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Challenges for Open-domain Targeted Sentiment Analysis. (arXiv:2204.06893v1 [cs.CL])
April 15, 2022, 1:11 a.m. | Yun Luo, Hongjie Cai, Linyi Yang, Yanxia Qin, Rui Xia, Yue Zhang
cs.CL updates on arXiv.org arxiv.org
Since previous studies on open-domain targeted sentiment analysis are limited
in dataset domain variety and sentence level, we propose a novel dataset
consisting of 6,013 human-labeled data to extend the data domains in topics of
interest and document level. Furthermore, we offer a nested target annotation
schema to extract the complete sentiment information in documents, boosting the
practicality and effectiveness of open-domain targeted sentiment analysis.
Moreover, we leverage the pre-trained model BART in a sequence-to-sequence
generation method for the task. …
More from arxiv.org / cs.CL updates on arXiv.org
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