Audience selection for on-line brand advertising: Privacy-friendly social network targeting

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2009, Pages 707-715

  Provost, Foster ^a   Dalessandro, Brian ^b   Hook, Rod ^b   Zhang, Xiaohan ^a   Murray, Alan ^b  

^a NEW YORK UNIVERSITY   (United States)

^b NONE   (United States)

Author keywords

On line advertising; Predictive modeling; Privacy; Social networks; User generated content

Indexed keywords

ON-LINE ADVERTISING; PREDICTIVE MODELING; PRIVACY; SOCIAL NETWORKS; USER-GENERATED CONTENT;

DATA MINING;

EID: 70350645569     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1557019.1557098     Document Type: Conference Paper

References (27)

1. Atlas-Institute. Where can you find your customer? Try the intersection of search and display. Digital Marketing Insight, 2007. http://www. AtlasSolutions.com/insights.
2. R. Bell, Y. Koren, and C. Volinsky. Chasing $1,000,000: How we won the Netflix progress prize. ASA Statistical and Computing Graphics Newsletter, 18(2):4-12, 2007.
3. A. Broder, M. Fontoura, V. Josifovski, and L. Riedel. A semantic approach to contextual advertising. In SIGIR '07, pages 559-566, 2007.
4. M. Ciaramita, V. Murdock, and V. Plachouras. Online learning from click data for sponsored search. In WWW '08, pages 227-236, 2008.
5. E. K. Clemons, S. Barnett, and A. Appadurai. The future of advertising and the value of social network websites: some preliminary examinations. In ICEC '07, pages 267-276, 2007.
6. comScore. New study shows that heavy clickers distort reality of display advertising click-through metrics. http://www.comscore.com/press/release.asp? press=2060.
7. comScore. Whither the Click? comScore brand metrix norms prove "view-thru" value of on-line advertising. http://www.comscore.com/ press/release.asp?press=2587.
8. R. Coolbrith. On-line advertising 2.0: The opportunity in non-premium display. ThinkEquity Partners LLC Industry Report, September 2007.
9. C. Cortes, D. Pregibon, and C. Volinsky. Communities of interest. Intell. Data Analysis, 6(3):211-219, 2002.
10. E. R. DeLong, D. M. DeLong, and D. L. Clarke-Pearson. Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach. Biometrics, 44(3):837-845, 1988.
11. G. T. Duncan, S. A. Keller-McNulty, and S. L. Stokes. Disclosure risk vs. data utility: The r-u confidentiality map. Technical Report Technical Report Number 121, National Institute of Statistical Sciences, 2001.
12. C. Elkan and K. Noto. Learning classifiers from only positive and unlabeled data. In ACM SIGKDD '08, pages 213-220, 2008.
13. T. Fawcett. ROC Graphs: Notes and Practical Considerations for Data Mining Researchers. HP Laboratories technical report, 2003.
14. F. Fouss, A. Pirotte, J. Renders, and M. Saerens. Random-walk computation of similarities between nodes of a graph, with application to collaborative recommendation. IEEE TKDE, 19(3):355-369, 2007.
15. S. Hill and F. Provost. The myth of the double-blind review? Author identification using only citations. ACM SIGKDD Explorations, 5(2):179-184, 2003.
16. S. Hill, F. Provost, and C. Volinsky. Network-based marketing: Identifying likely adopters via consumer networks. Statistical Science, 22(2):256-276, 2006.
17. S. Hill, F. Provost, and C. Volinsky. Learning and Inference in Massive Social Networks. In The 5th Intl. Wkshp. on Mining and Learning with Graphs, 2007.
18. G. Jeh and J. Widom. Simrank: a measure of structural-context similarity. In Proc. of ACM SIGKDD '02, pages 538-543, 2002.
19. Y. Koren, S. C. North, and C. Volinsky. Measuring and extracting proximity in networks. In Proc. of ACM SIGKDD '06, pages 245-255, 2006.
20. Lotame. Moms in social media. Lotame I.D. Reports, November 2008. http://www.Lotame.com.
21. M. McPherson, L. Smith-Lovin, and J. M. Cook. Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27:415-444, 2001.
22. A. Narayanan and V. Shmatikov. De-anonymizing social networks. 2009. To appear at IEEE Security and Privacy '09.
23. J. C. Perez. Facebook's beacon more intrusive than previously thought. 2007.
24. F. Provost, P. Melville, and M. Saar-Tsechansky. Data acquisition and cost-effective predictive modeling: targeting offers for electronic commerce. In Proceedings of ICEC-07, pages 389-398, 2007.
25. J. Sun, H. Qu, D. Chakrabarti, and C. Faloutsos. Neighborhood formation and anomaly detection in bipartite graphs. In Proc. ICDM '05, 2005.
26. S. White and P. Smyth. Algorithms for estimating relative importance in networks. In Proc. of ACM SIGKDD '03, pages 266-275, 2003.
27. B. Zhou, J. Pei, and W.-S. Luk. A brief survey on anonymization techniques for privacy preserving publishing of social network data. ACM SIGKDD Explorations, 10(2):12-22, 2008.