Implicit Opinion Aspect Clues in Portuguese Texts: Analysis and Categorization

Machado, Mateus Tarcinalli; Pardo, Thiago Alexandre Salgueiro; Ruiz, Evandro Eduardo Seron; Felippo, Ariani Di; Vargas, Francielle Alves

doi:10.1007/978-3-030-98305-5_7

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…To help the experts in this task, an annotation manual was built with specific guidelines for the phenomena that are typical of stock market tweets (see Di Felippo et al (2022)). This supporting material was necessary since the annotation guidance described in the UD literature did not provide strategies for the proper treatment of DANTEStocks lexical idiosyncrasies.…”

Section: Methodsmentioning

confidence: 99%

“…In Natural Language Processing (NLP), Part-of-Speech (PoS) tagging is one of the first processes applied to input data, being responsible for assigning a proper part-of-speech (or grammatical category) to each word in a text. Such basic information is useful for several NLP tasks and applications, as information extraction (CABRAL et al, 2022) (CHIARA, 2022), semantic parsing (ANCHIÊTA; PARDO, 2022) (SENO et al, 2022) and sentiment analysis (MACHADO et al, 2022), just to cite a few of very recently published state of the art research for Portuguese.…”

Section: Introductionmentioning

confidence: 99%

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The Dantestocks Corpus: An Analysis of the Distribution of Universal Dependencies-Based Part of Speech Tags

Felippo¹,

Pardo²,

Moura³

2022

Preprint

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<p>In the paper, we characterise DANTEStocks - a corpus of stock market tweets annotated with morphosyntactic information - in terms of the distribution of the PoS tags present in it. This effort provides a benchmark against which to compare other corpora and may support the investigation of the syntactic relations called dependencies, since some of them usually co-occur with specific PoS tags.</p>

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Dantestocks Corpus: An Analysis of the Distribution of Universal Dependencies-Based Part of Speech Tags

Felippo¹,

Pardo²,

Moura³

2022

Preprint

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“…Opinion mining or sentiment analysis seeks to extract the polarity of texts (e.g., positive, negative, or neutral) in an automated manner. It can be done at various levels: document, sentence, or aspect (Liu, 2012;Machado and Pardo, 2022). The document level is more general and does not always allow for the inference of exact sentiment.…”

Section: Introductionmentioning

confidence: 99%

Systematic Review on Aspect-Based SentimentAnalysis in Cross-Domain

Santin,

Rezende

2024

Preprint

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Aspect-level sentiment analysis is crucial for consumers and institutions, enabling them to monitor satisfaction regarding specific aspects of products and services through user reviews. Over time, various artificial intelligence techniques have been implemented with significant success. However, most of these techniques rely heavily on a substantial amount of labeled data. In this context, Cross-Domain Aspect-Based Sentiment Analysis (ABSA) emerges, leveraging data from source domains to enhance performance in the target domain. This systematic review contributes to this framework by outlining the primary solutions developed to tackle this challenge. It presents their data sources, compared methods, and the evolution of the main technologies adopted while identifying gaps that may inspire future research endeavors. A new classification of models is proposed here, considering the cross-domain approach. This fresh perspective aims to assist researchers in their quest for innovation, clarifying the context of their proposal and suggesting relevant comparisons with existing works.

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Implicit Opinion Aspect Clues in Portuguese Texts: Analysis and Categorization

Cited by 2 publications

References 17 publications

The Dantestocks Corpus: An Analysis of the Distribution of Universal Dependencies-Based Part of Speech Tags

The Dantestocks Corpus: An Analysis of the Distribution of Universal Dependencies-Based Part of Speech Tags

Systematic Review on Aspect-Based SentimentAnalysis in Cross-Domain

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