PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Are Emotions Conveyed Across Machine Translations? Establishing an Analytical Process for the Effectiveness of Multilingual Sentiment Analysis with Italian Text
Version 1
: Received: 10 August 2023 / Approved: 14 August 2023 / Online: 14 August 2023 (10:06:02 CEST)
How to cite:
Anderson, R.; Scala, C.; Samuel, J.; Kumar, V.; Jain, P. Are Emotions Conveyed Across Machine Translations? Establishing an Analytical Process for the Effectiveness of Multilingual Sentiment Analysis with Italian Text. Preprints2023, 2023081003. https://doi.org/10.20944/preprints202308.1003.v1
Anderson, R.; Scala, C.; Samuel, J.; Kumar, V.; Jain, P. Are Emotions Conveyed Across Machine Translations? Establishing an Analytical Process for the Effectiveness of Multilingual Sentiment Analysis with Italian Text. Preprints 2023, 2023081003. https://doi.org/10.20944/preprints202308.1003.v1
Anderson, R.; Scala, C.; Samuel, J.; Kumar, V.; Jain, P. Are Emotions Conveyed Across Machine Translations? Establishing an Analytical Process for the Effectiveness of Multilingual Sentiment Analysis with Italian Text. Preprints2023, 2023081003. https://doi.org/10.20944/preprints202308.1003.v1
APA Style
Anderson, R., Scala, C., Samuel, J., Kumar, V., & Jain, P. (2023). Are Emotions Conveyed Across Machine Translations? Establishing an Analytical Process for the Effectiveness of Multilingual Sentiment Analysis with Italian Text. Preprints. https://doi.org/10.20944/preprints202308.1003.v1
Chicago/Turabian Style
Anderson, R., Vivek Kumar and Parth Jain. 2023 "Are Emotions Conveyed Across Machine Translations? Establishing an Analytical Process for the Effectiveness of Multilingual Sentiment Analysis with Italian Text" Preprints. https://doi.org/10.20944/preprints202308.1003.v1
Abstract
Natural language processing (NLP) is being widely used globally for a variety of value-creation tasks ranging from chat-bots and machine translations to sentiment and topic analysis and multilingual large language models (LLMs). However, most of the advances are initially implemented within the English language framework, and it takes time and resources to develop comparable resources in other languages. The advances in machine translations have enabled the rapid and effective conversion of content in global languages into English and vice-versa. This creates potential opportunities to apply English language NLP methods and tools to other languages via machine translations. However, although this idea is powerful, it needs to be validated and processes and best practices need to be developed and kept updated. The present research is an effort to contribute to the development of best practices and an evaluation framework. We present a systematic and repeatable state-of-the-art process to evaluate the viability of applying English language sentiment analysis tools to Italian text by using multiple English language machine translation mechanisms such that it can be easily extended to other languages. hor[RU,RA]{\large Richard Anderson} \address[RU]{\large Rutgers University, USA} \address[RA]{\large rick.anderson@rutgers.edu} \author[RU]{\large Carmela Scala} \author[RU]{\large Jim Samuel} \author[UC]{\large Vivek Kumar} \address[UC]{\large University of Cagliari, Italy} \author[RU]{\large Parth Jain}
Keywords
natural language processing; natural language understanding; sentiment analysis; machine translation; Italian; emotion
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
