Annotated Tweets from Occupations in Natural sciences, geography and informatics

Background

The skills and qualifications of IT professionals are constantly changing and under discussion. In particular, we see the impact of emerging technologies and tools, such as AI, on the labor market and their reflection in the broader scientific community, media and everyday life. However, in order to uncover the complex dynamics surrounding vocational education, we need to take a closer look at the labor demand as well as the public perception and valuation of professionals. Therefore, we present a novel approach to work with social media data, in particular Twitter/X data. We have collected a large dataset of job-related X data (2007-2023) but see that a word list-based searching strategy is not enough. Most tweets are actually job offers, and this dataset contains manually annotated data to categorize tweets accordingly.

Data

This dataset contains mainly German tweets (2007-2023) related to occupations in Natural sciences, geography and informatics.

Tweets.id
Tweet ID

job_id
Occupation identifier (KldB)

Category
Annotated category (0 - not annotated, 1 - not related to occupations, 2 - information about occupations, 3 - people associated with a particular occupation, 4 - educational aspects, 5 - job offers) 

Contact

Please contact us if you have questions or want to use this dataset.