Emotive Expressions on Social Chatbot
Keywords:
emotive, social skill, emotional skill, social chatbot, artificial intelligenceAbstract
Building social chatbots to address users' needs for communication and affection is of great value to society (Shum et al., 2018). One of which, Replika, attempts to become an artificial intelligent companion by demonstrating sufficient social and emotional skills through emotive expressions. Emotive expressions are imperative in human-computer interaction, since they tend to elicit social cooperation. The present article aims to survey emotive expressions developed on Replika in order to determine the chatbot's active-reactive skills. They are collected by means of participant observation and are analysed with qualitative method. The present article observes six emotive expressions which Replika can process. These expressions include apologizing, thanking, condoling, complimenting, greeting, and welcoming. The generation of each expression is dependent of the context of each interaction.
References
Augello, A., et al. (2016). A Model of Social Chatbot. In G. D. Pietro., et al. (Eds.). In Intelligent Interactive Multimedia Systems and Services 2016 (pp. 637-647).
Brandtzaeg, P. B., & Folstad, Asbjorn. (2017). Why People Use Chatbots. In I. Kompatsiaris, et al. In Internet Science: 4th International Conference (pp. 22-24).
Jakobson (1960). Linguistics and Poetics. Retrieved from https://pure.mpg.de/rest/items/item_2350615/component/file_2350614/content
Kawulich, B. B. (2005). Participant Observation as a Data Collection Method. Forum: Qualitative Social Research, 6(2): 43-71.
Khan, R., & Das, A. (2018). Build Better Chatbots A Complete Guide to Getting Started with Chatbots. New York: Apress.
Maiz-Arevallo, C. (2017). Expressive Speech Acts in Educational E-Chats. Sociocultural Pragmatics, 5(2) 1-28.
Ospina, S. (2004). Qualitative Research. In Encyclopedia of Leadership. Thousand Oaks: Sage Publications.
Perikos, I., & Hatzilygeroudis, I. (2013). Recognizing Emotion Presence in Natural Language Sentences. In L. Illiadis and C. Jayne (Eds.), International Conference on Engineering Applications of Neural Networks (pp. 30-39). Rhodes: Springer.
Phillips, C. (2018, Mar 10). Why Your Chatbot's Greeting is Its Most Important Response. Retrieved from https://chatbotsmagazine.com/why-your-chatbots-greeting-is-its-most-important-response-3278898dc7a3
Ptaszynski, M., et al. (2014). Detecting Emotive Sentences with Pattern-Based Language Modelling. Procedia Computer Science, 35: 484-493.
Ronan, P. (2015). Categorizing Expressive Speech Acts in the Pragmatically Annotated SPICE Ireland Corpus. ICAME Journal, 39: 25-45.
Searle, J. R., & Vanderveken, D. (1985). Foundations of Illocutionary Logic. Cambridge: Cambridge University Press.
Shum et al., (2018). From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbots. Frontiers of Information Technology & Electronic Engineering, 19(1): 10-26.
Zamora, J. (2017). I'm Sorry, Dave, I'm Afraid I Can't Do That: Chatbot Perception and Expectations. In Proceedings of the 5th International Conference on Human Agent Interaction (pp. 253-260).
Zhou, H., et al. (2018). Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (pp. 730-738). New Orleans: Association for the Advancement of Artificial Intelligence.