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Article

Real-Time Sentiment Analysis for Polish Dialog Systems Using MT as Pivot

Polish-Japanese Academy of Information Technology, 02-008 Warsaw, Poland
Academic Editors: Diego Reforgiato Recupero, Harald Sack and Danilo Dessì
Electronics 2021, 10(15), 1813; https://doi.org/10.3390/electronics10151813
Received: 9 June 2021 / Revised: 25 July 2021 / Accepted: 26 July 2021 / Published: 28 July 2021
(This article belongs to the Special Issue Deep Learning and Explainability for Sentiment Analysis)
We live in a time when dialogue systems are becoming a very popular tool. It is estimated that in 2021 more than 80% of communication with customers on the first line of service will be based on chatbots. They enter not only the retail market but also various other industries, e.g., they are used for medical interviews, information gathering or preliminary assessment and classification of problems. Unfortunately, when these work incorrectly it leads to dissatisfaction. Such systems have the possibility of contacting a human consultant with a special command, but this is not the point. The dialog system should provide a good, uninterrupted and fluid experience and not show that it is an artificial creation. Analysing the sentiment of the entire dialogue in real time can provide a solution to this problem. In our study, we focus on studying the methods of analysing the sentiment of dialogues based on machine learning for the English language and the morphologically complex Polish language, which also represents a language with a small amount of training resources. We analyse the methods directly and use the machine translator as an intermediary, thus checking the quality changes between models based on limited resources and those based on much larger English but machine translated texts. We manage to obtain over 89% accuracy using BERT-based models. We make recommendations in this regard, also taking into account the cost aspect of implementing and maintaining such a system. View Full-Text
Keywords: sentiment analysis; polish sentiment; machine learning; machine translation; dialog systems; dialog sentiment; sentiment based user satisfaction sentiment analysis; polish sentiment; machine learning; machine translation; dialog systems; dialog sentiment; sentiment based user satisfaction
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MDPI and ACS Style

Wołk, K. Real-Time Sentiment Analysis for Polish Dialog Systems Using MT as Pivot. Electronics 2021, 10, 1813. https://doi.org/10.3390/electronics10151813

AMA Style

Wołk K. Real-Time Sentiment Analysis for Polish Dialog Systems Using MT as Pivot. Electronics. 2021; 10(15):1813. https://doi.org/10.3390/electronics10151813

Chicago/Turabian Style

Wołk, Krzysztof. 2021. "Real-Time Sentiment Analysis for Polish Dialog Systems Using MT as Pivot" Electronics 10, no. 15: 1813. https://doi.org/10.3390/electronics10151813

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