Paper Info
Title
Max-Intensity: Detecting Competitive Advertiser Communities in Sponsored Search Market
Abstract
In a sponsored search market, the problem of measuring the intensity of competition among advertisers is increasingly gaining prominence today. Usually, search providers want to monitor the advertiser communities that share common bidding keywords, so that they can intervene when competition slackens. However, to the best of our knowledge, not much research has been conducted in identifying advertiser communities and understanding competition within these communities. In this paper we introduce a novel approach to detect competitive communities in a weighted bi-partite network formed by advertisers and their bidding keywords. The proposed approach is based on an advertiser vertex metric called intensity score, which takes the following two factors into consideration: the competitors that bid on the same keywords, and the advertisers' consumption proportion within the community. Evidence shows that when market competition rises, the revenue for a search provider also increases. Our community detection algorithm Max-Intensity is designed to detect communities which have the maximum intensity score. In this paper, we conduct experiments and validate the performance of Max-Intensity on sponsored search advertising data. Compared to baseline methods, the communities detected by our algorithm have low Herfindahl-Hirschman index (HHI) and comprehensive concentration index (CCI), which demonstrates that the communities given by Max-Intensity can capture the structure of the competitive communities.
Year
DOI
Venue
2015
10.1109/ICDM.2015.128
IEEE International Conference on DataMining
Keywords
Field
DocType
Competition Community Detection,Competition Coefficient,Max-Intensity,Sponsored Search
Revenue,Search advertising,Data modeling,Data mining,Search engine,Computer science,Bidding,Market competition,Competitor analysis
Conference
ISSN
Citations 
PageRank 
1550-4786
1
0.35
References 
Authors
8
6
Name
Order
Citations
PageRank
Wenchao Yu114715.44
Ariyam Das2348.00
Justin Wood310.69
Wei Wang47122746.33
Carlo Zaniolo543051447.58
Ping Luo683953.92