Infodemiological data of high-school drop-out related web searches in Canada correlating with real-world statistical data in the period 2004-2012

The present data article describes high-school drop-out related web activities in Canada, from 2004 to 2012, obtained mining Google Trends (GT), using high-school drop-out as key-word. The searches volumes were processed, correlated and cross-correlated with statistical data obtained at national and...

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Bibliographic Details
Published in:Data in Brief
Main Authors: SIRI, ANNA, MARTINI, MARIANO, BRAGAZZI, NICOLA LUIGI, Khabbache, Hicham, Al Jafar, Ali, Brigo, Francesco
Other Authors: Siri, Anna, Martini, Mariano, Bragazzi, NICOLA LUIGI
Format: Article in Journal/Newspaper
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/11567/854777
https://doi.org/10.1016/j.dib.2016.09.032
Description
Summary:The present data article describes high-school drop-out related web activities in Canada, from 2004 to 2012, obtained mining Google Trends (GT), using high-school drop-out as key-word. The searches volumes were processed, correlated and cross-correlated with statistical data obtained at national and province level and broken down for gender. Further, an autoregressive moving-average (ARMA) model was used to model the GT-generated data. From a qualitative point of view, GT-generated relative search volumes (RSVs) reflect the decrease in drop-out rate. The peak in the Internet-related activities occurs in 2004 (56.35%, normalized value), and gradually declines to 40.59% (normalized value) in 2007. After, it remains substantially stable until 2012 (40.32%, normalized value). From a quantitative standpoint, the correlations between Canadian high-school drop-out rate and GT-generated RSVs in the study period (2004-2012) were statistically significant both using the drop-out rate for academic year and the 3-years moving average. Examining the data broken down by gender, the correlations were higher and statistically significant in males than in females. GT-based data for drop-out resulted best modeled by an ARMA(1,0) model. Considering the cross correlation of Canadian regions, all of them resulted statistically significant at lag 0, apart from for New Brunswick, Newfoundland and Labrador and the Prince Edward island. A number or cross-correlations resulted statistically significant also at lag -1 (namely, Alberta, Manitoba, New Brunswick and Saskatchewan).