Article published in:
What Influences Influence? How the Communicative Situation Influences Persuasion
Edited by Kerstin Fischer and Jaap Ham
[Interaction Studies 22:3] 2021
► pp. 488515
References
Ahmad, M. I., Mubin, O., & Orlando, J.
(2017) Adaptive Social Robot for Sustaining Social Engagement during Long-Term Children–Robot Interaction. International Journal of Human–Computer Interaction, 33 (12), 943–962. CrossrefGoogle Scholar
Bainbridge, W. A., Hart, J. W., Kim, E. S., & Scassellati, B.
(2010) The Benefits of Interactions with Physically Present Robots over Video-Displayed Agents. International Journal of Social Robotics, 3(1), 41–52. CrossrefGoogle Scholar
Bangerter, A., & Mayor, E.
(2013) 14 Interactional theories of communication. In Theories and models of communication. Handbook of Communication Science, 257–272. De Gruyter Mouton. CrossrefGoogle Scholar
Baxter, P., Kennedy, J., Vollmer, A. L., de Greeff, J., & Belpaeme, T.
(2014) Tracking gaze over time in HRI as a proxy for engagement and attribution of social agency. In Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction. ACM, New York, NY, USA, 126–127. CrossrefGoogle Scholar
Breazeal, C., Kidd, C. D., Thomaz, A. L., Hoffman, G., & Berlin, M.
(2005) Effects of nonverbal communication on efficiency and robustness in human-robot teamwork. In 2005 IEEE/RSJ international conference on intelligent robots and systems, 708–713. IEEE, Edmonton, Alta., Canada. CrossrefGoogle Scholar
Campos, J., & Paiva, A.
(2010) May: My memories are yours. In International Conference on Intelligent Virtual Agents, 406–412. Springer, Berlin, Heidelberg. CrossrefGoogle Scholar
Carlmeyer, B., Schlangen, D., & Wrede, B.
(2014) Towards closed feedback loops in hri: Integrating inprotk and pamini. In Proceedings of the 2014 Workshop on Multimodal, Multi-Party, Real-World Human-Robot Interaction, 1–6. CrossrefGoogle Scholar
Chidambaram, V., Chiang, Y. H., & Mutlu, B.
(2012) Designing persuasive robots: how robots might persuade people using vocal and nonverbal cues. In Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction, 293–300. ACM, Boston, Massachusetts, USA. CrossrefGoogle Scholar
Christian, B.
(2011) The most human human: What talking with computers teaches us about what it means to be alive. Doubleday, New York, USA.Google Scholar
Chromik, M., Carlmeyer, B., & Wrede, B.
(2017) Ready for the Next Step? Investigating the Effect of Incremental Information Presentation in an Object Fetching Task. In Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 95–96. ACM. CrossrefGoogle Scholar
Cialdini, R. B.
([1987] 2010) Influence (Vol. 31). Port Harcourt: A. Michel.Google Scholar
Clark, H. H.
(1996) Using Language. Cambridge University Press, Cambridge, USA. CrossrefGoogle Scholar
(1998) Communal lexicons. In K. Malmkjaer and J. Williams (Eds.), Context in Language Learning and Language Understanding, pp. 63–87. Cambridge: Cambridge University Press.Google Scholar
Cohen, J.
(1969) Statistical Power Analysis for the Behavioural Sciences. Academic.Google Scholar
Dautenhahn, K., Ogden, B., & Quick, T.
(2002) From embodied to socially embedded agents – Implications for interaction-aware robots. Cognitive Systems Research, 3 (3), 397–428. CrossrefGoogle Scholar
Fetzer, A.
(2004) Recontextualizing Context: Grammaticality meets appropriateness. John Benjamins Publishing Company. CrossrefGoogle Scholar
Fischer, K., & Saunders, J.
(2012) Getting acquainted with a developing robot. In International Workshop on Human Behavior Understanding, 125–133. Springer, Berlin, Heidelberg. CrossrefGoogle Scholar
Fischer, K., Lohan, K., & Foth, K.
(2012) Levels of embodiment: Linguistic analyses of factors influencing HRI. In 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 463–470. ACM, Boston, MA., USA. CrossrefGoogle Scholar
Fischer, K., Jensen, L. C., Suvei, S. D., & Bodenhagen, L.
(2016) Between legibility and contact: The role of gaze in robot approach. In 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 646–651. IEEE, New York City, USA. CrossrefGoogle Scholar
Fischer, Kerstin
(2016a) Robots as confederates: How robots can and should support research in the humanities. In Proceedings of the Robophilosophy 2016 Conference, Aarhus, Denmark 2016.Google Scholar
Fischer, K.
(2016b) Designing Speech for a Recipient: The roles of partner modeling, alignment and feedback in so-called simplified registers. John Benjamins Publishing Company. Pragmatics and Beyond New Series, Vol. 270. CrossrefGoogle Scholar
Fischer, K., Lohan, K. S., Nehaniv, C., & Lehmann, H.
(2013a) Effects of different kinds of robot feedback. In International Conference on Social Robotics, 260–269. Springer, Berlin Heidelberg, Germany. CrossrefGoogle Scholar
Fischer, K., Lohan, K., Saunders, J., Nehaniv, C., Wrede, B., & Rohlfing, K.
(2013b) The impact of the contingency of robot feedback on HRI. In 2013 International Conference on Collaboration Technologies and Systems (CTS), 210–217. IEEE, San Diego, CA, USA. CrossrefGoogle Scholar
Fischer, Kerstin & Niebuhr, Oliver
(2020) Studying Language Attitudes Using Robots. HRI’20 Companion, March 23–26 2020, Cambridge, United Kingdom. CrossrefGoogle Scholar
Fischer, Kerstin, Naik, Lakshadeep, Langedijk, Rosalyn, Baumann, Timo, Jelinek, Matous & Palinko, Oskar
(2021) Initiating Human-Robot Interactions Using Incremental Speech Adaptation. HRI’21 Companion, Boulder, Colorado. CrossrefGoogle Scholar
Ghigi, F., Eskenazi, M., Torres, M. I., & Lee, S.
(2014) Incremental dialog processing in a task-oriented dialog. In Fifteenth Annual Conference of the International Speech Communication Association. CrossrefGoogle Scholar
Goldstein, N. J., Cialdini, R. B., & Griskevicius, V.
(2008) A room with a viewpoint: Using social norms to motivate environmental conservation in hotels. Journal of consumer Research, 35 (3), 472–482. CrossrefGoogle Scholar
Gumperz, J. J.
(1992) Contextualization and understanding. Rethinking context: Language as an interactive phenomenon, 11 1, 229–252.Google Scholar
Ham, Jaap
(2022) Influencing robot influence: Personalization of persuasive robots. Interaction Studies (in this special issue).Google Scholar
Ham, J., Cuijpers, R. H., & Cabibihan, J. J.
(2015) Combining robotic persuasive strategies: the persuasive power of a storytelling robot that uses gazing and gestures. International Journal of Social Robotics, 7(4), 479–487. CrossrefGoogle Scholar
Higgins, C., & Walker, R.
(2012) Ethos, logos, pathos: Strategies of persuasion in social/environmental reports. In Accounting Forum, (36)31, 194–208. No longer published by Elsevier. CrossrefGoogle Scholar
Ishii, R., Nakano, Y. I., & Nishida, T.
(2013) Gaze awareness in conversational agents: Estimating a user’s conversational engagement from eye gaze. ACM Transactions on Interactive Intelligent Systems (TiiS), 3 (2), 1–25. CrossrefGoogle Scholar
Jefferson, Gail
(1984) Transcription conventions. Structures of social action, ix–xvi.Google Scholar
Johnson, D. O., & Agah, A.
(2009) Human robot interaction through semantic integration of multiple modalities, dialog management, and contexts. International Journal of Social Robotics, 1 (4), 283–305. CrossrefGoogle Scholar
Kanda, T., Shiomi, M., Miyashita, Z., Ishiguro, H., & Hagita, N.
(2010) A communication robot in a shopping mall. IEEE Transactions on Robotics, 26 (5), 897–913. CrossrefGoogle Scholar
Kasap, Z., & Magnenat-Thalmann, N.
(2012) Building long-term relationships with virtual and robotic characters: the role of remembering. The Visual Computer, 28 (1), 87–97. CrossrefGoogle Scholar
Kennington, C., Kousidis, S., Baumann, T., Buschmeier, H., Kopp, S., & Schlangen, D.
(2014) Better driving and recall when in-car information presentation uses situationally-aware incremental speech output generation. In Proceedings of the 6th international conference on automotive user interfaces and interactive vehicular applications, 1–7. ACM. CrossrefGoogle Scholar
Kidd, C. D., & Breazeal, C.
(2008) Robots at home: Understanding long-term human-robot interaction. In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, 3230–3235. IEEE, Nice, France. CrossrefGoogle Scholar
Kiesler, S.
(2005) Fostering common ground in human-robot interaction. In ROMAN 2005. IEEE International Workshop on Robot and Human Interactive Communication, 729–734. IEEE Press, Piscataway, NJ, USA. CrossrefGoogle Scholar
Kim, T., & Hinds, P.
(2006) Who should I blame? Effects of autonomy and transparency on attributions in human-robot interaction. In ROMAN 2006 – The 15th IEEE International Symposium on Robot and Human Interactive Communication, 80–85. IEEE. CrossrefGoogle Scholar
Kipp, A., & Kummert, F.
(2016) “I know how you performed!”: Fostering Engagement in a Gaming Situation Using Memory of Past Interaction. In Proceedings of the Fourth International Conference on Human Agent Interaction, 281–288. ACM, Biopolis, Singapore. CrossrefGoogle Scholar
Klamer, T., Allouch, S. B., & Heylen, D.
(2010) “Adventures of Harvey”–Use, acceptance of and relationship building with a social robot in a domestic environment. In International Conference on Human-Robot Personal Relationship, 74–82. Springer, Berlin, Heidelberg, Germany. CrossrefGoogle Scholar
Langedijk, R., & Ham, J.
(2022) More than advice: The influence of adding references to prior discourse and signals of empathy on the persuasiveness of an advice-giving robot. Interaction Studies (in this special issue).Google Scholar
Lee, S., Lau, I. Y., Kiesler, S., & Chiu, C.
(2005) Human mental model of humanoid robot. In IEEE International Conference on Robotics and Automation . Crossref
Leite, I., Pereira, A., & Lehman, J. F.
(2017) Persistent memory in repeated child-robot conversations. In Proceedings of the 2017 conference on interaction design and children, 238–247. ACM, New York, NY, USA. CrossrefGoogle Scholar
Leite, I., Castellano, G., Pereira, A., Martinho, C., & Paiva, A.
(2014) Empathic robots for long-term interaction. International Journal of Social Robotics, 6 (3), 329–341. CrossrefGoogle Scholar
Lemaignan, S., Garcia, F., Jacq, A., & Dillenbourg, P.
(2016) From real-time attention assessment to “with-me-ness” in human-robot interaction. In 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 157–164. IEEE. CrossrefGoogle Scholar
Leyzberg, D., Spaulding, S., & Scassellati, B.
(2014) Personalizing robot tutors to individuals’ learning differences. In 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 423–430. ACM, New York, NY, USA. CrossrefGoogle Scholar
Lockridge, C. B., & Brennan, S. E.
(2002) Addressees’ needs influence speakers’ early syntactic choices. Psychonomic bulletin & review, 9(3), 550–557. CrossrefGoogle Scholar
Lohan, K. S., Pitsch, K., Rohlfing, K. J., Fischer, K., Saunders, J., Lehmann, H., Nehaniv, C. L., & Wrede, B.
(2011) Contingency allows the robot to spot the tutor and to learn from interaction. In 2011 IEEE International Conference on Development and Learning (ICDL) (2), 1–8. IEEE, Frankfurt and Main, Germany. CrossrefGoogle Scholar
Lohan, K. S., Rohlfing, K. J., Pitsch, K., Saunders, J., Lehmann, H., Nehaniv, C. L., Fischer, K., & Wrede, B.
(2012) Tutor spotter: Proposing a feature set and evaluating it in a robotic system. International Journal of Social Robotics, 4 (2), 131–146. CrossrefGoogle Scholar
Lyons, J. B.
(2013) Being transparent about transparency: A model for human-robot interaction. In 2013 AAAI Spring Symposium Series. (pp. 48–53). Stanford, CA, USA.Google Scholar
Manuvinakurike, R., Paetzel, M., Qu, C., Schlangen, D., & DeVault, D.
(2016) Toward incremental dialogue act segmentation in fast-paced interactive dialogue systems. In Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue, 252–262. CrossrefGoogle Scholar
Nass, C.
(2004) Etiquette equality: exhibitions and expectations of computer politeness. Communications of the ACM, 47(4), 35–37. CrossrefGoogle Scholar
Riek, L. D., Paul, P. C., & Robinson, P.
(2010) When my robot smiles at me: Enabling human-robot rapport via real-time head gesture mimicry. Journal on Multimodal User Interfaces, 3 (1), 99–108. CrossrefGoogle Scholar
Rossi, S., Staffa, M., Giordano, M., De Gregorio, M., Rossi, A., Tamburro, A., & Vellucci, C.
(2015) Robot head movements and human effort in the evaluation of tracking performance. In 2015 24th IEEE international symposium on robot and human interactive communication (RO-MAN), 791–796. IEEE, Kobe, Japan. CrossrefGoogle Scholar
Ruijten, P. A., Haans, A., Ham, J., & Midden, C. J.
(2019) Perceived human-likeness of social robots: testing the Rasch model as a method for measuring anthropomorphism. International Journal of Social Robotics, 11(3), 477–494. CrossrefGoogle Scholar
Sacks, H., Schegloff, E. A., & Jefferson, G.
(1974) A Simplest Systematics for the Organization of Turn-Taking for. Language, 50(4 Part 1), 696–735.Google Scholar
Sadouohi, N., Pereira, A., Jain, R., Leite, L., & Lehman, J. F.
(2017) Creating prosodic synchrony for a robot co-player in a speech-controlled game for children. In 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 91–99). IEEE. CrossrefGoogle Scholar
Schegloff, E. A.
(1997) Whose text, whose context? Discourse & Society 8(2), 165–187. CrossrefGoogle Scholar
Schober, M. F., & Brennan, S. E.
(2003) Processes of interactive spoken discourse: The role of the partner. In Handbook of discourse processes (pp. 128–169). Routledge.Google Scholar
Sirkin, D., Fischer, K., Jensen, L., & Ju, W.
(2015) How Effective an Odd Message Can Be: Appropriate and Inappropriate Topics in Speech-Based Vehicle Interfaces. In AAAI Conference on Human Computation and Crowdsourcing, 36–37. San Diego, CA, USA.Google Scholar
(2016) Eliciting conversation in robot vehicle interactions. In Proceedings of the Association for the Advancement of Artificial Intelligence Spring Symposium Series: Enabling Computing Research in Socially Intelligent Human Robot Interaction, 164–171. AAAI, Stanford, CA, USA.Google Scholar
Skantze, G., & Hjalmarsson, A.
(2010) Towards incremental speech generation in dialogue systems. In Proceedings of the the 11th annual meeting of the special interest group on discourse and dialogue (SIGDIAL) 2010 Conference, 1–8.Google Scholar
(2013) Towards incremental speech generation in conversational systems. Computer Speech & Language, 27 (1), 243–262. CrossrefGoogle Scholar
Skantze, G., Hjalmarsson, A., & Oertel, C.
(2014) Turn-taking, feedback and joint attention in situated human–robot interaction. Speech Communication, 65 1, 50–66. CrossrefGoogle Scholar
Smedegaard, C. V.
(2019) Reframing the role of novelty within social HRI: from noise to information. In 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 411–420. IEEE. CrossrefGoogle Scholar
Stanton, C., & Stevens, C. J.
(2014) Robot pressure: the impact of robot eye gaze and lifelike bodily movements upon decision-making and trust. In International conference on social robotics, 330–339. Springer, Sydney, Australia. CrossrefGoogle Scholar
Staudte, M., & Crocker, M. W.
(2011) Investigating joint attention mechanisms through spoken human–robot interaction. Cognition, 120 (2), 268–291. CrossrefGoogle Scholar
Wainer, J., Feil-Seifer, D. J., Shell, D. A., & Mataric, M. J.
(2006) The role of physical embodiment in human-robot interaction. In ROMAN 2006 – The 15th IEEE International Symposium on Robot and Human Interactive Communication, 117–122. IEEE, Hatfield, UK. CrossrefGoogle Scholar
Wang, E., Lignos, C., Vatsal, A., & Scassellati, B.
(2006) Effects of head movement on perceptions of humanoid robot behavior. In Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-robot Interaction, 180–185. ACM, Salt Lake City, Utah, USA. CrossrefGoogle Scholar
Zhang, J., Zheng, J., & Thalmann, N. M.
(2018) MCAEM: mixed-correlation analysis-based episodic memory for companion–user interactions. The Visual Computer, 34 (6), 1129–1141. CrossrefGoogle Scholar
Zheng, M., Moon, A., Croft, E. A., & Meng, M. Q. H.
(2015) Impacts of robot head gaze on robot-to-human handovers. International Journal of Social Robotics, 7 (5), 783–798. CrossrefGoogle Scholar