Job Posts dataset

The dataset consists of 19,000 job postings that were posted through the Armenian human resource portal CareerCenter. The data was extracted from the Yahoo! mailing group https://groups.yahoo.com/neo/groups/careercenter-am. This was the only online human resource portal in the early 2000s.
A job posting usually has some structure, although some fields of the posting are not necessarily filled out by the client (poster). The data was cleaned by removing posts that were not job related or had no structure.
The data consists of job posts from 2004-2015

Content

jobpost – The original job post
date – Date it was posted in the group
Title – Job title
Company - employer
AnnouncementCode – Announcement code (some internal code, is usually missing)
Term – Full-Time, Part-time, etc
Eligibility -- Eligibility of the candidates
Audience --- Who can apply?
StartDate – Start date of work
Duration - Duration of the employment
Location – Employment location
JobDescription – Job Description
JobRequirment - Job requirements
RequiredQual -Required Qualification
Salary - Salary
ApplicationP – Application Procedure
OpeningDate – Opening date of the job announcement
Deadline – Deadline for the job announcement
Notes - Additional Notes
AboutC - About the company
Attach - Attachments
Year - Year of the announcement (derived from the field date)
Month - Month of the announcement (derived from the field date)
IT – TRUE if the job is an IT job. This variable is created by a simple search of IT job titles within column “Title”

Acknowledgements

The data collection and initial research was funded by the American University of Armenia’s research grant (2015).

Inspiration

The online job market is a good indicator of overall demand for labor in the local economy. In addition, online job postings data are easier and quicker to collect, and they can be a richer source of information than more traditional job postings, such as those found in printed newspapers.
The data can be used in the following ways:
-Understand the demand for certain professions, job titles, or industries
-Help universities with curriculum development
-Identify skills that are most frequently required by employers, and how the distribution of necessary skills changes over time
-Make recommendations to job seekers and employers

Past research

We have used association rules mining and simple text mining techniques to analyze the data. Some results can be found here (https://www.slideshare.net/HabetMadoyan/it-skills-analysis-63686238).