BERT-based Ensembles for Modeling Disclosure and Support in Conversational Social Media Text

• URL: http://arxiv.org/abs/2006.01222v1
• Date: Mon, 1 Jun 2020 19:52:01 GMT
• Title: BERT-based Ensembles for Modeling Disclosure and Support in Conversational Social Media Text
• Authors: Tanvi Dadu, Kartikey Pant and Radhika Mamidi
• Abstract summary: We introduce a predictive ensemble model exploiting the finetuned contextualized word embeddings, RoBERTa and ALBERT. We show that our model outperforms the base models in all considered metrics, achieving an improvement of $3%$ in the F1 score.
• Score: 9.475039534437332
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: There is a growing interest in understanding how humans initiate and hold conversations. The affective understanding of conversations focuses on the problem of how speakers use emotions to react to a situation and to each other. In the CL-Aff Shared Task, the organizers released Get it #OffMyChest dataset, which contains Reddit comments from casual and confessional conversations, labeled for their disclosure and supportiveness characteristics. In this paper, we introduce a predictive ensemble model exploiting the finetuned contextualized word embeddings, RoBERTa and ALBERT. We show that our model outperforms the base models in all considered metrics, achieving an improvement of $3\%$ in the F1 score. We further conduct statistical analysis and outline deeper insights into the given dataset while providing a new characterization of impact for the dataset.

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