TY - GEN
T1 - Enhancing Event-Level Sentiment Analysis with Structured Arguments
AU - Zhang, Qi
AU - Zhou, Jie
AU - Chen, Qin
AU - Bai, Qingchun
AU - He, Liang
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/7/7
Y1 - 2022/7/7
N2 - Previous studies about event-level sentiment analysis (SA) usually model the event as a topic, a category or target terms, while the structured arguments (e.g., subject, object, time and location) that have potential effects on the sentiment are not well studied. In this paper, we redefine the task as structured event-level SA and propose an End-to-End Event-level Sentiment Analysis (E3SA) approach to solve this issue. Specifically, we explicitly extract and model the event structure information for enhancing event-level SA. Extensive experiments demonstrate the great advantages of our proposed approach over the state-of-the-art methods. Noting the lack of the dataset, we also release a large-scale real-world dataset with event arguments and sentiment labelling for promoting more researches.
AB - Previous studies about event-level sentiment analysis (SA) usually model the event as a topic, a category or target terms, while the structured arguments (e.g., subject, object, time and location) that have potential effects on the sentiment are not well studied. In this paper, we redefine the task as structured event-level SA and propose an End-to-End Event-level Sentiment Analysis (E3SA) approach to solve this issue. Specifically, we explicitly extract and model the event structure information for enhancing event-level SA. Extensive experiments demonstrate the great advantages of our proposed approach over the state-of-the-art methods. Noting the lack of the dataset, we also release a large-scale real-world dataset with event arguments and sentiment labelling for promoting more researches.
KW - datasets
KW - event-level sentiment analysis
KW - structured
UR - https://www.scopus.com/pages/publications/85135083119
U2 - 10.1145/3477495.3531784
DO - 10.1145/3477495.3531784
M3 - 会议稿件
AN - SCOPUS:85135083119
T3 - SIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 1944
EP - 1949
BT - SIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
PB - Association for Computing Machinery, Inc
T2 - 45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2022
Y2 - 11 July 2022 through 15 July 2022
ER -