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Making sense of strangers' expertise from signals in digital artifacts

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Published:04 April 2009Publication History

ABSTRACT

Contemporary work increasingly involves interacting with strangers in technology-mediated environments. In this context, we come to rely on digital artifacts to infer characteristics of other people. This paper reports the results of a study conducted in a global company that used expertise search as a vehicle for exploring how people interpret a range of information available in online profiles in evaluating whom to interact with for expertise. Using signaling theory as a conceptual framework, we describe how certain 'signals' in various social software are hard to fake, and are thus more reliable indicators of expertise. Multi-level regression analysis revealed that participation in social software, social connection information, and self-described expertise in the corporate directory were significantly helpful in the decision to contact someone for expertise. Qualitative analysis provided further insights regarding the interpretations people form of others' expertise from digital artifacts. We conclude with suggestions on differentiating various types of information available within online profiles and implications for the design of expertise locator/recommender systems.

References

  1. Ackerman, M. S. Augmenting the organizational memory: a field study of answer garden. In Proc. CSCW 1994, ACM Press (1994), 243--252. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Adler, P. S. and Kwon, S.-W. Social capital: Prospects for a new concept. The Academy of Management Review 27, 1 (2002), 17--40.Google ScholarGoogle ScholarCross RefCross Ref
  3. Borgatti, S. P. and Cross, R. A Relational View of Information Seeking and Learning in Social Networks. Management Science 49, 4 (2003), 432--445. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Carroll, J. M. and Rosson, M. B. Getting around the task-artifact cycle: How to make claims and design by scenario. ACM Transactions on Information Systems 10, 2 (1992), 181--212. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Cronk, L. The application of animal signaling theory to human phenomena: some thoughts and clarifications. Social Science Information 44, 4 (2005), 603--620.Google ScholarGoogle ScholarCross RefCross Ref
  6. Dervin, B. From the mind's eye of the user: The sense-making qualitative-quantitative methodology. In J. Glazier and R. Powell (Eds.), Qualitative research in information management (pp. 61--84). Englewood, CO: Libraries Unlimited, 1992.Google ScholarGoogle Scholar
  7. Donath, J. Identity and deception in the virtual community. In M. A. Smith and P. Kollock (Eds.), Communities in cyberspace (pp. 29--59). London; New York: Routledge, 1999.Google ScholarGoogle Scholar
  8. Donath, J. Signals in Social Supernets. Journal of Computer-Mediated Communication 13, 1 (2007), 231--251.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Donath, J. Signals, Truth&Design. MIT Press, Cambridge, MA, In Press.Google ScholarGoogle Scholar
  10. Ehrlich, K., Lin, C.-Y. and Griffiths-Fisher, V. Searching for experts in the enterprise: Combining text and social network analysis. In Proc. GROUP 2007, ACM Press (2007), 117--126. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Ellison, N., Heino, R. D. and Gibbs, J. L. Managing Impressions Online: Self-Presentation Processes in the Online Dating Environment. Journal of Computer-Mediated Communication 11, 2 (2006), 415--441.Google ScholarGoogle ScholarCross RefCross Ref
  12. Fiore, A. T., Taylor, L. S., Mendelsohn, G. A. and Hearst, M. Assessing attractiveness in online dating profiles. In Proc. CHI 2008, ACM Press (2008), 797--806. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Fiske, S. T., Lin, M. H. and Neuberg, S. L. The Continuum Model: Ten years later. In S. Chaiken and Y. Trope (Eds.), Dual process theories in social psychology (pp. 231--254). New York: Guilford, 1999.Google ScholarGoogle Scholar
  14. Frank, R. H. Microeconomics and behavior. McGraw-Hill, New York, 2001.Google ScholarGoogle Scholar
  15. Furnas, G. W. and Russell, D. M. Making sense of sensemaking. In Proc. CHI 2005, ACM Press (2005), 2115--2116. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Goffman, E. The presentation of self in everyday life. Doubleday, Garden City, N.Y., 1959.Google ScholarGoogle Scholar
  17. Gosling, S. D., Gaddis, S. and Vazire, S. Personality Impressions Based on Facebook Profiles. In Proc. ICWSM '07, (2007),Google ScholarGoogle Scholar
  18. Gosling, S. D., Ko, S. J., Mannarelli, T. and Morris, M. E. A room with a cue: Personality judgments based on offices and bedrooms. Journal of Personality and Social Psychology 82, 3 (2002), 379--398.Google ScholarGoogle ScholarCross RefCross Ref
  19. Gotz, D. The ScratchPad: Sensemaking support for the web. In Proc. WWW 2007, ACM Press (2007), 1329--1330. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Hancock, J. T., Toma, C. and Ellison, N. The truth about lying in online dating profiles. In Proc. CHI 2007, ACM Press (2007), 449--452. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Hertzum, M. and Pejtersen, A. M. The information-seeking practices of engineers: searching for documents as well as for people. Information Processing&Management 36, 5 (2000), 761--778. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Hill, W. and Terveen, L. G. Using frequency-of-mention in public conversations for social filtering. In Proc. CSCW 1996, ACM Press (1996), 106--112. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Kautz, H., Selman, B. and Shah, M. Referral Web: combining social networks and collaborative filtering. Communications of the ACM 40, 3 (1997), 63--65. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Lampe, C., Ellison, N. and Steinfield, C. A familiar face(book): profile elements as signals in an online social network. In Proc. CHI 2007, ACM Press (2007), 435--444. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Lin, C.-Y., Ehrlich, K., Griffiths-Fisher, V. and Desforges, C. SmallBlue: People Mining for Expertise Search. IEEE Multimedia Magazine 15, 1 (2008), 78--84. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Marlow, C., Naaman, M., Boyd, D. and Davis, M. HT06, tagging paper, taxonomy, Flickr, academic article, to read. In Proc. Hyptertext 2006, ACM (2006), 31--40. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. McDonald, D. W. and Ackerman, M. S. Just talk to me: A field study of expertise location. In Proc. CSCW 1998, ACM Press (1998), 315--324. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. McDonald, D. W. and Ackerman, M. S. Expertise recommender: a flexible recommendation system and architecture. In Proc. CSCW 2000, ACM Press (2000), 231--240. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Mika, P. Flink: Semantic Web technology for the extraction and analysis of social networks. Journal of Web Semantics 3, 2-3 (2005), 211--223. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Oreg, S. and Nov, O. Exploring motivations for contributing to open source initiatives: The roles of contribution context and personal values. Computers in Human Behavior 24, 5 (2008), 2055--2073. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Palazzolo, E. T. Organizing for Information Retrieval in Transactive Memory Systems. Communication Research 32, 6 (2005), 726--761.Google ScholarGoogle Scholar
  32. Pan, B., Hembrooke, H., Joachims, T., Lorigo, L., Gay, G. and Granka, L. In Google We Trust: Users' Decisions on Rank, Position, and Relevance. Journal of Computer-Mediated Communication 12, 3 (2007), 801--823.Google ScholarGoogle ScholarCross RefCross Ref
  33. Pentland, A. Honest signals: How they shape our world. MIT Press, Cambridge, MA, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Randall, D., O'Brien, J., Rouncefield, M. and Hughes, J. A. Organizational Memory and CSCW: Supporting the Mavis Phenomenon. In Proc. OZCHI 1996, IEEE Computer Society (1996), 26--33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Reichling, T., Veith, M. and Wulf, V. Expert Recommender: Designing for a Network Organization. Computer Supported Cooperative Work (CSCW) 16, 4 (2007), 431--465. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Riegelsberger, J., Counts, S., Farnham, S. D. and Philips, B. C. Sounds good to me: Effects of photo and voice profiles on gaming partner choice. In Proc. CSCW 2006, ACM Press (2006), 159--162. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Russell, D. M., Stefik, M. J., Pirolli, P. and Card, S. K. The cost structure of sensemaking. In Proc. CHI 1993, ACM Press (1993), 269--276. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Shami, N. S., Ehrlich, K. and Millen, D. R. Pick me! Link selection in expertise search results. In Proc. CHI 2008, ACM Press (2008), 1089--1092. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Shami, N. S., Yuan, Y. C., Cosley, D., Xia, L. and Gay, G. That's what friends are for: facilitating 'who knows what' across group boundaries. In Proc. GROUP 2007, ACM (2007), 379--382. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Spence, M. Job Market Signaling. Quarterly Journal of Economics 87, 3 (1973), 355--374.Google ScholarGoogle ScholarCross RefCross Ref
  41. Stecher, K. B. and Counts, S. Spontaneous inference of personality traits from online profiles. In Proc. ICWSM 2008, (2008).Google ScholarGoogle Scholar
  42. Terveen, L. G. and McDonald, D. Social matching: A framework and research agenda. ACM Transactions on Computer Human Interaction (TOCHI) 12, 3 (2005), 401--434. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Terveen, L. G., Selfridge, P. G. and Long, M. D. Living Design Memory: Framework, Implementation, Lessons Learned. Human-Computer Interaction 10, 1 (1995), 1--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Thom-Santelli, J., Muller, M. J. and Millen, D. R. Social tagging roles: publishers, evangelists, leaders. In Proc. CHI 2008, ACM Press (2008), 1041--1044. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Vazire, S. and Gosling, S. D. e-Perceptions: Personality Impressions Based on Personal Websites. Journal of Personality and Social Psychology 87, 1 (2004), 123--132.Google ScholarGoogle ScholarCross RefCross Ref
  46. Welser, H., Gleave, E., Fisher, D. and Smith, M. A. Visualizing the Signatures of Social Roles in Online Discussion Groups. Journal of Social Structure 8, 2 (2007).Google ScholarGoogle Scholar
  47. Zahavi, A. Mate selection - A selection for a handicap. Journal of Theoretical Biology 53, 1 (1975), 205--214.Google ScholarGoogle ScholarCross RefCross Ref
  48. Zahavi, A. and Zahavi, A. The handicap principle a missing piece of Darwin's puzzle. Oxford University Press, New York, 1997.Google ScholarGoogle Scholar

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        cover image ACM Conferences
        CHI '09: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
        April 2009
        2426 pages
        ISBN:9781605582467
        DOI:10.1145/1518701

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        • Published: 4 April 2009

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