![]() ![]() Since entities refer to the semantics, they are independent from which terms are used to refer to them (i.e. Terms refer to the text or keywords included in the search box.Īn entity is an abstraction to refer to a single semantic unit, such as a place, a person, an object, an event, or a concept. The searches whose popularity is reported by GT may be specified as terms, entities or categories. ![]() Reports, which include time-series data, are available for any user-selected time period, from 2004 to the present day and can also be restricted to focus on searches done in a certain language or from a specific location. Google Trends is a freely available tool developed by Google that provides reports with the popularity of searches in Google Search. Our analysis detects that GT data have some non-negligible quality issues, which are evidenced in an illustrative example. ![]() This paper addresses this gap by discussing the data quality aspects of GT following the framework proposed by Karr, Sanil, and Banks ( Citation2006). However, its quality as a data source has not been assessed. It is also widely applied in other applied economics topics, ranging from unemployment to tourism demand (Choi and Varian Citation2012 Jun, Yoo, and Choi Citation2018). It has demonstrated to be a good proxy for investor’s attention (Da, Engelberg, and Gao Citation2011), even during the COVID-19 outbreak (Shear, Ashraf, and Sadaqat Citation2021 Costola, Iacopini, and Santagiustina Citation2021). Among the non-traditional data sources, GT is one of the most widely used in the empirical economic literature. Google Trends (GT) is a tool that provides reports on the popularity of certain searches in the Google search engine. Issues with data quality, such as high measurement error, may impact on model parameter estimates and create economic inefficiencies (Bound, Brown, and Mathiowetz Citation2001). Data quality is a multi-dimensional concept which refers to the capability of data to be used quickly and effectively to inform and evaluate decisions. Citation2009) or politics (Mellon Citation2014) to finance (Preis, Moat, and Stanley Citation2013).ĭespite its increasing use in the literature, the quality of these non-traditional data sources has been largely overlooked. Such online data include sources such as social networking sites, corporate websites, and search engines, which have been used in a wide variety of research topics ranging from medicine (Pelat et al. The rise in popularity of digital media has brought an enormous growth in the number of data sources related to the digital footprint left by businesses and consumers (Blazquez and Domenech Citation2018). ![]()
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