Kun Xu, Ph.D.
Media Effects and Technology Lab (METL) and UFCJC Research Lab Director -
Associate Professor in Emerging Technologies - Department of Media Production, Management, and Technology
Office: 3065 Weimer
Phone: 352-392-0435
Email: kun.xu@ufl.edu
Kun Xu, Ph.D.
Media Effects and Technology Lab (METL) and UFCJC Research Lab Director -
Associate Professor in Emerging Technologies - Department of Media Production, Management, and Technology
Kun Xu’s research areas broadly focus on human-computer interaction, human-robot interaction, computer-mediated communication, and psychological processing of emerging technologies. His work investigates how individuals perceive, interact with, and respond to a range of AI-based technologies, such as social robots and virtual agents. He also examines how people use virtual and augmented reality (VR/AR) technologies to make sense of spaces and maintain social relationships. Using a variety of methodological approaches, including lab experiments, psychophysiology measures, computational methods, and visual analyses, his research seeks to understand the role of (tele)presence in people’s technology use experience and the mutual shaping between humans and machines.
His lead-authored works have been published in journals such as Communication Theory, Journal of Computer-Mediated Communication, New Media & Society, Human-Machine Communication, International Journal of Communication, Journal of Broadcasting & Electronic Media, International Journal of Social Robotics, International Communication Gazette, Telematics & Informatics and Computers in Human Behavior.
Kun was a cameraman and a news editor at Thomson Reuters and Shanghai Media Group. More information is available at https://xkunnet.github.io/
Areas of Expertise
Artificial Intelligence (AI), Communication Technology, Emerging Media (gaming, VR, etc.), Human-Machine Communication, Media Psychology and Media Effects
Education
Ph.D., Temple University
News
- Kun Xu Named New Director of UFCJC Media Effects and Technology Lab and Research Lab (November 18, 2024)
- Four UFCJC Faculty Included in 2024 Stanford Top 2% Scientists List (October 7, 2024)
- Decoding the Digital Dialogue: A Two-Step Framework for Human-AI Interaction (September 18, 2024)
- Study: Human-Machine Communication and Explainable Artificial Intelligence Can Help Influence Humans’ AI Perceptions and Attitudes (August 27, 2024)
- Study: Facial Recognition Technology in Human-Robot Interaction Enhances Users’ Robot Acceptance (June 20, 2024)
- All News About Kun Xu →
Publications
Refereed Journal Articles
Xu, K., & Shi, J. (2024). Visioning a two-level human-machine communication framework: Initiating conversations between explainable AI and communication. Communication Theory. DOI: 10.1093/ct/qtae016
Xu, K., Chen, X., Liu, F., & Huang , L. (2024). What did you hear and what did you see? Understanding the transparency of facial recognition and speech recognition systems during human-robot interaction. New Media & Society. DOI: 10.1177/14614448241256899
Kim , J., Merrill , K., Jin, X., Collins , C., & Xu, K. (2023). Trust, perceived usefulness, and intentions to adopt robotic health advisors for physical and relational health issues. The Social Science Journal. DOI: 10.1080/03623319.2023.2289241
Kim, J., Merrill , K., Xu, K., & Collins, C. (2023). My health advisor is a robot: Understanding intentions to adopt a robotic health advisor. International Journal of Human-Computer Interaction. DOI: 10.1080/10447318.2023.2239559
Liu , W., Xu, K., & Yao, M. (2023). Can you tell me about yourself? The impacts of chatbot names and communication contexts on users’ willingness to self-disclose information in human-machine conversations. Communication Research Reports, 40, 122-133. Retrieved from https://www.tandfonline.com/doi/abs/10.1080/08824096.2023.2212899#:~:text=The%20results%20showed%20that%20a,chatbot%20names%20was%20not%20significant.
Xu, K. (2023). A mini imitation game: How individuals model social robots via behavioral outcomes and social roles. Telematics & Informatics, 78. DOI: 10.1016/j.tele.2023.101950
Xu, K., Chen , M., & You , L. (2023). The Hitchhiker’s Guide to a Credible and Socially Present Robot: Two Meta-Analyses of the Power of Social Cues in Human–Robot Interaction. International Journal of Social Robotics. DOI: 10.1007/s12369-022-00961-3
Kim , J., Merrill , K., Xu, K., & Kelly , S. (2022). Perceived credibility of an AI instructor in online education: The role of social presence and voice features. Computers in Human Behavior, 136. DOI: 10.1016/j.chb.2022.107383
Xu, K., Chen, X., & Huang, L. (2022). Deep mind in social responses to technologies: A new approach to explaining the Computers are Social Actors phenomena. Computers in Human Behavior, 134, 107321. DOI: 10.1016/j.chb.2022.107321
Kim , J., Merrill , K., Xu, K., & Sellnow , D. (2022). Embracing AI-based machine teacher in higher-education: Examining social presence in online education. Human-Machine Communication.
Kim , J., Xu, K., & Merrill , K. (2022). Man vs machine: Human responses to an AI newscaster and the role of social presence. The Social Science Journal. DOI: 10.1080/03623319.2022.2027163
Xu, K., Chan-Olmsted, S., & Liu, F. (2022). Smart speakers require smart management: Two routes from user gratifications to privacy settings. International Journal of Communication, 16. Retrieved from https://ijoc.org/index.php/ijoc/article/view/17823
Kim, J., Kelly , M., Xu, K., & Sellnow , D. (2021). I like my relational machine teacher: An AI instructor’s communication styles and social presence in online education. International Journal of Human-Computer Interaction. DOI: 10.1080/10447318.2021.1908671
Lombard, M., & Xu, K. (2021). Social responses to media technologies in the 21st century: The Media are Social Actors paradigm. Human-Machine Communication, 2, 29-55. Retrieved from https://stars.library.ucf.edu/cgi/viewcontent.cgi?article=1030&context=hmc
Xu, K. (2020). Language, modality, and mobile media use experiences: Social responses to smartphones in a task-oriented context. Telematics & Informatics, 48. DOI: 10.1016/j.tele.2020.101344
Kim, J., Merrill, K., Xu, K., & Sellnow, D. (2020). My teacher is a machine: Understanding students’ perception of AI teaching assistants in online education. International Journal of Human-Computer Interaction, 36, 1902-1911. DOI: 10.1080/10447318.2020.1801227
Xu, K., Liu , F., Mou, Y., Wu, Y., Zeng, J., & Schafer , M. (2020). Using machine learning to learn machines: A cross-cultural study of users’ responses to machine-generated art works. Journal of Broadcasting and Electronic Media. DOI: 10.1080/08838151.2020.1835136
Liao, T., & Xu, K. (2020). A process approach to understanding multiple open source innovation contests: Assessing the contest structures, execution, and participant responses in the Android Developer Challenges. Information and Organization, 30(2). Retrieved from https://www.sciencedirect.com/science/article/abs/pii/S1471772720300245
Wu, Y., Mou, Y., Li, Z., & Xu, K. (2020). Investigating American and Chinese Subjects’ explicit and implicit perceptions of AI-Generated artistic work. Computers in Human Behavior, 104. Retrieved from https://www.sciencedirect.com/science/article/pii/S074756321930398X
Liao, T., Yang, H., Lee, S., Xu, K., & Bennett , S. (2020). Augmented criminality: How people process in-situ augmented reality crime information in relation to space/place. Mobile Media and Communication. DOI: 10.1177/2050157919899696
Steiner, E., & Xu, K. (2020). Binge-watching motivates change: Uses and gratifications of streaming video viewers challenge traditional TV research. Convergence: The International Journal of Research into New Media Technologies, 26(1), 82-101. Retrieved from https://journals.sagepub.com/doi/abs/10.1177/1354856517750365
Xu, K., & Liao, T. (2020). Explicating cues: A typology for understanding emerging media technologies. Journal of Computer-Mediated Communication, 25(1), 32-43. DOI: 10.1093/jcmc/zmz023
Xu, K. (2019). First encounter with robot Alpha: How individual differences interact with vocal and kinetic cues in users’ social responses. New Media & Society, 21(11-12), 2522-2547. Retrieved from https://journals.sagepub.com/doi/abs/10.1177/1461444819851479
Mou, Y., Shi, C., Shen, T., & Xu, K. (2019). A Systematic Review of the Personality of Robot: Mapping Its Conceptualization, Operationalization, Contextualization and Effects. International Journal of Human--Computer Interaction, 36, 591-605. Retrieved from https://www.tandfonline.com/doi/abs/10.1080/10447318.2019.1663008
Xu, K. (2018). Location Speaks: Using GIS Approach to Understand an Anti-pornography Campaign in Mainland China. China Media Research, 14(2), 29-44.
Mou, Y., Xu, K., & Xia, K. (2018). Unpacking the black box: Examining the (de) Gender categorization effect in human-machine communication. Computers in Human Behavior, 90, 380-387. Retrieved from https://www.sciencedirect.com/science/article/pii/S0747563218304242
Xu, K. (2018). Painting Chinese mythology: Varying touches on the magazine covers of Time, The Economist, Der Spiegel, and China Today. International Communication Gazette, 80(2), 135-157. Retrieved from https://journals.sagepub.com/doi/abs/10.1177/1748048517707386
Xu, K., & Lombard, M. (2017). Persuasive computing: Feeling peer pressure from multiple computer agents. Computers in Human Behavior, 74, 152-162. Retrieved from https://www.sciencedirect.com/science/article/pii/S0747563217302856
Mou, Y., & Xu, K. (2017). The media inequality: Comparing the initial human-human and human-AI social interactions. Computers in Human Behavior, 72, 432-440. Retrieved from https://www.sciencedirect.com/science/article/pii/S0747563217301486
Xu, K., Lin, M., & Haridakis, P. (2015). Being Addicted to Chinese Twitter: Exploring the Roles of Users' Expected Outcomes and Deficient Self-regulation in Social Network Service Addiction. China Media Research, 11(2).
Research
Specialization
Human-robot interaction, human-computer interaction, virtual/augmented reality, media psychology, lab experiments, statistical modeling, computational methods
Courses
Syllabi from the current and three previous semesters:
-
MMC 6936 - Human-Machine Communication - Fall 2024 (PDF)
-
RTV 4930 - Technology User Experience - section 24129 - Fall 2024 (PDF)
-
MMC 6936 - Computer-Mediated Communication - Spring 2024 (PDF)
-
RTV 4930 - Media User Experience - section 27141 - Spring 2024 (PDF)
-
MMC 6936 - Human-Machine Communication - Fall 2023 (PDF)
-
RTV 4930 - Media User Experience - section 25757 - Fall 2023 (PDF)
Specialization
Human-robot interaction, human-computer interaction, virtual/augmented reality, media psychology, lab experiments, statistical modeling, computational methods
Courses
Syllabi from the current and three previous semesters:
- MMC 6936 - Human-Machine Communication - Fall 2024 (PDF)
- RTV 4930 - Technology User Experience - section 24129 - Fall 2024 (PDF)
- MMC 6936 - Computer-Mediated Communication - Spring 2024 (PDF)
- RTV 4930 - Media User Experience - section 27141 - Spring 2024 (PDF)
- MMC 6936 - Human-Machine Communication - Fall 2023 (PDF)
- RTV 4930 - Media User Experience - section 25757 - Fall 2023 (PDF)