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http://dx.doi.org/10.5370/JEET.2016.11.1.227

Nowcast of TV Market using Google Trend Data  

Youn, Seongwook (Dept. of Software, Korea National University of Transportation)
Cho, Hyun-chong (Division of Electrical and Electronic Engineering, Kangwon National University)
Publication Information
Journal of Electrical Engineering and Technology / v.11, no.1, 2016 , pp. 227-233 More about this Journal
Abstract
Google Trends provides weekly information on keyword search frequency on the Google search engine. Search volume patterns for the search keyword can also be analyzed based on category and by the location of those making the search. Also, Google provides “Hot searches” and “Top charts” including top and rising searches that include the search keyword. All this information is kept up to date, and allows trend comparisons by providing past weekly figures. In this study, we present a predictive model for TV markets using the searched data in Google search engine (Google Trend data). Using a predictive model for the market and analysis of the Google Trend data, we obtained an efficient and meaningful result for the TV market, and also determined highly ranked countries and cities. This method can provide very useful information for TV manufacturers and others.
Keywords
ARIMA; Google trend; Nowcast; TV;
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