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Rule-Based Approach for Party-Based Sentiment Analysis in Legal Opinion Texts

Isanka Rajapaksha, Chanika Ruchini Mudalige, Dilini Karunarathna, Nisansa de Silva, Gathika Rathnayaka, Amal Shehan Perera
2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer)

Aspect Based Sentiment Analysis (ABSA) deals with extracting aspects from a given text and then allocate each aspect a sentiment level (positive, negative or neutral) [1]. A number of researchers have addressed ABSA in different domains except for the legal domain. In this study, we explore how the concepts related to aspect-based sentiment analysis can be used in the legal domain to extract valuable information from legal opinion text. To this regard, we propose a rule based approach to perform aspect-based sentiment analysis in order to figure out the sentiment level of a sentence in relation to each legal party related to a court case (considering the legal parties as the aspects).

Keywords: Natural Language Processing | Machine Learning / Deep Learning | Law | Legal Domain | Sentiment Analysis |