Google Trends for Data Mining. Study of Czech Towns View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Jiří Horák , Igor Ivan , Pavel Kukuliač , Tomáš Inspektor , Branislav Devečka , Markéta Návratová

ABSTRACT

Selected web search engines provide statistics of user activities according to the topics, time and locations. The utilization requires well prepared phrases and searching range. The system of etalons for calibration searching frequencies provided by Google Trends is proposed. It was applied for evaluation of searching names of Czech towns. The regression analysis proved high correlation with population. Highlighted anomalies were explored. K-means cluster analysis enabled a categorization of selected towns. The geographical network analysis of relationships among towns suffers from low quality of locations provided by Google. The discussion includes an overview of main pros and cons of Google Trends and provides recommendations. More... »

PAGES

100-109

References to SciGraph publications

Book

TITLE

Computational Collective Intelligence. Technologies and Applications

ISBN

978-3-642-40494-8
978-3-642-40495-5

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-40495-5_11

DOI

http://dx.doi.org/10.1007/978-3-642-40495-5_11

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1039010201


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