Nowcast of TV Market using Google Trend Data

Youn, Seongwook; Cho, Hyun-chong

doi:10.5370/jeet.2016.11.1.227

Cited by 8 publications

(7 citation statements)

References 11 publications

(14 reference statements)

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“…GT data was proven to be effective in terms of modeling other areas such as marketing and information security. Youn and Cho (2016) used GT data and Autoregressive Integrated Moving Average (ARIMA) models to conduct nowcast for TV market of a few brands and was able reveal the correlation. Accurate prediction for the near future of the market was obtained.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the impact of health awareness events on Google search frequency

Hao

Liu

2019

Preventive Medicine Reports

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Over two hundred health awareness events take place in the United States in order to educate the public about various diseases. It would be informative and instructive for the organizations to know the impact of these events, although such information could be difficult to measure. We investigated whether 46 selected events attract the public attention by increasing the search frequencies of certain keywords. Internet search data from 2004 to 2017 were downloaded from Google Trend (GT). Three statistical methods including Transfer Function Noise modeling, Wilcoxon Rank Sum test, and Binomial inference were conducted. Our study showed that 10 health awareness events resulted in increased search frequencies in the event months, and 28 events did not, with the rest being classified as unclear.

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Section: Introductionmentioning

confidence: 99%

Evaluating the impact of health awareness events on Google search frequency

Hao

Liu

2019

Preventive Medicine Reports

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“…The global search engine market share of Google is 92.41% in March 2021(StatCounter 2021 ). Google is widely used by people because the search algorithm of Google is superior (Youn and Cho 2016 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Online search data represent the attention individuals pay to specific topics (Li and Law 2019 ). Previous research show that search engine query data has been used to forecast a variety of things, such as unemployment (Choi and Varian 2012 ; Suhoy 2009 ), housing (McLaren and Shanbhogue 2009 ; Wu and Brynjolfsson 2009 ), gun sales (Scott and Varian 2013 ), automobile purchases (Carriere-Swallow and Labbe 2011 ; Jun 2012 ), tourist inflow (Park et al 2017 ; Artola and Martinez Galán 2012 ), diseases (Ginsberg et al 2009 ; Althouse et al 2011 ), auto, house, retail and tourism (Choi and Varian 2009 ), feature films, video games and rank of song on the Billboard Hot 100 chart (Goel et al 2010 ), private consumption (Schmidt and Vosen 2011 ), TV market (Youn and Cho 2016 ), algorithm offer (Fang and Chen 2016 ) and more. As can be seen from the above studies, many studies started to pay attention to Internet search data in terms of forecasts.…”

Section: Literature Reviewmentioning

confidence: 99%

Can Google Trends data provide information on consumer’s perception regarding hotel brands?

Bakırtaş

Demirci

2022

Inf Technol Tourism

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Previous studies show that search engine query data is a valuable predictor for tourism demand forecasting. The goals of this study are to identify the current positions of hotels in the perception of the customer and to propose a method for practitioners to increase the visibility of consumer's mind perception of hotel brands. The study used volume of travel queries 30 hotel chains in the Turkey constructed from Google Trends and analyzed search query time series data (2014–2018). To visualize the position of brands was conducted social network analysis techniques. The results show that search engine query data regarding hotels reveal the positioning consumer’s mind of hotels. The study offers that Google Trends data is useful. In addition, the study proposes a method for practitioners. Tourism businesses could use search engine data to reveal its place in the consumer’s mind and change the consumer perception over the years.

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“…Google Trends data can be used as a measure of the likelihood of users' searches by a particular term via Google.com (Kumar et al, 2018). Youn and Cho (2016) demonstrated that their analysis on keyword search records on Google Trends (e.g. flu search versus actual flu patients) shows the positive correlation between users' search data and actual flu patient data.…”

Section: 4mentioning

confidence: 99%

The traces of ecotourism in a digital world: spatial and trend analysis of geotagged photographs on social media and Google search data for sustainable development

Kang

Nam

2020

JHTT

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Purpose This paper aims to track how ecotourism has been presented in a digital world over time using geotagged photographs and internet search data. Ecotourism photographs and Google Trends search data are used to evaluate tourist perceptions of ecotourism by developing a categorization of essential attributes, examining the relation of ecotourism and sustainable development, and measuring the popularity of the ecotourism sites. Design/methodology/approach The researchers collected geotagged photographs from Flickr.com and downloaded Google search data from Google Trends. An integrative approach of content, trend and spatial analysis was applied to develop ecotourism categories and investigate tourist perceptions of ecotourism. First, the authors investigate ecotourism geotagged photographs on a social media to comprehend tourist perceptions of ecotourism by developing a categorization of key ecotourism attributes and measuring the popularity of the ecotourism sites. Second, they examined how ecotourism has been related with sustainable development using internet search data and investigate the trends in search data. Third, spatial analysis using GIS maps was used to visualize the spatial-temporal changes of photographs and tourist views throughout the world. Findings This study identified three primary themes of ecotourism perceptions and 13 categories of ecotourism attributes. Interest over time about ecotourism was mostly presented as its definitions in Google Trends. The result indicates that tracked ecotourism locations and tourist footprints are not congruent with the popular regions of ecotourism Google search. Originality/value This research follows the changing trends in ecotourism over a decade using geotagged photographs and internet search data. The evaluation of the global ecotourism trend provides important insights for global sustainable tourism development and actual tourist perception. Analyzing the trend of ecotourism is a strategic approach to assess the achievement of UN sustainable development goals. Factual perspectives and insights into how tourists are likely to seek and perceive natural attractions are valuable for a range of audiences, such as tourism industries and governments.

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Nowcast of TV Market using Google Trend Data

Cited by 8 publications

References 11 publications

Evaluating the impact of health awareness events on Google search frequency

Evaluating the impact of health awareness events on Google search frequency

Can Google Trends data provide information on consumer’s perception regarding hotel brands?

The traces of ecotourism in a digital world: spatial and trend analysis of geotagged photographs on social media and Google search data for sustainable development

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