Analyzing Change on Emotion Scores of Tweets Before and After Machine Translation

Karin Fukuda, Qun Jin*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many of the texts posted on Twitter are broken sentences, and the translated sentences may not be accurate. An inaccurate translation may spoil the meaning of the original text and induce miscommunication between the poster and the reader who uses the machine translation. Since many sentences tweeted on Twitter contain emotional expressions, this study uses sentiment analysis to calculate and compare the sentiment scores of the original and translated sentences to investigate the change in sentiment before and after machine translation. As a result of using dictionaries to classify tweets before and after translation, it was found that the classification of positive sentences tended to be more likely the same before and after translation. In addition, the results of the sentiment analysis of “joy”, “like”, “relief” and “excitement” by machine learning showed that the sentiment of “joy” was particularly increased when translated from Japanese into English.

Original languageEnglish
Title of host publicationSocial Computing and Social Media
Subtitle of host publicationDesign, User Experience and Impact - 14th International Conference, SCSM 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Proceedings
EditorsGabriele Meiselwitz
PublisherSpringer Science and Business Media Deutschland GmbH
Pages294-308
Number of pages15
ISBN (Print)9783031050602
DOIs
Publication statusPublished - 2022
Event14th International Conference on Social Computing and Social Media, SCSM 2022 Held as Part of the 24th HCI International Conference, HCII 2022 - Virtual, Online
Duration: 2022 Jun 262022 Jul 1

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13315 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Social Computing and Social Media, SCSM 2022 Held as Part of the 24th HCI International Conference, HCII 2022
CityVirtual, Online
Period22/6/2622/7/1

Keywords

  • BERT
  • Emotion score
  • Machine translation
  • SNS
  • Sentiment analysis
  • Twitter

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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