Abstract
This paper introduces a new facet of social media, namely that depicting social interaction. More concretely, we address this problem from the perspective of nonverbal behavior-based analysis of competitive meetings. For our study, we made use of “The Apprentice” reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person’s role in a meeting: predicting the person with the highest status, and predicting the fired candidates. We address this problem by adopting both supervised and unsupervised strategies. The current study was carried out using nonverbal audio cues. Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. The analysis is based on two types of data: individual and relational measures. Results obtained from the analysis of a full season of the show are promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach has been conveniently compared with the Influence Model, demonstrating its superiority.
Similar content being viewed by others
Notes
This has been decided by the authors. It was set up between 80% and 95% from the length of an episode, depending on the case.
References
Ambady N, Bernieri F, Richeson J (2000) Towards a histology of social behavior: judgmental accuracy from thin slices of behavior. In: Zanna P (ed) Advances in experimental social psychology, pp 201–272
Bales R (1951) Interaction process analysis: a method for the study of small groups. Addison–Wesley, New York
Banerjee S, Rudnicky A (2004) Using simple speech-based features to detect the state of a meeting and the roles of the meeting participants. In: Proc. of int’l. conf. on spoken language processing (ICSLP), p N/A. Jeju Island, Korea
Basu S, Choudhury T, Clarkson B, Pentland A (2001) Learning human interactions with the influence model. In: Tech report 539. MIT Media Lab
Basu S, Choudhury T, Clarkson B, Pentland A (2001) Towards measuring human interactions in conversational settings. In: Proc. IEEE int’l. conf. on computer vision, workshop on cues in communication (CVPR-CUES). Kauai, Hawaii, USA
Benne K, Sheats P (1948) Functional roles of group members. J Soc Issues 4(2):41–49
Biddle T (1979) Role theory: expectations, identities, and behaviors. Academic, New York
Bormann E (1990) Comunicating in small groups: theory and practice. Harper and Row, New York
Burgoon J, Dunbar N (2006) Nonverbal expressions of dominance and power in human relationships. In: Manusov Vea (ed) The Sage handbook of nonverbal communication. Sage, pp 279–297
Dong W, Lepri B, Capelletti A, Pentland A, Pianesi F, Zancanaro M (2007) Using the influence model to recognize functional roles in meetings. In: Proc. of int’l. conf. on multimodal interfaces (ICMI), pp 271–278. Nagoya, Japan
Dunbar N, Burgoon J (2005) Perceptions of power and interactional dominance in interpersonal relationships. J Soc Pers Relatsh 22(2):207–233
Ellis D, Fisher B (1994) Group decision-making: communication and the group process. McGraw-Hill, New York
Favre S, Salamin H, Dines J, Vinciarelli A (2008) Role recognition in multiparty recordings using social affiliation networks and discrete distributions. In: Proc. int. conf. on multimodal interfaces (ICMI), p N/A. Chania, Crete Island, Greece
Gatica-Perez D (2006) Analyzing group interactions in conversations: a review. In: Proc. of IEEE int’l. conf. on multisensor fusion and integration for intelligent systems. Heidelberg, Germany
Gatica-Perez D (2009) Automatic nonverbal analysis of social interaction in small groups: a review. Image Vis Comput (Special Issue on Human Spontaneous Behavior) 27(12):1775–1787
Gatica-Perez D, Zhang D, Bengio S (2005) Extracting information from multimedia meeting collections. In: Proc. of ACM int. conf. on multimedia, workshop on multimedia information retrieval (ACM MM MIR). Singapore
Giddens A (1984) The constitution of society: outline of the theory of structuration. University of California Press, Berkeley
Goffman E (1959) The presentation of self in everyday life. Doubleday, New York
Graf H, Cosatto E, Strom V, Huang F (2002) Visual prosody: facial movements accompanying speech. In: Fifth IEEE int’l. conf. on automatic face and gesture recognition. Washington, DC
Gregory Jr S, Gallagher T (2002) Spectral analysis of candidates’ nonverbal vocal communication: predicting U.S. presidential election outcomes. Soc Psychol Q 65(3):298–308
Hanneman RA, Riddle M (2005) Introduction to social network methods. University of California (Riverside), Riverside, CA. Retrieved from http://faculty.ucr.edu/~hanneman/
Hare A (1976) Handbook of small group research. Free Press, New York
Jayagopi D, Ba S, Odobez JM, Gatica-Perez D (2008) Predicting two facets of social verticality in meetings from five-minute time slices and nonverbal cues. In: Proc. of int’l. conf. on multimodal interfaces (ICMI), p N/A. Chania, Greece
Jayagopi D, Hung H, Yeo C, Gatica-Perez D (2009) Modeling dominance in group conversations from nonverbal activity cues. IEEE Trans on Audio, Speech and Language Processing (Special Issue on Multimodal Processing for Speech-based Interactions) 17(3)
Katz D, Kahn R (1978) The social psychology of organization. Wiley, New York
McCowan I, Carletta J, Kraaij W, Ashby S, Bourban S, Flynn M, Guillemot M, Hain T, Kadlec J, Karaiskos V, Kronenthal M, Lathoud G, Lincoln M, Lisowska A, Post W, Reidsma D, Wellner P (2005) The ami meeting corpus. In: Proc. of the 5th int. conf. on methods and techniques in behavioral research, p N/A. Wageningen, The Netherlands
McCowan I, Gatica-Perez D, Bengio S, Lathoud G, Barnard M, Zhang D (2005) Automatic analysis of multimodal group actions in meetings. IEEE Trans Pattern Anal Mach Intell 27(3):305–317
McGrath J (1984) Groups: interaction and performance. Prentice Hall, New York
Otsuka K, Sawada H, Yamato J (2007) Automatic inference of cross-modal nonverbal interactions in multiparty conversations. In: Proc. ACM 9th int’l conf. on multimodal interfaces (ICMI), pp 255–262. Nagoya, Japan
Pentland A (2005) Socially aware computation and communication. Computer:63–70
Pentland A (2008) Honest signals. MIT Press, Cambridge, MA
Pentland A, Madan A (2005) Perception of social interest. In: Proc. IEEE intl. conf. on computer vision, workshop on modeling people and human interaction (ICCV-PHI). Beijing, China
Raducanu B, Vitrià J, Gatica-Perez D (2009) You are fired! nonverbal role analysis in competitive meetings. In: Proc. of int’l. conf. on audio, speech and signal processing (ICASSP), pp 1949–1952. Taipei, Taiwan
Rienks R, Zhang D, Gatica-Perez D, Post W (2006) Detection and application of influence rankings in small group meetings. In: Proc. ACM 8th int’l. conf. on multimodal interfaces (ICMI), pp 257–264. New York, US
Salazar A (1996) An analysis of the development and evolution of roles in the small group. Small Group Res 27(4):475–503
Schmid Mast M (2002) Dominance as expressed and inferred through speaking time: a meta-analysis. Human Commun Res 28(3):420–450
Smith-Lovin L, Brody C (1989) Interruptions in group discussions: the effects of gender and group composition. Am Sociol Rev 54(3):424–435
Stiefelhagen R, Chen S, Yang J (2005) Capturing interactions in meetings using omnidirectional cameras. International Journal of Distance Education Technologies 3(3):34–37
The Apprentice. http://www.nbc.com/The_Apprentice/
Valbonesi L, Ansari R, McNeill D, Quek F, Duncan S, McCullough KE, Bryll R (2002) Multimodal signal analysis of prosody and hand motion: temporal correlation of speech and gesture. In: EUSIPCO. Toulouse, France (2002)
Vinciarelli A (2007) Speakers role recognition in multiparty audio recordings using social network analysis and duration distribution modeling. IEEE Trans Multimedia 9(6):1215–1226
Wasserman S, Faust K (1994) Social network analysis. Cambridge University Press, Cambridge, UK
Weber M (2000) Basic concepts in sociology. Citadel, California
Zancanaro M, Lepri B, Pianesi F (2006) Automatic detection of group functional roles in face to face interactions. In: Proc. of int’l. conf. on multimodal interfaces (ICMI), p N/A. Banff, Canada
Acknowledgements
This work was done while B. Raducanu visited IDIAP as an AMIDA project trainee. D. Gatica-Perez thanks the support of the AMIDA and IM2 projects. B. Raducanu is also supported by MEC Grants TIN2009-14404-C02-01 and CONSOLIDER-INGENIO CSD 2007-00018, Spain. We thank Dinesh Jayagopi (IDIAP) for providing the code for Influence Model.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Raducanu, B., Gatica-Perez, D. Inferring competitive role patterns in reality TV show through nonverbal analysis. Multimed Tools Appl 56, 207–226 (2012). https://doi.org/10.1007/s11042-010-0545-8
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-010-0545-8