This methodological guide provides a comprehensive framework for the identification, selection, and assessment of online job advertisement (OJA) sources as part of the Web Intelligence Hub (WIH) initiative. The guide introduces a structured protocol for surveying web sources, with distinct methodologies for countries for which the landscaping is done for the first time those updating a landscaping done in the past.
The guide details a multi-step approach that includes web source identification, classification, and selection. A ranking model is proposed to assess the overall level of quality and relevance of OJA sources using quantitative metrics, ensuring that selected sources provide stable, representative, and high-quality data. Additionally, the document describes the analytical techniques used to evaluate source popularity, stability, and coverage.
The methodology integrates expert validation through International Country Experts (ICEs) and employs computational techniques such as Google Trends analysis and the Analytic Hierarchy Process (AHP) to quantify categorical variables. The structured workflow contributes to ensure data quality and reliability.
This guide serves as a key reference for statisticians and researchers aiming to enhance labor market statistics with online job advertisements data.
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