Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/141370
Author(s): Brazdil, Pavel
Silvano, Maria da Purificação
Silva, Maria de Fátima Henriques da
Muhammad, Shamsuddeen
Oliveira, Fátima
Cordeiro, João
Leal, António
Title: Extending general sentiment lexicon to specific domains in (semi-)automatic manner
Issue Date: 2022
Abstract: This paper describes an approach to the construction of a sentiment analysis system that uses both automatic and manual processes. The system includes a domain-specific sentiment lexicon, modifier patterns and rules that are used to derive the sentiment values of sentences in new texts. The lexicon that includes single words (unigrams) is obtained in an automatic manner from the distribution of ratings for all words in the labelled training data. The sentiment values of phrases is derived from a list of modifier patterns, built/developed manually. These include a modifier and a focal element. The modifiers can be of different types, depending on whether the operation is intensification, downtoning or reversal. This approach was applied to texts on economics and finance in European Portuguese. In our view, this line of work deserves more attention in the community, as the system not only has reasonable performance, but also can provide understandable explanations to the user.
Subject: Ciências da linguagem
language sciences
URI: https://hdl.handle.net/10216/141370
Source: 1st Workshop on Sentiment Analysis & Linguistic Linked Data: Proceedings of the Workshops and Tutorials held at LDK 2021 co-located with the 3rd Language, Data and Knowledge Conference (LDK 2021)
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
Appears in Collections:FEP - Artigo em Livro de Atas de Conferência Internacional
FLUP - Artigo em Livro de Atas de Conferência Internacional

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