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The predictive power of online chatter
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Source International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining table of contents
Chicago, Illinois, USA
SESSION: Research track paper table of contents
Pages: 78 - 87  
Year of Publication: 2005
ISBN:1-59593-135-X
Authors
Daniel Gruhl  IBM Almaden Research Center, San Jose, CA
R. Guha  Google, Inc, Mountain View, CA
Ravi Kumar  IBM Almaden Research Center, San Jose, CA
Jasmine Novak  IBM Almaden Research Center, San Jose, CA
Andrew Tomkins  IBM Almaden Research Center, San Jose, CA
Sponsors
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
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ABSTRACT

An increasing fraction of the global discourse is migrating online in the form of blogs, bulletin boards, web pages, wikis, editorials, and a dizzying array of new collaborative technologies. The migration has now proceeded to the point that topics reflecting certain individual products are sufficiently popular to allow targeted online tracking of the ebb and flow of chatter around these topics. Based on an analysis of around half a million sales rank values for 2,340 books over a period of four months, and correlating postings in blogs, media, and web pages, we are able to draw several interesting conclusions.First, carefully hand-crafted queries produce matching postings whose volume predicts sales ranks. Second, these queries can be automatically generated in many cases. And third, even though sales rank motion might be difficult to predict in general, algorithmic predictors can use online postings to successfully predict spikes in sales rank.


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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CITED BY  17

Collaborative Colleagues:
Daniel Gruhl: colleagues
R. Guha: colleagues
Ravi Kumar: colleagues
Jasmine Novak: colleagues
Andrew Tomkins: colleagues