Making sense of strangers’
 expertise from signals in
     digital artifacts

N.
Sadat
Shami,
Kate
Ehrlich,
Geri
Gay,
Jeff
...
Proliferation of online information




“An abundance of information leads to a poverty of

                    attention”...
Outline of talk


 Research question

 Prior research
    expertise search, self presentation

 The use of signaling t...
General Research Question

 ‘People sensemaking’
   When looking for specific expertise using a tool, how

  do individu...
Context of study

 Context
   Finding an expert to contact

   Evaluating them by by viewing

  online profile

   Usu...
Prior research

 Expertise search
    Many tools built to find experts (Terveen &

   McDonald, 2005)

    Focus on fin...
Prior research

 Self presentation
    Selective self presentation (Goffman, 1959)

    Identity claims and behavioral ...
Signaling theory


 Interpretive framework

    Theory of communication

    Process of discerning and interpreting

  ...
Signaling theory


Reliable signals are pieces of information that are hard to
fake (Spence, 1973; Zahavi, 1975; Zahavi & ...
Signals in digital artifacts


 Assessment signals

    Quality correlated with trait

    Quality is ‘wasted’ in produ...
Signals of expertise in digital artifacts


Conventional signal             Assessment signal
Study: Making sense of the different pieces of
        Information on a profile page
Enterprise expertise locator system

 SmallBlue, renamed to Atlas™ (Ehrlich et al. 2007;
  Lin et al., 2008)
    Conveni...
Participants

 Email invitation
    Performed at least 20 searches using SmallBlue

    131 employees, 67 responded (51...
User Task


 Find an expert in ‘AJAX’
    On a committee evaluating a new project

   proposal. Need a second opinion on...
“AJAX” scenario: User Task




Shami, Ehrlich, Millen, CHI 2007, Pick me! Link selection in expertise search
Corporate        Recommended                      Mailing list
directory        and alternate connection paths   membershi...
Self reported rating data
 Outcome variable (1-9 scale)
    Likelihood of contacting a person

 Predictor variables (1-...
Profile data

 Outcome variable
    Likelihood of contacting a person (1-9 scale)

 Predictor variables
    Participat...
Results from rating data: Social software


 For each point increase in perceived helpfulness of social

software, likeli...
Results from rating data: social closeness

 For each point increase in perceived helpfulness of social
connection inform...
Results from profile data (counts)



 Posting one more tag, blog, or forum post increased

likelihood of contact by 0.01...
Signaling theory as a decision aid

 Signaling theory in ‘people sensemaking’
   Focus on information that is hard to fa...
Implications for design

 ‘Page rank’ for experts
    Analyze structural patterns to find ‘answer people’ (Wesler
     e...
Thank you!




         sadat@us.ibm.com

http://www.research.ibm.com/social
Making sense of strangers' expertise from signals in digital artifacts
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Making sense of strangers' expertise from signals in digital artifacts

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Introduces the use of signaling theory as a decision aid in the people sensemaking process in deciding whom to contact for expertise. This work was presented at CHI 2009 in Boston, MA, USA.

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Making sense of strangers' expertise from signals in digital artifacts

  1. 1. Making sense of strangers’ expertise from signals in digital artifacts N.
Sadat
Shami,
Kate
Ehrlich,
Geri
Gay,
Jeff
Hancock
  2. 2. Proliferation of online information “An abundance of information leads to a poverty of attention” - Herbert Simon
  3. 3. Outline of talk  Research question  Prior research  expertise search, self presentation  The use of signaling theory as a decision aid  Study design  Findings
  4. 4. General Research Question  ‘People sensemaking’  When looking for specific expertise using a tool, how do individuals make sense of different information about a stranger conveyed through digital artifacts?
  5. 5. Context of study  Context  Finding an expert to contact  Evaluating them by by viewing online profile  Usually only after personal networks are exhausted (Borgatti & Cross, 2003; Cross & Sproull, 2004)
  6. 6. Prior research  Expertise search  Many tools built to find experts (Terveen & McDonald, 2005)  Focus on finding ‘best expert’  Less attention on finding people likely to respond
  7. 7. Prior research  Self presentation  Selective self presentation (Goffman, 1959)  Identity claims and behavioral residue (Vizier & Gosling, 2004)  Profiles on social networking sites (Donath, 2007; Lampe et al. 2007)  Deception can occur (Hancock et al. 2007)
  8. 8. Signaling theory  Interpretive framework  Theory of communication  Process of discerning and interpreting conveyed information  Useful for decision making under uncertainty where deception can occur
  9. 9. Signaling theory Reliable signals are pieces of information that are hard to fake (Spence, 1973; Zahavi, 1975; Zahavi & Zahavi, 1997)
  10. 10. Signals in digital artifacts  Assessment signals  Quality correlated with trait  Quality is ‘wasted’ in production  Conventional signals  Need not possess the trait  Social norms and mores maintain quality Based on Donath, in press
  11. 11. Signals of expertise in digital artifacts Conventional signal Assessment signal
  12. 12. Study: Making sense of the different pieces of Information on a profile page
  13. 13. Enterprise expertise locator system  SmallBlue, renamed to Atlas™ (Ehrlich et al. 2007; Lin et al., 2008)  Convenient platform for research  Description  Mines outgoing email and instant messaging transcripts  Data aggregator  Opt in system
  14. 14. Participants  Email invitation  Performed at least 20 searches using SmallBlue  131 employees, 67 responded (51.15%)  Demographics  21 countries (majority US - 43.75%)  48 males, 19 females  Average tenure 10.5 years  Majority from consulting or sales (37.5%)
  15. 15. User Task  Find an expert in ‘AJAX’  On a committee evaluating a new project proposal. Need a second opinion on whether AJAX is appropriate for the project.  Why ‘AJAX’?  Among top searches in SmallBlue
  16. 16. “AJAX” scenario: User Task Shami, Ehrlich, Millen, CHI 2007, Pick me! Link selection in expertise search
  17. 17. Corporate Recommended Mailing list directory and alternate connection paths membership information Corporate directory self Social reported bookmarking expertise tags Blog posts Forum posts Social bookmarks
  18. 18. Self reported rating data  Outcome variable (1-9 scale)  Likelihood of contacting a person  Predictor variables (1-9 scale)  Social software (tags + blogs + forums)  Social connection information  Mailing list membership  Corporate directory info  Self-described expertise  Control variables  Familiarity with AJAX
  19. 19. Profile data  Outcome variable  Likelihood of contacting a person (1-9 scale)  Predictor variables  Participation in social software i.e. count of: tags + blog posts + forum posts (0-1100)  Social closeness (0-6)  Mailing list membership (0-13)  Control variables  Familiarity with AJAX
  20. 20. Results from rating data: Social software  For each point increase in perceived helpfulness of social software, likelihood of contact increased by 0.33 points (p < 0.01). “People who use dogear or IBM Forums are more likely to reach out to the community with their questions and their expertise and therefore I would think they would be more likely to assist in sharing their own expertise.”
  21. 21. Results from rating data: social closeness  For each point increase in perceived helpfulness of social connection information, likelihood of contact increased by 0.37 points (p < 0.01). “I know the people that the system recommended to go through. If I contact them, I'll be able to get straight to him.” “...it wouldn't be too much of a cold call to say ‘hi, I understand you know my colleague so and so, I'm calling you about this other topic.’ I guess it would make me feel more comfortable knowing that I could sort of name drop.”
  22. 22. Results from profile data (counts)  Posting one more tag, blog, or forum post increased likelihood of contact by 0.01 points (p < 0.001).  Each degree increase in social closeness corresponds to a 0.29 point increase in likelihood of contact (p < 0.01)
  23. 23. Signaling theory as a decision aid  Signaling theory in ‘people sensemaking’  Focus on information that is hard to fake  More credible, reliable, less open to deception  Social software related to approachability  Social connection information related to accessibility and verifying expertise.
  24. 24. Implications for design  ‘Page rank’ for experts  Analyze structural patterns to find ‘answer people’ (Wesler et al., 2007)  No systematic analysis of social software  Find others likely to respond
  25. 25. Thank you! sadat@us.ibm.com http://www.research.ibm.com/social

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