Comparative Usefulness of Naver and Google Search Information in Predictive Models for Youth Unemployment Rate in Korea
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Recently, web search query information has been applied in advanced predictive model research. Google dominates the global web search market in the Korean market; however, Naver possesses a dominant market share. Based on this characteristic, this study intends to compare the utility of the Korean web search query information of Google and Naver using predictive models. Therefore, this study develops three time-series predictive models to estimate the youth unemployment rate in Korea using the ARIMA model. Model 1 only used the youth unemployment rate in Korea, whereas Models 2 and 3 added the Korean web search query information of Naver and Google, respectively, to Model 1. Compared to the predictability of the models during the training period, Models 2 and 3 showed better fit compared with Model 1. Models 2 and 3 correlated different query information. During predictive periods 1 (continuous with the training period) and 2 (discontinuous with the training period), Model 3 showed the best performance. During predictive period 2, only Model 3 exhibited a significant prediction result. This comparative study contributes to a general understanding of the usefulness of Korean web query information using the Naver and Google search engines.
Abstract
Recently, web search query information has been applied in advanced predictive model research. Google dominates the global web search market in the Korean market; however, Naver possesses a dominant market share. Based on this characteristic, this study intends to compare the utility of the Korean web search query information of Google and Naver using predictive models. Therefore, this study develops three time-series predictive models to estimate the youth unemployment rate in Korea using the ARIMA model. Model 1 only used the youth unemployment rate in Korea, whereas Models 2 and 3 added the Korean web search query information of Naver and Google, respectively, to Model 1. Compared to the predictability of the models during the training period, Models 2 and 3 showed better fit compared with Model 1. Models 2 and 3 correlated different query information. During predictive periods 1 (continuous with the training period) and 2 (discontinuous with the training period), Model 3 showed the best performance. During predictive period 2, only Model 3 exhibited a significant prediction result. This comparative study contributes to a general understanding of the usefulness of Korean web query information using the Naver and Google search engines.
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