Extracting Knowledge From On-Line Sources for Software Engineering Labor Market: A Mapping Study

Abstract

Software engineering is a continuously evolving sector and the demands of the related labor market result in a wide variety of job openings, ranging from developers to customer service positions. Thus, there is a need to continuously monitor labor market trends using data and analytics. Both employers and employees can benefit by capturing emerging trends which can facilitate continuous learning and training in new technologies, support of better matching between a job offer and the ideal candidate and expertise detection. To fulfill these needs, the results of labor market analytics need to reach the stakeholders timely and accurately. However, often delays occur, which stem from time-consuming approaches based on collecting data from traditional sources, such as questionnaires or interviews. Recently, researchers started leveraging content from digital sources, which are easily accessed and contain a wealth of information. This paper presents the results of a Systematic Mapping Study on digital sources that can be used to address the data analytics needs of the labor market. It provides a multifaceted categorization of the issues involved in the analysis of digital sources of the software engineering labor market. It aims to identify digital labor market sources for data retrieval which are appropriate for employers and employees analytics. Additionally, it aims to connect different skill types, needs and goals of labor market with the utilization of digital sources and data analysis methods. In total 86 primary studies were selected and each one was evaluated and classified aiming to identify the: (a) digital sources that are used for labor market analytics; (b) type of skills they examine; (c) methods which are used to utilize the raw digital content; (d) goals for which every primary study is conducted; (e) beneficiaries (stakeholder) of the results; and (f) time trends for all the above.

Using Data Sciences in Digital Marketing: Framework, methods, and performance metrics

“…& Metho. • • • Papoutsoglou, Ampatzoglou, Mittas, and Angelis (2019) IEEE Access Computer Sciences • • Poddar, Banerjee, and Sridhar (2019) Journal of Business Research Business • • • Roundy and Asllani (2018) Journal of Entrepreneurship, Management and Innovation Business, Economics • • • • • Ruggieri, Pedreschi, and Turini (2010) ACM Transactions on Knowledge Discovery from Data Information Sciences • • • Saleemi, Anjum, and Rehman (2017) IEEE Access Computer Sciences • • • • Salminen, Yoganathan, Corporan, Jansen, and Jung (2019) Journal of Business Research Business • • • • • Sang and Xu (2011) ACM Trans. Mult.…”

A Survey on Skill Identification From Online Job Ads

“…They evaluated the data collection methods and analysis techniques employed. Papou et al [7] provided a mapping study on knowledge extraction from online sources for the software engineering job market. They inspected the digital sources, the extracted information, the methods, stakeholders for software engineering job market analysis.…”

“…• e-CF: this is the European e-Competence Framework based on competencies. Its purpose is to provide general and comprehensive e-Competences specified at five proficiency levels that can then be adapted and customized into different contexts from the ICT business and stakeholder application perspectives 7 .…”

“…Javed et al [25] and zhao et al [27] examined the skill sections of resumes and Wikipedia categories to define and develop a taxonomy of professional skills. Malherbe et al [26] built a skill base that relied on page redirection in DBpedia, where skills were first extracted from candidate profiles found in various professional social media, and page redirections in Wikipedia were 7 https://www.ecompetences.eu/e-cf-overview/ added to these skills as aliases or alternative labels. In [28], they built a soft skill taxonomy by combining learned word embedding from a dataset of job ads and DBpedia hyperlinks.…”

What Industry Wants from Requirements Engineers in China?

“…To answer these RQs, we planed and executed a qualitative data collection and analysis process that used job ads available in job posting repositories, namely portals. As reported in the latest systematic mapping study on knowledge extraction for SE labor [14], job portals were not only the earliest used on-line sources, but remain popular in online labor market analytics. Moreover, our choice for using portals was also motivated by previous research in using this data collection approach [5,15].…”