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Root Cause Analysis Based on Relations Among Sentiment Words

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Abstract

Sentiment analysis is a useful method to extract user preferences from product reviews; however, it cannot explain the detailed reasons for user preferences because of the exclusion of neutral sentiment words, constituting a large proportion of the words used in reviews. In contrast, there are limitations to using root cause analysis to analyze sentiment relations using sentiment words extracted from user preferences. This research aimed to extract a more fine-grained root cause by proposing a novel method capable of analyzing the root cause based on the relations between sentiment words. To identify the root causes of negative opinions in aspect-level sentiment analysis, we analyze the hierarchical and causal relations between sentiment triples and utilize hierarchical clustering based on sentiment triples’ relation to compensate for general sentiment words. The experimental results showed that the proposed method was 6.4% and 5.1% more accurate than the existing aspect-level analysis for the mobile device and clothing domains, respectively. Finally, we discussed some issues associated with the proposed method using a qualitative evaluation. In this study, a novel root cause identification method that can utilize the hierarchical and causal relations between sentiment words using negative and neutral sentiment expressions of product reviews is proposed.

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Funding

This work was supported by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2019-0-00231, Development of artificial intelligence based video security technology and systems for public infrastructure safety).

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Authors and Affiliations

  1. Dept. of Computer Science and Engineering, Korea University, 145 anam-ro seonguk-gu, 02841, Seoul, South Korea

    Sang-Min Park

  2. Dept. of Computer and Information Security, Convergence Engineering for Intelligent Drone, Sejong University, 209 Neungdong-ro, Gwangjin-gu, 05006, Seoul, South Korea

    Young-Gab Kim

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  1. Sang-Min Park
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  2. Young-Gab Kim
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Correspondence to Young-Gab Kim.

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Park, SM., Kim, YG. Root Cause Analysis Based on Relations Among Sentiment Words. Cogn Comput 13, 903–918 (2021). https://doi.org/10.1007/s12559-021-09872-3

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  • DOI: https://doi.org/10.1007/s12559-021-09872-3

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