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arXiv · 1901.10619

Twitter Job/Employment Corpus: A Dataset of Job-Related Discourse Built with Humans in the Loop

Tong Liu·Christopher M. Homan
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Abstract

We present the Twitter Job/Employment Corpus, a collection of tweets annotated by a humans-in-the-loop supervised learning framework that integrates crowdsourcing contributions and expertise on the local community and employment environment. Previous computational studies of job-related phenomena have used corpora collected from workplace social media that are hosted internally by the employers, and so lacks independence from latent job-related coercion and the broader context that an open domain, general-purpose medium such as Twitter provides. Our new corpus promises to be a benchmark for the extraction of job-related topics and advanced analysis and modeling, and can potentially benefit a wide range of research communities in the future.

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Tong Liu, Christopher M. Homan. 2019-01-30. Twitter Job/Employment Corpus: A Dataset of Job-Related Discourse Built with Humans in the Loop. https://arxiv.org/abs/1901.10619

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