arXiv Open Access 2020

Reactive Supervision: A New Method for Collecting Sarcasm Data

Boaz Shmueli Lun-Wei Ku Soumya Ray

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Abstrak

Sarcasm detection is an important task in affective computing, requiring large amounts of labeled data. We introduce reactive supervision, a novel data collection method that utilizes the dynamics of online conversations to overcome the limitations of existing data collection techniques. We use the new method to create and release a first-of-its-kind large dataset of tweets with sarcasm perspective labels and new contextual features. The dataset is expected to advance sarcasm detection research. Our method can be adapted to other affective computing domains, thus opening up new research opportunities.

Topik & Kata Kunci

cs.CL cs.SI

Penulis (3)

Boaz Shmueli

Lun-Wei Ku

Soumya Ray

Format Sitasi

APA MLA BibTeX

Shmueli, B., Ku, L., Ray, S. (2020). Reactive Supervision: A New Method for Collecting Sarcasm Data. https://arxiv.org/abs/2009.13080

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Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓