ACM Home Page
Please provide us with feedback. Feedback
Searching for expertise
Full text PdfPdf (227 KB)
Source
Conference on Human Factors in Computing Systems archive
Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems table of contents
Florence, Italy
SESSION: Search table of contents
Pages 1093-1096  
Year of Publication: 2008
ISBN:978-1-60558-011-1
Authors
Kate Ehrlich  IBM, Cambridge, MA, USA
N. Sadat Shami  Cornell University, Ithaca, NY, USA
Sponsors
ACM: Association for Computing Machinery
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 38,   Downloads (12 Months): 241,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
Save this Article to a Binder    Display Formats: BibTex  EndNote ACM Ref   
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1357054.1357224
What is a DOI?

ABSTRACT

It is well established that there is a need to find experts to get answers or advice. A variety of expertise locator tools have emerged to help locate the right person. But there is little systematic study on what people are really looking for when such systems are used and how external factors such as job role may shape that search. We conducted a study of 75 employees who were current users of an expertise locator system. An analysis of the reasons for their search revealed that people in client facing roles are primarily seeking to have a dialog with an expert, while others are just as likely to seek answers to technical questions. We also surveyed various tools for finding experts and found that corporate directories and personal networks were most often cited as alternatives to an expertise locator. We discuss the implications of these results for the design of tools for finding experts and expert knowledge.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
Constant, D., Sproull, L., and Kiesler, S. The kindness of strangers: The usefulness of electronic weak ties for Technical Advice. Organization Science, 7, 2 (1996), 119--135.
 
3
Ehrlich, K. Locating expertise: Design issues for an expertise locator system. In M. S. Ackerman, P. Volkmar and V. Wulf (eds.): Beyond Knowledge Management: Sharing Expertise. MIT Press, Cambridge, MA (2003), 137--158.
4
 
5
Farrell, S. and Lau, T. Fringe Contacts: People-Tagging for the Enterprise. In Proc. Workshop on Collaborative Web Tagging, (2006).
 
6
Lin, C.-Y., Griffiths-Fisher, V., Ehrlich, K., and Desforges, C. SmallBlue: People mining for expertise search and social network analysis. IEEE Multimedia Magazine, (2008).
7
8
9
 
10
Nardi, B.A., Whittaker, S., and Schwarz, H. It's not what you know, it's who you know: Work in the information age. First Monday 2002
11
 
12
Yiman-Seid, D. and Kobsa, A. Expert-finding systems for organizations: Problem and domain analysis and the DEMOIR approach. In M. S. Ackerman, V. Pipek and V. Wulf (eds.): Sharing Expertise: Beyond Knowledge Management. MIT Press, Cambridge, MA (2003), 328--358.

Collaborative Colleagues:
Kate Ehrlich: colleagues
N. Sadat Shami: colleagues