Abstract
To gain insights into labor demands or supply, researchers and policymakers have traditionally relied on interviews, trade publications, surveys, and vacancies. Although such traditional data sources have some clear advantages, they are also characterized by limitations that can be addressed by using web-based data available in abundance.
The scope of this workshop includes the vision of an open 'job knowledge base' that can be used by employers, employees, job seekers, labor market experts and policy makers. Such a knowledge base could contain different types of information such as responsibilities and roles, required competences, that could be used to develop trainings and identify priorities, wage information, geographical and demographic trends, cultural issues, demands of the job markets in different domains, job announcement information and rates, job popularity and other useful labor market dynamics. This workshop aims at identifying the challenges for job knowledge discovery, and proposing solutions to overcome these challenges. Due to the compelling human factors that play a vital role in decision-making processes related to job search, job satisfaction, etc. we are particularly interested in inter-disciplinary approaches that can support job knowledge discovery.
The scope of this workshop includes the vision of an open 'job knowledge base' that can be used by employers, employees, job seekers, labor market experts and policy makers. Such a knowledge base could contain different types of information such as responsibilities and roles, required competences, that could be used to develop trainings and identify priorities, wage information, geographical and demographic trends, cultural issues, demands of the job markets in different domains, job announcement information and rates, job popularity and other useful labor market dynamics. This workshop aims at identifying the challenges for job knowledge discovery, and proposing solutions to overcome these challenges. Due to the compelling human factors that play a vital role in decision-making processes related to job search, job satisfaction, etc. we are particularly interested in inter-disciplinary approaches that can support job knowledge discovery.
Original language | English |
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Title of host publication | HT '19. Proceedings of the 30th ACM Conference on Hypertext and Social Media |
Editors | Claus Atzenbeck, Jessica Rubart, David E. Millard |
Number of pages | 2 |
Place of Publication | New York, NY |
Publisher | Association for Computing Machinery |
Publication date | 2019 |
Pages | 305-306 |
ISBN (Print) | 9781450368858 |
DOIs | |
Publication status | Published - 2019 |
Event | 30th ACM Conference on Hypertext and Social Media. HT '19 - Hof University of Applied Sciences, Hof, Germany Duration: 17 Sept 2019 → 20 Sept 2019 Conference number: 30 https://human.iisys.de/ht2019/ |
Conference
Conference | 30th ACM Conference on Hypertext and Social Media. HT '19 |
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Number | 30 |
Location | Hof University of Applied Sciences |
Country/Territory | Germany |
City | Hof |
Period | 17/09/2019 → 20/09/2019 |
Internet address |
Keywords
- Job knowledge
- Web data
- Social media
- Employers
- Job search
- Job posting
- Labor market