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Aspect-based opinion mining framework using heuristic patterns

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Abstract

The aspect-based online opinions expressed by users on social media sites have become a popular source of information for consumers regarding their purchase decisions as well as for companies seeking opinions on their products. Therefore, it is important to develop aspect-based opinion mining applications with an emphasis on extracting and classifying the aspect-based opinions expressed by users about products in a given review. Previous studies have used a limited set of heuristic patterns for aspect extraction with both supervised (annotated-dataset-based) and unsupervised (lexical-resource-based) aspect-related sentiment classification algorithms. However, the present study proposes an integrated framework comprising of an extended set of heuristic patterns for aspect extraction, a hybrid sentiment classification module with the additional support of intensifiers and negations, and a summary generator. The performance evaluation of the proposed aspect-based opinion mining system using state-of-the-art methods shows that the proposed system outperforms the alternative methods in terms of better precision, recall and F-measure, since it achieves an average precision of 85%, an average recall of 73% and an average F-measure of 0.78. The comparative results indicate that the proposed technique provides more efficient results for the aspect-sentiment extraction, classification and summary generation of online product reviews.

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Authors and Affiliations

  1. Institute of Computing and Information Technology, Gomal University, D.I. Khan, Pakistan

    Muhammad Zubair Asghar, Syeda Rabail Zahra & Fazal Masud Kundi

  2. Department of Computer Science, University of Science and Technology, Bannu, Pakistan

    Aurangzeb Khan

  3. Faculty of Computing and Information Technology in Rabigh (FCITR), King Abdul Aziz University (KAU), Jeddah, Saudi Arabia

    Shakeel Ahmad

Authors
  1. Muhammad Zubair Asghar
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  2. Aurangzeb Khan
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  3. Syeda Rabail Zahra
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  4. Shakeel Ahmad
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  5. Fazal Masud Kundi
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Correspondence to Muhammad Zubair Asghar.

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Asghar, M.Z., Khan, A., Zahra, S.R. et al. Aspect-based opinion mining framework using heuristic patterns. Cluster Comput 22 (Suppl 3), 7181–7199 (2019). https://doi.org/10.1007/s10586-017-1096-9

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  • DOI: https://doi.org/10.1007/s10586-017-1096-9

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