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Abstract Details
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Activity Number:
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311
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 8:30 AM to 10:20 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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| Abstract - #302834 |
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Title:
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A Poisson Regression Examination of the Relationship Between Website Traffic and Search Engine Queries
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Author(s):
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Heather L. R. Tierney*+ and Bing Pan
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Companies:
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College of Charleston and College of Charleston
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Address:
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Dept of Econ and Finc, Charleston, SC, 29401,
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Keywords:
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Poisson Regression ;
Search Engine ;
Google Insights ;
Aggregation ;
Normalization Effects ;
Scaling Effects
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Abstract:
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A new area of research involves the use of normalized and scaled Google search volume data to predict economic activity. This new source of data holds both many advantages as well as disadvantages. Daily and weekly data are employed to show the effect of aggregation in Google data, which can lead to contradictory findings. In this paper, Poisson regressions are used to explore the relationship between the online traffic to a specific website and the search volumes for certain keyword search queries, along with the rankings of that website for those queries. The purpose of this paper is to point out the benefits and the pitfalls of a potential new source of data that lacks transparency in regards to the original level data, which is due to the normalization and scaling procedures utilized by Google.
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