A message-passing multi-task architecture for the implicit event and polarity detection

Chunli Xiang, Junchi Zhang and Donghong Ji

PLOS ONE, 2021, vol. 16, issue 3, 1-14

Abstract: Implicit sentiment analysis is a challenging task because the sentiment of a text is expressed in a connotative manner. To tackle this problem, we propose to use textual events as a knowledge source to enrich network representations. To consider task interactions, we present a novel lightweight joint learning paradigm that can pass task-related messages between tasks during training iterations. This is distinct from previous methods that involve multi-task learning by simple parameter sharing. Besides, a human-annotated corpus with implicit sentiment labels and event labels is scarce, which hinders practical applications of deep neural models. Therefore, we further investigate a back-translation approach to expand training instances. Experiment results on a public benchmark demonstrate the effectiveness of both the proposed multi-task architecture and data augmentation strategy.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0247704

DOI: 10.1371/journal.pone.0247704

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