<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The global diffusion of Internet involves economic, political and demographic factors that can predict in real time. In this article, we demonstrate that according to data provided by EUROSTAT, the number of people looking for a job in Romania it is correlated with specific query terms using Google Trends. Search engine data is used to “predict the present” values of different economic indicators. The obtained results are compared with the classical method of developing the economic indicators, with official EUROSTAT employment data. In this paper, we demonstrate that the new methods to extract the economic indicators from web technologies are accurate.</p></abstract>

The global diffusion of Internet involves economic, political and demographic factors that can predict in real time. In this article, we demonstrate that according to data provided by EUROSTAT, the number of people looking for a job in Romania it is correlated with specific query terms using Google Trends. Search engine data is used to “predict the present” values of different economic indicators. The obtained results are compared with the classical method of developing the economic indicators, with official EUROSTAT employment data. In this paper, we demonstrate that the new methods to extract the economic indicators from web technologies are accurate.

Modelling prediction of unemployment statistics using web technologies

HOLISTICA – Journal of Business and Public Administration

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Modelling prediction of unemployment statistics using web technologies"}

The global diffusion of Internet involves economic, political and demographic factors that can predict in real time. In this article, we demonstrate that...

Modelling prediction of unemployment statistics using web technologies

Data publikacji: 24 sty 2018

Zakres stron: 55 - 60

DOI: https://doi.org/10.1515/hjbpa-2017-0023

Słowa kluczowe
Data Mining, Big Data, Demography, Unemployment, Job Search

© 2017 Mioara Popescu, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Modelling prediction of unemployment statistics using web technologies

Data publikacji: 24 sty 2018

Zakres stron: 55 - 60

DOI: https://doi.org/10.1515/hjbpa-2017-0023

Słowa kluczoweData Mining, Big Data, Demography, Unemployment, Job Search

© 2017 Mioara Popescu, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
Data Mining, Big Data, Demography, Unemployment, Job Search