Seeing (Movement) is Believing: The Effect of Motion on Perception of Automatic Systems Performance

References

• Ariely, D. (2009). Predictably irrational (p. 71). New York: HarperCollins.
   Google Scholar
• Bakhshi, S., Shamma, D. A., Kennedy, L., Song, Y., De Juan, P., & Kaye, J. J. (2016). Fast, cheap, and good: Why animated gifs engage us. Proceedings of the 2016 chi conference on human factors in computing systems (pp. 575–586). New York, NY, USA. ACM.
   Google Scholar
• Bellotti, V., & Edwards, K. (2001, December). Intelligibility and accountability: Human considerations in context-aware systems. Human–Computer Interaction, 16(2), 193–212. doi:10.1207/S15327051HCI16234_05
   Web of Science ®Google Scholar
• Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. doi:10.1191/1478088706qp063oa
   Google Scholar
• Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s mechanical turk. Perspectives on Psychological Science, 6(1), 3–5. doi:10.1177/1745691610393980
   Web of Science ®Google Scholar
• Camp Wilson, T., & Nisbett, R. E. (1978). The accuracy of verbal reports about the effects of stimuli on evaluations and behavior. Social Psychology, 41(2), 118–131. doi:10.2307/3033572
   Web of Science ®Google Scholar
• Card, S. K., Mackinlay, J. D., & Shneiderman, B. (1999). Readings in information visualization: Using vision to think. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.
   Google Scholar
• Chang, B.-W., & Ungar, D. (1993). Animation: From cartoons to the user interface. Proceedings of the 6th annual acm symposium on user interface software and technology (pp. 45–55). New York, NY, USA. ACM.
   Google Scholar
• Chuang, J., Manning, C. D., & Heer, J. (2012, October). Without the clutter of unimportant words: Descriptive keyphrases for text visualization. ACM transactions on Computer-Human Interaction, 19(3), 19:1–19:29. doi:10.1145/2362364
   PubMed Web of Science ®Google Scholar
• Detenber, B. H., & Reeves, B. (1996). A bio-informational theory of emotion: Motion and image size effects on viewers. Journal of Communication, 46(3), 66–84. doi:10.1111/j.1460-2466.1996.tb01489.x
   Web of Science ®Google Scholar
• Difallah, D. E., Catasta, M., Demartini, G., Ipeirotis, P. G., & Cudŕe-Mauroux, P. (2015). The dynamics of micro-task crowdsourcing: The case of amazon mturk. Proceedings of the 24th international conference on world wide web (pp. 238–247). Republic and Canton of Geneva, Switzerland. International World Wide Web Conferences Steering Committee.
   Google Scholar
• Dittrich, W. H., & Lea, S. E. G. (1994). Visual perception of intentional motion. Perception, 23(3), 253–268. doi:10.1068/p230253
   PubMed Web of Science ®Google Scholar
• Dragicevic, P., Bezerianos, A., Javed, W., Elmqvist, N., & Fekete, J.-D. (2011). Temporal distortion for animated transitions. Proceedings of the sigchi conference on human factors in computing systems (pp. 2009–2018). New York, NY, USA. ACM.
   Google Scholar
• Fritz Heider, M. S. (1944). The American journal of psychology. An Experimental Study of Apparent Behavior, 57(2), 243–259. Retrieved from http://www.jstor.org/stable/1416950
   Google Scholar
• Gao, T., McCarthy, G., & Scholl, B. J. (2010). The wolfpack effect: Perception of animacy irresistibly influences interactive behavior. Psychological Science, 21(12), 1845–1853. doi:10.1177/0956797610388814
   PubMed Web of Science ®Google Scholar
• Gao, T., & Scholl, B. J. (2011). Chasing vs. stalking: Interrupting the perception of animacy. Journal of Experimental Psychology: Human Perception and Performance, 37(3), 669.
   PubMed Web of Science ®Google Scholar
• Garcia, P. G., Costanza, E., Ramchurn, S. D., & Verame, J. K. M. (2016). The potential of physical motion cues: Changing people’s perception of robots’ performance. Proceedings of the 2016 acm international joint conference on pervasive and ubiquitous computing (pp. 510–518). New York, NY, USA. ACM.
   Google Scholar
• Gelman, R., Durgin, F., & Kaufman, L. (1995). Distinguishing between animates and inanimates: Not by motion alone. Causal Cognition: A Multidisciplinary Debate, 3, 150–184.
   Google Scholar
• Germine, L., Nakayama, K., Duchaine, B., Chabris, C., Chatterjee, G., & Wilmer, J. (2012). Is the web as good as the lab? comparable performance from web and lab in cogni- tive/perceptual experiments. Psychonomic Bulletin & Review, 19(5), 847–857. doi:10.3758/s13423-012-0296-9
   PubMed Web of Science ®Google Scholar
• Harrison, C., Amento, B., Kuznetsov, S., & Bell, R. (2007). Rethinking the progress bar. Proceedings of the 20th annual acm symposium on user interface software and technology (pp. 115–118). New York, NY, USA. ACM.
   Google Scholar
• Harrison, C., Yeo, Z., & Hudson, S. E. (2010). Faster progress bars: Manipulating perceived duration with visual augmentations. Proceedings of the sigchi conference on human factors in computing systems (pp. 1545–1548). New York, NY, USA. ACM.
   Google Scholar
• Ju, W., & Takayama, L. (2009). Approachability: How people interpret automatic door movement as gesture. International Journal of Design, 3(2), 77–86.
   Web of Science ®Google Scholar
• Kazai, G., Kamps, J., & Milic-Frayling, N. (2013). An analysis of human factors and label accuracy in crowdsourcing relevance judgments. Information Retrieval, 16(2), 138–178. doi:10.1007/s10791-012-9205-0
   Web of Science ®Google Scholar
• Kieras, D. E., & Bovair, S. (1984). The role of a mental model in learning to operate a device. Cognitive Science, 8(3), 255–273. doi:10.1207/s15516709cog0803_3
   Web of Science ®Google Scholar
• Krause, J., Perer, A., & Ng, K. (2016). Interacting with predictions: Visual inspection of black-box machine learning models. Proceedings of the 2016 chi conference on human factors in computing systems (pp. 5686–5697). New York, NY, USA. ACM.
   Google Scholar
• Laird, D. A. (1932). How the consumer estimates quality by subconscious sensory impressions. Journal of Applied Psychology, 16(3), 241–246. doi:10.1037/h0074816
   Google Scholar
• Lim, B. Y., & Dey, A. K. (2011a). Design of an intelligible mobile context-aware application. Proceedings of the 13th international conference on human computer interaction with mobile devices and services (pp. 157–166). New York, NY, USA. ACM.
   Google Scholar
• Lim, B. Y., & Dey, A. K. (2011b). Investigating intelligibility for uncertain context-aware applications. Proceedings of the 13th international conference on ubiquitous computing (pp. 415–424). New York, NY, USA. ACM.
   Google Scholar
• Lim, B. Y., Dey, A. K., & Avrahami, D. (2009). Why and why not explanations improve the intelligibility of context-aware intelligent systems. Proceedings of the sigchi conference on human factors in computing systems (pp. 2119–2128). New York, NY, USA. ACM.
   Google Scholar
• Lyons, J. (2013, 01). Being transparent about transparency: A model for human-robot interaction. In Aaai spring symposium - technical report (p. 48–53). Retrieved from http://www.aaai.org/ocs/index.php/SSS/SSS13/paper/view/5712
   Google Scholar
• Mason, W., & Watts, D. J. (2010, May). Financial incentives and the “performance of crowds”. SIGKDD Explor Newsletter, 11(2), 100–108. doi:10.1145/1809400
   Google Scholar
• Mayo, E. (2004). The human problems of an industrial civilization. New York: Macmillan Co.
   Google Scholar
• Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology, 90(2), 227. doi:10.1037/h0031564
   PubMedGoogle Scholar
• Michotte, A. (1963). The perception of causality. Oxford, England: Basic Books.
   Google Scholar
• Norman, D. A. (2013). The design of everyday things: Revised and expanded edition. New York: Basic books.
   Google Scholar
• Nowacka, D., Hammerla, N. Y., Elsden, C., Plötz, T., & Kirk, D. (2015). Diri - the actuated helium balloon: A study of autonomous behaviour in interfaces. Proceedings of the 2015 acm international joint conference on pervasive and ubiquitous computing (pp. 349–360). New York, NY, USA. ACM.
   Google Scholar
• O’Donovan, J., Smyth, B., Gretarsson, B., Bostandjiev, S., & H ̈Ollerer, T. (2008). Peerchooser: Visual interactive recommendation. Proceedings of the sigchi conference on human factors in computing systems (pp. 1085–1088). New York, NY, USA. ACM.
   Google Scholar
• Padrao, G., Gonzalez-Franco, M., Sanchez-Vives, M. V., Slater, M., & Rodriguez-Fornells, A. (2016). Violating body movement semantics: Neural signatures of self-generated and external-generated errors. NeuroImage, 124, 147–156. doi:10.1016/j.neuroimage.2015.08.022
   PubMed Web of Science ®Google Scholar
• Pantelis, P. C., & Feldman, J. (2012). Exploring the mental space of autonomous intentional agents. Attention, Perception, & Psychophysics, 74(1), 239–249. doi:10.3758/s13414-011-0215-6
   PubMed Web of Science ®Google Scholar
• Parasuraman, R., & Riley, V. (1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors: The Journal of the Human Factors and Ergonomics Society, 39(2), 230–253. doi:10.1518/001872097778543886
   Web of Science ®Google Scholar
• Park, D., & Lee, J.-H. (2010a). Investigating the affective quality of motion in user inter- faces to improve user experience. In H. S. Yang, R. Malaka, J. Hoshino, & J. H. Han (Eds.), Entertainment computing - icec 2010: 9th international conference, icec 2010, seoul, korea, september 8-11, 2010. proceedings (pp. 67–78). Berlin, Heidelberg: Springer Berlin Heidelberg.
   Google Scholar
• Park, D., & Lee, J.-H. (2010b, December). Understanding how the affective quality of motion is perceived in the user interface. Computation Entertain, 8(2), 14:1–14: 11. doi:10.1145/1899687.1899696
   Google Scholar
• Popovic, J., Seitz, S. M., & Erdmann, M. (2003, October). Motion sketching for control of rigid-body simulations. ACM Transactions Graph, 22(4), 1034–1054. doi:10.1145/944020.944025
   Web of Science ®Google Scholar
• Reeves, B., & Nass, C. (1996). How people treat computers, television, and new media like real people and places. Cambridge, UK: CSLI Publications and Cambridge university press.
   Google Scholar
• Schlottmann, A., & Surian, L. (1999). Do 9-month-olds perceive causation-at-a-distance? Perception, 28(9), 1105–1113. doi:10.1068/p281105
   PubMed Web of Science ®Google Scholar
• Schwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. Journal of Personality and Social Psychology, 45(3), 513. doi:10.1037/0022-3514.45.3.513
   Web of Science ®Google Scholar
• Takayama, L., Dooley, D., & Ju, W. (2011). Expressing thought: Improving robot readability with animation principles. Proceedings of the 6th international conference on human-robot interaction (pp. 69–76). New York, NY, USA. ACM.
   Google Scholar
• Talbot, J., Lee, B., Kapoor, A., & Tan, D. S. (2009). Ensemble matrix: Interactive visualization to support machine learning with multiple classifiers. Proceedings of the sigchi conference on human factors in computing systems (pp. 1283–1292). New York, NY, USA. ACM.
   Google Scholar
• Tremoulet, P. D., & Feldman, J. (2000). Perception of animacy from the motion of a single object. Perception, 29(8), 943–951. doi:10.1068/p3101
   PubMed Web of Science ®Google Scholar
• Tullio, J., Dey, A. K., Chalecki, J., & Fogarty, J. (2007). How it works: A field study of non- technical users interacting with an intelligent system. Proceedings of the sigchi conference on human factors in computing systems (pp. 31–40). New York, NY, USA. ACM.
   Google Scholar
• Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. In (Vol. 211 pp. 453–458). American Association for the Advancement of Science.
   Google Scholar
• Verame, J. K. M., Costanza, E., & Ramchurn, S. D. (2016). The effect of displaying system confidence information on the usage of autonomous systems for non-specialist applications: A lab study. Proceedings of the 2016 chi conference on human factors in computing systems (pp. 4908–4920). New York, NY, USA. ACM.
   Google Scholar
• Vermeulen, J. (2010). Improving intelligibility and control in ubicomp. Proceedings of the 12th acm international conference adjunct papers on ubiquitous computing - adjunct (pp. 485–488). New York, NY, USA. ACM.
   Google Scholar
• Vermeulen, J., Luyten, K., Coninx, K., & Marquardt, N. (2014). The design of slow-motion feedback. Proceedings of the 2014 conference on designing interactive systems (pp. 267–270). New York, NY, USA. ACM.
   Google Scholar
• Ware, C. (2012). Information visualization: Perception for design. Boston: Elsevier.
   Google Scholar
• Yang, R., & Newman, M. W. (2013). Learning from a learning thermostat: Lessons for intelligent systems for the home. Proceedings of the 2013 acm international joint conference on pervasive and ubiquitous computing (pp. 93–102). New York, NY, USA. ACM.
   Google Scholar
• Yatani, K., Novati, M., Trusty, A., & Truong, K. N. (2011). Review spotlight: A user interface for summarizing user-generated reviews using adjective-noun word pairs. Proceedings of the sigchi conference on human factors in computing systems (pp. 1541–1550). New York, NY, USA. ACM.
   Google Scholar