A poisson regression examination of the relationship between website traffic and search engine queries

Heather L.R. Tierney, Bing Pan

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

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 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 raw data, which is due to the normalization and scaling procedures utilized by Google.

Original languageEnglish (US)
Pages (from-to)155-189
Number of pages35
JournalNETNOMICS: Economic Research and Electronic Networking
Volume13
Issue number3
DOIs
StatePublished - Dec 1 2012

Fingerprint

Search engines
Websites
Transparency
Agglomeration
Economics
Poisson regression
Google
Web sites
Search engine
Query

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Economics and Econometrics
  • Computer Networks and Communications

Cite this

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A poisson regression examination of the relationship between website traffic and search engine queries. / Tierney, Heather L.R.; Pan, Bing.

In: NETNOMICS: Economic Research and Electronic Networking, Vol. 13, No. 3, 01.12.2012, p. 155-189.

Research output: Contribution to journalArticle

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