Hofmarcher, Paul, Grün, Bettina, Hornik, Kurt, Mair, Patrick. 2013. Determining the similarity between US cities using a gravity model for search engine query data.. In: Algorithms from and for Nature and Life - Studies in Classification, Data Analysis, and Knowledge Organization,, Hrsg. Berthold Lausen, Dirk Van den Poel, Alfred Ultsch, 243-250. Wien: Springer.

RIS

@INBOOK{Hofmarcher2013,
title = {Determining the similarity between US cities using a gravity model for search engine query data.},
author = {Paul Hofmarcher and Bettina Grün and Kurt Hornik and Patrick Mair},
publisher = {Springer},
year = {2013},
address = {Wien},
url = {http://www.springerprofessional.de/024---determining-the-similarity-between-us-cities-using-a-gravity-model-for-search-engine-query-data/4647580.html},
publisher = {Springer},
language = {EN},
pages = {243-250},
series = {Algorithms from and for Nature and Life - Studies in Classification, Data Analysis, and Knowledge Organization,},
abstract = {In this paper we use the gravity model to estimate the similarity of US cities based on data provided by Google Trends (GT). GT allows to look up search terms and to obtain ranked lists of US cities according to the relative frequencies of requests for each term. The occurences of the US cities on these ranked lists are used to determine the similarities with the gravity model. As search terms for GT serve dictionaries derived from the General Inquirer (GI), containing the categories Economy and Politics/Legal. The estimated similarity scores are visualized with multidimensional scaling (MDS).},
}