Entity-Level Sentiment Analysis (ELSA): An Exploratory Task Survey

Egil Rønningstad, Erik Velldal, Lilja Øvrelid


Abstract
This paper explores the task of identifying the overall sentiment expressed towards volitional entities (persons and organizations) in a document - what we refer to as Entity-Level Sentiment Analysis (ELSA). While identifying sentiment conveyed towards an entity is well researched for shorter texts like tweets, we find little to no research on this specific task for longer texts with multiple mentions and opinions towards the same entity. This lack of research would be understandable if ELSA can be derived from existing tasks and models. To assess this, we annotate a set of professional reviews for their overall sentiment towards each volitional entity in the text. We sample from data already annotated for document-level, sentence-level, and target-level sentiment in a multi-domain review corpus, and our results indicate that there is no single proxy task that provides this overall sentiment we seek for the entities at a satisfactory level of performance. We present a suite of experiments aiming to assess the contribution towards ELSA provided by document-, sentence-, and target-level sentiment analysis, and provide a discussion of their shortcomings. We show that sentiment in our dataset is expressed not only with an entity mention as target, but also towards targets with a sentiment-relevant relation to a volitional entity. In our data, these relations extend beyond anaphoric coreference resolution, and our findings call for further research of the topic. Finally, we also present a survey of previous relevant work.
Anthology ID:
2022.coling-1.589
Volume:
Proceedings of the 29th International Conference on Computational Linguistics
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
6773–6783
Language:
URL:
https://aclanthology.org/2022.coling-1.589
DOI:
Bibkey:
Cite (ACL):
Egil Rønningstad, Erik Velldal, and Lilja Øvrelid. 2022. Entity-Level Sentiment Analysis (ELSA): An Exploratory Task Survey. In Proceedings of the 29th International Conference on Computational Linguistics, pages 6773–6783, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
Cite (Informal):
Entity-Level Sentiment Analysis (ELSA): An Exploratory Task Survey (Rønningstad et al., COLING 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.coling-1.589.pdf
Code
 egilron/elsa-introduction
Data
NoReCNoReC_fine