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Exploring aspect-based sentiment analysis methodologies for literary-historical research purposes

Tess Dejaeghere (UGent) , Pranaydeep Singh (UGent) , Els Lefever (UGent) and Julie M. Birkholz (UGent)
(2024) Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024. In COLING ; LREC proceedings p.129-143
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Abstract
This study explores aspect-based sentiment analysis (ABSA) methodologies for literary-historical research, aiming to address the limitations of traditional sentiment analysis in understanding nuanced aspects of literature. It evaluates three ABSA toolchains: rule-based, machine learning-based (utilizing BERT and MacBERTh embeddings), and a prompt-based workflow with Mixtral 8x7B. Findings highlight challenges and potentials of ABSA for literary-historical analysis, emphasizing the need for context-aware annotation strategies and technical skills. The research contributes by curating a multilingual corpus of travelogues, publishing an annotated dataset for ABSA, creating openly available Jupyter Notebooks with Python code for each modeling approach, conducting pilot experiments on literary-historical texts, and proposing future endeavors to advance ABSA methodologies in this domain.
Keywords
aspect-based sentiment analysis, travelogues, methodology

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MLA
Dejaeghere, Tess, et al. “Exploring Aspect-Based Sentiment Analysis Methodologies for Literary-Historical Research Purposes.” Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024, edited by Rachele Sprugnoli and Marco Passarotti, ELRA, 2024, pp. 129–43.
APA
Dejaeghere, T., Singh, P., Lefever, E., & Birkholz, J. M. (2024). Exploring aspect-based sentiment analysis methodologies for literary-historical research purposes. In R. Sprugnoli & M. Passarotti (Eds.), Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024 (pp. 129–143). ELRA.
Chicago author-date
Dejaeghere, Tess, Pranaydeep Singh, Els Lefever, and Julie M. Birkholz. 2024. “Exploring Aspect-Based Sentiment Analysis Methodologies for Literary-Historical Research Purposes.” In Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024, edited by Rachele Sprugnoli and Marco Passarotti, 129–43. ELRA.
Chicago author-date (all authors)
Dejaeghere, Tess, Pranaydeep Singh, Els Lefever, and Julie M. Birkholz. 2024. “Exploring Aspect-Based Sentiment Analysis Methodologies for Literary-Historical Research Purposes.” In Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024, ed by. Rachele Sprugnoli and Marco Passarotti, 129–143. ELRA.
Vancouver
1.
Dejaeghere T, Singh P, Lefever E, Birkholz JM. Exploring aspect-based sentiment analysis methodologies for literary-historical research purposes. In: Sprugnoli R, Passarotti M, editors. Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024. ELRA; 2024. p. 129–43.
IEEE
[1]
T. Dejaeghere, P. Singh, E. Lefever, and J. M. Birkholz, “Exploring aspect-based sentiment analysis methodologies for literary-historical research purposes,” in Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024, Turin, Italy, 2024, pp. 129–143.
@inproceedings{01JDSMRRYXH1G1N4GM8A5DEBWC,
  abstract     = {{This study explores aspect-based sentiment analysis (ABSA) methodologies for literary-historical research, aiming to address the limitations of traditional sentiment analysis in understanding nuanced aspects of literature. It evaluates three ABSA toolchains: rule-based, machine learning-based (utilizing BERT and MacBERTh embeddings), and a prompt-based workflow with Mixtral 8x7B. Findings highlight challenges and potentials of ABSA for literary-historical analysis, emphasizing the need for context-aware annotation strategies and technical skills. The research contributes by curating a multilingual corpus of travelogues, publishing an annotated dataset for ABSA, creating openly available Jupyter Notebooks with Python code for each modeling approach, conducting pilot experiments on literary-historical texts, and proposing future endeavors to advance ABSA methodologies in this domain.}},
  author       = {{Dejaeghere, Tess and Singh, Pranaydeep and Lefever, Els and Birkholz, Julie M.}},
  booktitle    = {{Proceedings of the Third Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA) @ LREC-COLING-2024}},
  editor       = {{Sprugnoli, Rachele and Passarotti, Marco}},
  isbn         = {{9782493814463}},
  issn         = {{2951-2093}},
  keywords     = {{aspect-based sentiment analysis,travelogues,methodology}},
  language     = {{eng}},
  location     = {{Turin, Italy}},
  pages        = {{129--143}},
  publisher    = {{ELRA}},
  title        = {{Exploring aspect-based sentiment analysis methodologies for literary-historical research purposes}},
  url          = {{https://aclanthology.org/2024.lt4hala-1.16/}},
  year         = {{2024}},
}