extended-abstract

Linguistic Features to Consider When Applying Persona of the Real Person to the Text-based Agent

Authors:

Youjin Hwang,

Seokwoo Song,

Donghoon Shin,

Joonhwan LeeAuthors Info & Claims

MobileHCI '20: 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services

Article No.: 23, Pages 1 - 4

https://doi.org/10.1145/3406324.3410723

Published: 25 February 2021 Publication History

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Abstract

As artificial intelligence (AI) technologies advance, the possibility of developing virtual agents capable of mimicking human beings is increasing. Furthermore, AI techniques applicable to mimicking certain features of a specific person (e.g., facial expression, voice, motion) are becoming more sophisticated. Although the HCI community has explored how to design or develop AI agents mimicking a real person, limited studies on mimicking someone’s text-based behavior shown in the instant messaging exist. This study investigates the features that make users perceive text-based agents as people they know in reality. On top of the previous efforts of designing human-like virtual agents, our work suggests design guidelines for applying the persona of the real person (PRP) to text-based agents.

References

[1]

2011. Tlk.io. https://tlk.io

Google Scholar

[2]

2014. Phoenix. https://fenixbegravning.se

Google Scholar

[3]

2016. Didimo. https://mydidimo.com

Google Scholar

[4]

Lois Bloom and Margaret Lahey. 1978. Language development and language disorders.(1978).

Google Scholar

[5]

Elizabeth Broadbent, Vinayak Kumar, Xingyan Li, John Sollers 3rd, Rebecca Q Stafford, Bruce A MacDonald, and Daniel M Wegner. 2013. Robots with Display Screens: A Robot with a More Humanlike Face Display Is Perceived To Have More Mind and a Better Personality. PLOS ONE 8, 8 (August 2013), 1–9. https://doi.org/10.1371/journal.pone.0072

Crossref

Google Scholar

[6]

Tyler J. Burleigh, Jordan R. Schoenherr, and Guy L. Lacroix. 2013. Does the uncanny valley exist? An empirical test of the relationship between eeriness and the human likeness of digitally created faces. Computers in Human Behavior 29, 3 (2013), 759 – 771. https://doi.org/10.1016/j.chb.2012.11.021

Digital Library

Google Scholar

[7]

Leigh Clark, Nadia Pantidi, Orla Cooney, Philip Doyle, Diego Garaialde, Justin Edwards, Brendan Spillane, Emer Gilmartin, Christine Murad, Cosmin Munteanu, Vincent Wade, and Benjamin R. Cowan. 2019. What Makes a Good Conversation? Challenges in Designing Truly Conversational Agents. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3290605.3300705

Digital Library

Google Scholar

[8]

Julia Fink. 2012. Anthropomorphism and Human Likeness in the Design of Robots and Human-Robot Interaction. In Social Robotics, Shuzhi Sam Ge, Oussama Khatib, John-John Cabibihan, Reid Simmons, and Mary-Anne Williams(Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 199–208.

Digital Library

Google Scholar

[9]

Sang-Su Lee, Jeonghun Chae, Hyunjeong Kim, Youn-kyung Lim, and Kun-pyo Lee. 2013. Towards More Natural Digital Content Manipulation via User Freehand Gestural Interaction in a Living Room. In Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Zurich, Switzerland) (UbiComp ’13). Association for Computing Machinery, New York, NY, USA, 617–626. https://doi.org/10.1145/2493432.2493480

Digital Library

Google Scholar

[10]

François Mairesse, Marilyn A. Walker, Matthias R. Mehl, and Roger K. Moore. 2007. Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text. J. Artif. Int. Res. 30, 1 (Nov. 2007), 457–500.

Crossref

Google Scholar

[11]

Elizabeth Phillips, Xuan Zhao, Daniel Ullman, and Bertram F. Malle. 2018. What is Human-like? Decomposing Robots’ Human-like Appearance Using the Anthropomorphic RoBOT (ABOT) Database. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (Chicago, IL, USA) (HRI ’18). Association for Computing Machinery, New York, NY, USA, 105–113. https://doi.org/10.1145/3171221.3171268

Digital Library

Google Scholar

[12]

Giorgio Roffo, Cinzia Giorgetta, Roberta Ferrario, and Marco Cristani. 2014. Just the way you chat: Linking personality, style and recognizability in chats. In International Workshop on Human Behavior Understanding. Springer, 30–41.

Crossref

Google Scholar

[13]

Giorgio Roffo, Cinzia Giorgetta, Roberta Ferrario, Walter Riviera, and Marco Cristani. 2014. Statistical analysis of personality and identity in chats using a keylogging platform. In Proceedings of the 16th International Conference on Multimodal Interaction. 224–231.

Digital Library

Google Scholar

[14]

Tuva Lunde Smestad and Frode Volden. 2018. Chatbot Personalities Matters. In International Conference on Internet Science. Springer, 170–181.

Google Scholar

Cited By

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Ha JJeon HHan DSeo JOh C(2024)CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language ModelsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642472(1-24)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642472
Félix BRibeiro J(2022)Understanding People’s Expectations When Designing a Chatbot for Cancer PatientsChatbot Research and Design10.1007/978-3-030-94890-0_3(39-54)Online publication date: 1-Jan-2022
https://doi.org/10.1007/978-3-030-94890-0_3

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Abstract
This work explores the effect of chatbot personality on user experience and investigates how users perceive agent personality when conveyed through text. Building on previous work in the field of human-computer interaction on designing chatbot ...

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MobileHCI '20: 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services

October 2020

248 pages

ISBN:9781450380522

DOI:10.1145/3406324

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 25 February 2021

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MobileHCI '20

MobileHCI '20: 22nd International Conference on Human-Computer Interaction with Mobile Devices and Services

October 5 - 8, 2020

Oldenburg, Germany

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Ha JJeon HHan DSeo JOh C(2024)CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language ModelsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642472(1-24)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642472
Félix BRibeiro J(2022)Understanding People’s Expectations When Designing a Chatbot for Cancer PatientsChatbot Research and Design10.1007/978-3-030-94890-0_3(39-54)Online publication date: 1-Jan-2022
https://doi.org/10.1007/978-3-030-94890-0_3

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Statistical Analysis of Personality and Identity in Chats Using a Keylogging Platform

Conversationally-inspired stylometric features for authorship attribution in instant messaging

User Perception of Text-Based Chatbot Personality

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