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Service Is Good, Very Good or Excellent? Towards Aspect Based Sentiment Intensity Analysis

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Advances in Information Retrieval (ECIR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13980))

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Abstract

Aspect-based sentiment analysis (ABSA) is a fast-growing research area in natural language processing (NLP) that provides more fine-grained information, considering the aspect as the fundamental item. The ABSA primarily measures sentiment towards a given aspect, but does not quantify the intensity of that sentiment. For example, intensity of positive sentiment expressed for service in service is good is comparatively weaker than in service is excellent. Thus, aspect sentiment intensity will assist the stakeholders in mining user preferences more precisely. Our current work introduces a novel task called aspect based sentiment intensity analysis (ABSIA) that facilitates research in this direction. An annotated review corpus for ABSIA is introduced by labelling the benchmark SemEval ABSA restaurant dataset with the seven (7) classes in a semi-supervised way. To demonstrate the effective usage of corpus, we cast ABSIA as a natural language generation task, where a natural sentence is generated to represent the output in order to utilize the pre-trained language models effectively. Further, we propose an effective technique for the joint learning where ABSA is used as a secondary task to assist the primary task, i.e. ABSIA. An improvement of 2 points is observed over the single task intensity model. To explain the actual decision process of the proposed framework, model explainability technique is employed that extracts the important opinion terms responsible for generation (Source code and the dataset has been made available on https://www.iitp.ac.in/~ai-nlp-ml/resources.html#ABSIA, https://github.com/20118/ABSIA)

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Notes

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Authors and Affiliations

  1. Department of Computer Science and Engineering, IIT Patna, Patna, India

    Mamta & Asif Ekbal

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  1. Mamta
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  2. Asif Ekbal
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Correspondence to Mamta .

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Editors and Affiliations

  1. University of Amsterdam, Amsterdam, The Netherlands

    Jaap Kamps

  2. Université Grenoble-Alpes, Saint-Martin-d’Hères, France

    Lorraine Goeuriot

  3. Università della Svizzera Italiana, Lugano, Switzerland

    Fabio Crestani

  4. University of Copenhagen, Copenhagen, Denmark

    Maria Maistro

  5. University of Tsukuba, Ibaraki, Japan

    Hideo Joho

  6. Dublin City University, Dublin, Ireland

    Brian Davis

  7. Dublin City University, Dublin, Ireland

    Cathal Gurrin

  8. Universität Regensburg, Regensburg, Germany

    Udo Kruschwitz

  9. Dublin City University, Dublin, Ireland

    Annalina Caputo

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Mamta, Ekbal, A. (2023). Service Is Good, Very Good or Excellent? Towards Aspect Based Sentiment Intensity Analysis. In: Kamps, J., et al. Advances in Information Retrieval. ECIR 2023. Lecture Notes in Computer Science, vol 13980. Springer, Cham. https://doi.org/10.1007/978-3-031-28244-7_43

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  • DOI: https://doi.org/10.1007/978-3-031-28244-7_43

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