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Camera brand congruence in the Flickr social graph
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Source Web Search and Web Data Mining archive
Proceedings of the Second ACM International Conference on Web Search and Data Mining table of contents
Barcelona, Spain
SESSION: Graph mining and web content table of contents
Pages 252-261  
Year of Publication: 2009
ISBN:978-1-60558-390-7
Authors
Adish Singla  Ecole Polytechnique, Fédérale de Lausanne
Ingmar Weber  Ecole Polytechnique, Fédérale de Lausanne
Sponsors
SIGMOD: ACM Special Interest Group on Management of Data
: Google
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
: Yahoo! Research
Microsoft : Microsoft
: Nokia
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Given that my friends on Flickr use cameras of brand X, am I more likely to also use a camera of brand X? Given that one of these friends changes her brand, am I likely to do the same? These are the kind of questions addressed in this work. Direct applications involve personalized advertising in social networks.

For our study we crawled a complete connected component of the Flickr friendship graph with a total of 67M edges and 3.9M users. Camera brands and models were assigned to users and time slots according to the model specific meta data pertaining to their images taken during these time slots. Similarly, we used, where provided in a user's profile, information about a user's geographic location and the groups joined on Flickr.

Our main findings are the following. First, a pair of friends on Flickr has a significantly higher probability of being congruent, i.e., using the same brand, compared to two random users (27% vs. 19%). Second, the degree of congruence goes up for pairs of friends (i) in the same country (29%), (ii) who both only have very few friends (30%), and (iii) with a very high cliqueness (38%). Third, given that a user changes her camera model between March-May 2007 and March-May 2008, high cliqueness friends are more likely than random users to do the same (54% vs. 48%). Fourth, users using high-end cameras are far more loyal to their brand than users using point-and-shoot cameras, with a probability of staying with the same brand of 60% vs 33%, given that a new camera is bought. Fifth, these "expert" users' brand congruence reaches 66% (!) for high cliqueness friends.

To the best of our knowledge this is the first time that the phenomenon of brand congruence is studied for hundreds of thousands of users and over a period of two years.


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.

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Collaborative Colleagues:
Adish Singla: colleagues
Ingmar Weber: colleagues