Increasing the Crowd's Capacity to Create: How Alternative Generation Affects the Diversity, Relevance and Effectiveness of Generated Ads

Ren, J., Nickerson, J. V., Mason, W., Sakamoto, Y. and Graber, B. "Increasing the Crowd’s Capacity to Create: How Alternative Generation Affects the Diversity, Relevance and Effectiveness of Generated Ads", Decision Support Systems, special issue on "Social Decision Making and Crowdsourcing", Forthc

34 Pages Posted: 26 Nov 2013 Last revised: 11 Dec 2013

See all articles by Jie Ren

Jie Ren

Fordham University

Jeffrey V. Nickerson

Stevens Institute of Technology - School of Business

Winter Mason

Facebook; Stevens Institute of Technology - School of Business

Yasuaki Sakamoto

AXA Direct Japan

Bruno Graber

Stevens Institute of Technology - School of Business

Date Written: February 20, 2013

Abstract

Crowds can generate ideas by searching for new designs. A model for such crowd-based search is proposed consisting of three major forces: the problem domain, the actors, and the process. One particular process that can perform such search is that described by human based genetic algorithms, in which crowds are responsible for creating, modifying, and combining designs. This study looks at one aspect of the process: the alternative generation algorithm. Three systems were built that performed greenfield, modification and combination-based alternative generation. These were compared in an experiment involving 2220 participants who played different roles in creating and evaluating advertisements. The results favor the modification system. This suggests for domains like advertising, crowd-based design systems should encourage a series of modifications of initial ideas. For designers of other crowd-based systems in other problem domains, this study suggests that both modification and combination processes should be tested and their ratio of use adjusted according to the results obtained, much as the ratio of mutation and crossover are adjusted in genetic algorithms.

Keywords: creativity, human based genetic algorithms, advertisement, crowdsourcing, design, evolutionary computing

JEL Classification: M1, M2, M3, M5

Suggested Citation

Ren, Jie and Nickerson, Jeffrey V. and Mason, Winter and Sakamoto, Yasuaki and Graber, Bruno, Increasing the Crowd's Capacity to Create: How Alternative Generation Affects the Diversity, Relevance and Effectiveness of Generated Ads (February 20, 2013). Ren, J., Nickerson, J. V., Mason, W., Sakamoto, Y. and Graber, B. "Increasing the Crowd’s Capacity to Create: How Alternative Generation Affects the Diversity, Relevance and Effectiveness of Generated Ads", Decision Support Systems, special issue on "Social Decision Making and Crowdsourcing", Forthc, Available at SSRN: https://ssrn.com/abstract=2359207

Jie Ren (Contact Author)

Fordham University ( email )

Rose Hill Campus Bronx
New York, NY 10458
United States

Jeffrey V. Nickerson

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States

Winter Mason

Facebook ( email )

1601 S. California Ave.
Palo Alto, CA 94304
United States

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States

Yasuaki Sakamoto

AXA Direct Japan ( email )

Japan

Bruno Graber

Stevens Institute of Technology - School of Business ( email )

Hoboken, NJ 07030
United States

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