2026-06-01T19:48:44Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/398092026-02-03T11:24:44Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Moreno-Ortiz, Antonio Jesús
author
García Gámez, María
2025-09-09T12:02:54Z
2025-09-09T12:02:54Z
2025-07-08
Moreno-Ortiz, A., García-Gámez, M. Corpus Annotation of Functional Discourse Units for Aspect-Based Sentiment Analysis. Corpus Pragmatics (2025). https://doi.org/10.1007/s41701-025-00199-0
https://hdl.handle.net/10630/39809
10.1007/s41701-025-00199-0
Aspect-based sentiment analysis (ABSA) aims to identify the sentiment associated
with specifc aspects or entities in a text. In order to facilitate the development and
evaluation of ABSA systems, it is crucial to have annotated datasets that contain
information about the aspects, entities, and the sentiments expressed towards them.
However, the amount of information in existing datasets (for example those used in
the SemEval shared tasks) is very limited. We innovate on existing corpora by introducing a multi-layered annotation schema that includes not only entities and aspects,
but also lexical items and, crucially, functional discourse units (FDUs). These FDUs
are text segments (typically sentences or clauses) that play a specifc role or function
within the overall text, such as “description”, “evaluation”, or “advice”, a type of
information which we believe can be of great help in ABSA. Our corpus focuses on
user reviews of tourist attractions (specifcally monuments) in the region of Andalusia (Spain), but the same schema can be used to annotate reviews of other domains
simply by adapting the aspects layer, which is domain-dependent. The annotation
schema is described, and the validation process is carried out on a sample of 400
reviews from this domain. Results show a substantial level of agreement among the
annotators, indicating that the schema is reliable and consistent. We go on to illustrate and discuss some difcult cases where annotation showed discrepancy among
annotators. The annotation of FDUs in the corpus is a signifcant advancement for
aspect-based sentiment analysis.
eng
Atribución 4.0 Internacional
Lingüística aplicada
Corpus lingüístico - Proceso de datos
Corpus annotation of functional discourse units for aspect‑based sentiment analysis
journal article
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