michael Thomas Knierim, and Alexander Maedche. 2020. Chatbot-Based Emotion Management for Distributed Teams: A Participatory Design Study. Proc. ACM Hum.-Comput. Interact. 4, CSCW2, Article 118 (Oct. 2020), 30 pages. https://doi.org/10.1145/3415189Google Scholar
Digital Library
- Mark Davies. 2021. Word frequency data. [Online]. Available: https://www.wordfrequency.info.Google Scholar
- Mauro de Gennaro, Eva G. Krumhuber, and Gale Lucas. 2020. Effectiveness of an Empathic Chatbot in Combating Adverse Effects of Social Exclusion on Mood. Frontiers in Psychology 10 (2020), 3061. https://doi.org/10.3389/fpsyg.2019.03061Google ScholarCross Ref
- Emilio Ferrara and Zeyao Yang. 2015. Measuring Emotional Contagion in Social Media. PLOS ONE 10, 11 (11 2015), 1–14. https://doi.org/10.1371/journal.pone.0142390Google ScholarCross Ref
- Xiusen Gu, Weiran Xu, and Chao Zhang. 2019. Neural Emotional Response Generation via Adversarial Transfer Learning. In Proceedings of the 2019 3rd International Conference on Innovation in Artificial Intelligence (Suzhou, China) (ICIAI 2019). Association for Computing Machinery, New York, NY, USA, 106–110.Google ScholarDigital Library
- Mingming Liu, Qicheng Ding, Yu Zhang, Guoguang Zhao, Changjian Hu, Jiangtao Gong, Penghui Xu, Yu Zhang, Liuxin Zhang, and Qianying Wang. 2020. Cold Comfort Matters - How Channel-Wise Emotional Strategies Help in a Customer Service Chatbot. In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI EA ’20). Association for Computing Machinery, New York, NY, USA, 1–7. https://doi.org/10.1145/3334480.3382905Google ScholarDigital Library
- The Washington Post. 2016. Trolls turned Tay, Microsoft’s fun millennial AI bot, into a genocidal maniac. [Online]. Available: https://www.washingtonpost.com/news/the-intersect/wp/2016/03/24/the-internet-turned-tay-microsofts-fun-millennial-ai-bot-into-a-genocidal-maniac/.Google Scholar
- Masahiro Shiomi, Soto Okumura, Mitsuhiko Kimoto, Takamasa Iio, and Katsunori Shimohara. 2020. Two is better than one: Social rewards from two agents enhance offline improvements in motor skills more than single agent. PLOS ONE 15, 11 (11 2020), 1–14. https://doi.org/10.1371/journal.pone.0240622Google ScholarCross Ref
- Hiroya Takamura, Takashi Inui, and Manabu Okumura. 2005. Extracting Semantic Orientations of Words using Spin Model. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL2005). Association for Computational Linguistics, Ann Arbor, Michigan, 133–140.Google ScholarDigital Library
- Jared B. Torre and Matthew D. Lieberman. 2018. Putting Feelings Into Words: Affect Labeling as Implicit Emotion Regulation. Emotion Review 10, 2 (2018), 116–124. https://doi.org/10.1177/1754073917742706Google ScholarCross Ref
- D. Watson, L. A. Clark, and A. Tellegen. 1988. Development and validation of brief measures of positive and negative affect: the PANAS scales.Journal of personality and social psychology 54 6 (1988), 1063–70.Google Scholar
- Junchao Xu, Joost Broekens, Koen Hindriks, and Mark A. Neerincx. 2014. Robot Mood is Contagious: Effects of Robot Body Language in the Imitation Game. In International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’14, Paris, France, May 5-9, 2014 (Paris, France) (AAMAS ’14). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 973–980.Google Scholar
Index Terms
- A Subtle Effect of Inducing Positive Words by Playing Web-Based Word Chain Game
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