A Taxonomy of Social Cues for Conversational Agents

When using the taxonomy, please cite as Feine, J., Gnewuch U., Morana S. and Maedche A. (2019): “A Taxonomy of Social Cues for Conversational Agents” International Journal of Human-Computer Studies. To read the paper, please click here.

Social cue: Gender
Communication system: Visual
Cue category: Appearance
Cue Description
The CA belongs to either one of the two sexes (male, female) or it is ambiguous.
Cue example
Male, female, ambiguous CA appearance.
Cue impact
Gender of agent visualization leads to attribution of various gender stereotypes towards the agent (Forlizzi et al. 2007; Nunamaker et al. 2001; Louwerse et al. 2005; Niculescu et al. 2010; Brahnam, Angeli 2012; Beldad et al. 2016; Hayashi 2016; Kraemer et al. 2016). Female agents are more effective in reducing user frustration because they are more associated with empathy (Hone 2006). Gender ambiguous agents are not preferred by the user (Niculescu et al. 2010). Other did not find an impact of the agent gender (Li et al. 2017). Moreover, user do have a preference of a certain gender of the agent (Cowell, Stanney 2005).
Reference List
1. Beldad, A., Hegner, S., & Hoppen, J. (2016). The effect of virtual sales agent (VSA) gender - product gender congruence on product advice credibility, trust in VSA and online vendor, and purchase intention. Computers in Human Behavior (60, pp. 62-72.
2. Brahnam, S., & Angeli, A. de (2012). Gender affordances of conversational agents. INTERACTING WITH COMPUTERS (24:3), pp. 139-153.
3. Forlizzi, J., Zimmerman, J., Mancuso, V., & Kwak, S. (2007). How Interface Agents Affect Interaction Between Humans and Computers. In : DPPI ’07, Proceedings of the 2007 Conference on Designing Pleasurable Products and Interfaces (pp. 209-221). New York, NY, USA: ACM.
4. Cowell, A. J., & Stanney, K. M. (2005). Manipulation of non-verbal interaction style and demographic embodiment to increase anthropomorphic computer character credibility. INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES (62:2), pp. 281-306.
5. Hayashi, Y. (2016). Lexical Network Analysis on an Online Explanation Task: Effects of Affect and Embodiment of a Pedagogical Agent. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS (E99D:6), pp. 1455-1461.
6. Hone, K. (2006). Empathic agents to reduce user frustration: The effects of varying agent characteristics. INTERACTING WITH COMPUTERS (18:2), pp. 227-245.
7. Kraemer, N. C., Karacora, B., Lucas, G., Dehghani, M., Ruether, G., & Gratch, J. (2016). Closing the gender gap in STEM with friendly male instructors? On the effects of rapport behavior and gender of a virtual agent in an instructional interaction. COMPUTERS & EDUCATION (99, pp. 1-13.
8. Li, J., Zhou, M. X., Yang, H., & Mark, G. (2017). Confiding in and Listening to Virtual Agents. In G. A. Papadopoulos, T. Kuflik, F. Chen, C. Duarte, & W.-T. Fu (Eds.), Proceedings of the 22nd International Conference on Intelligent User Interfaces - IUI 17 (pp. 275-286). New York, New York, USA: ACM Press.
9. Louwerse, M. M., Graesser, A. C., Lu, S. L., & Mitchell, H. H. (2005). Social cues in animated conversational agents. APPLIED COGNITIVE PSYCHOLOGY (19:6), pp. 693-704.
10. Niculescu, A., Hofs, D., van Dijk, B., & Nijholt, A. (Eds.). 2010. How the agent s gender influence users evaluation of a QA system. 2010 International Conference on User Science and Engineering (i-USEr).
11. Nunamaker, J. J. E., Derrick, D. C., Elkins, A. C., Burgoon, J. K., & Patton, M. W. (2011). Embodied Conversational Agent-Based Kiosk for Automated Interviewing. JOURNAL OF MANAGEMENT INFORMATION SYSTEMS (28:1), pp. 17-48.
12. Ryokai, K., C. Vaucelle and J. Cassell (2003). Virtual peers as partners in storytelling and literacy learning Journal of Computer Assisted Learning 19 (2), 195?208.
13. Bailenson, J. N. and N. Yee (2005). Digital chameleons. Automatic assimilation of nonverbal gestures in immersive virtual environments Psychological science 16 (10), 814?819.