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Web credibility research: a method for online experiments and early study results
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Source Conference on Human Factors in Computing Systems archive
CHI '01 extended abstracts on Human factors in computing systems table of contents
Seattle, Washington
SESSION: Short talks: trust, credibility, community table of contents
Pages: 295 - 296  
Year of Publication: 2001
ISBN:1-58113-340-5
Authors
BJ Fogg  Stanford University, Stanford, CA
Jonathan Marshall  Stanford University, Stanford, CA
Tami Kameda  Stanford University, Stanford, CA
Joshua Solomon  Stanford University, Stanford, CA
Akshay Rangnekar  Reactivity, Belmont, CA
John Boyd  Stanford University, Stanford, CA
Bonny Brown  Vividence Corp., San Mateo, CA
Sponsor
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 58,   Downloads (12 Months): 221,   Citation Count: 19
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ABSTRACT

Through iterative design and testing, we developed a procedure for conducting online experiments. Using this research method, we conducted two recent studies on Web credibility. The data from the first study suggest that Web banner ads reduce the perceived credibility of a Web page's content. The data from the second study show that attribution elements--in this case, author photographs--can also affect the credibility of Web content. This research method and our early results have implications for both HCI researchers and Web site designers.


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
Cheskin Research, S.A.S., eCommerce Trust Study. 1999. See www.studioarchetype.com/headlines/etrust_frameset.html
 
2
Critchfield, R. Credibility and Web Site Design, 1998. See www.warner.edu/critchfield/hci/critchfield.html
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6
Morkes, J. and Nielsen, J., Concise, Scannable and Objective: How to Write for the Web, 1997. See www.useit.com/papers/webwriting/writing.html

CITED BY  19

Collaborative Colleagues:
BJ Fogg: colleagues
Jonathan Marshall: colleagues
Tami Kameda: colleagues
Joshua Solomon: colleagues
Akshay Rangnekar: colleagues
John Boyd: colleagues
Bonny Brown: colleagues