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Audience Selection for On-Line Brand Advertising: Privacy-Friendly Social Network Targeting

9 Pages Posted: 25 May 2011  

Foster Provost

New York University

Brian Dalessandro

affiliation not provided to SSRN

Rod Hook

affiliation not provided to SSRN

Xiaohan Zhang

New York University (NYU) - Department of Information, Operations, and Management Sciences

Alan Murray

affiliation not provided to SSRN

Date Written: May, 25 2011

Abstract

This paper describes and evaluates privacy-friendly methods for extracting quasi-social networks from browser behavior on user-generated content sites, for the purpose of finding good audiences for brand advertising (as opposed to click maximizing, for example). Targeting social-network neighbors resonates well with advertisers, and on-line browsing behavior data counterintuitively can allow the identification of good audiences anonymously. Besides being one of the first papers to our knowledge on data mining for on-line brand advertising, this paper makes several important contributions. We introduce a framework for evaluating brand audiences, in analogy to predictive-modeling holdout evaluation. We introduce methods for extracting quasi-social networks from data on visitations to social networking pages, without collecting any information on the identities of the browsers or the content of the social-network pages. We introduce measures of brand proximity in the network, and show that audiences with high brand proximity indeed show substantially higher brand affinity. Finally, we provide evidence that the quasi-social network embeds a true social network, which along with results from social theory offers one explanation for the increases in audience brand affinity.

Keywords: on-line advertising, predictive modeling, social

Suggested Citation

Provost, Foster and Dalessandro, Brian and Hook, Rod and Zhang, Xiaohan and Murray, Alan, Audience Selection for On-Line Brand Advertising: Privacy-Friendly Social Network Targeting (May, 25 2011). Available at SSRN: https://ssrn.com/abstract=1852644 or http://dx.doi.org/10.2139/ssrn.1852644

Foster Provost (Contact Author)

New York University ( email )

44 West Fourth Street
New York, NY 10012
United States

Brian Dalessandro

affiliation not provided to SSRN ( email )

Rod Hook

affiliation not provided to SSRN ( email )

Xiaohan Zhang

New York University (NYU) - Department of Information, Operations, and Management Sciences ( email )

44 West Fourth Street
New York, NY 10012
United States
2129980390 (Phone)

Alan Murray

affiliation not provided to SSRN ( email )

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