Dataset Information

Appraisal of the Fairness Moral Foundation Predicts the Language Use Involving Moral Issues on Twitter Among Japanese.

ABSTRACT: Moral appraisals are found to be associated with a person's individual differences (e.g., political ideology), and the effects of individual differences on language use have been studied within the framework of the Moral Foundations Theory (MFT). However, the relationship between one's moral concern and the use of language involving morality on social media is not self-evident. The present exploratory study investigated that relationship using the MFT. Participants' tweets and self-reported responses to the questionnaire were collected to measure the degree of their appraisals according to the five foundations of the MFT. The Japanese version of the Moral Foundations Dictionary (J-MFD) was used to quantify the number of words in tweets relevant to the MFT's five moral foundations. The results showed that endorsement of the Fairness and Authority foundations predicted the word frequency in the J-MFD across all five foundations. The findings suggest that the trade-off relationship between the Fairness and Authority foundations plays a key role in online language communication. The implications and future directions to scrutinize that foundation are discussed.

SUBMITTER: Matsuo A

PROVIDER: S-EPMC8120267 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Appraisal of the Fairness Moral Foundation Predicts the Language Use Involving Moral Issues on Twitter Among Japanese.

Matsuo Akiko A Du Baofa B Sasahara Kazutoshi K

Frontiers in psychology 20210430

Moral appraisals are found to be associated with a person's individual differences (e.g., political ideology), and the effects of individual differences on language use have been studied within the framework of the Moral Foundations Theory (MFT). However, the relationship between one's moral concern and the use of language involving morality on social media is not self-evident. The present exploratory study investigated that relationship using the MFT. Participants' tweets and self-reported resp ...[more]

PMID: 33995173

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Project description:BackgroundHikikomori syndrome is a form of severe social withdrawal prevalent in Japan but is also a worldwide psychiatric issue. Twitter (subsequently rebranded X) offers valuable insights into personal experiences with mental health conditions, particularly among isolated individuals or hard-to-reach populations.ObjectiveThis study aimed to examine trends in firsthand and secondhand experiences reported on Twitter between 2021 and 2023 in the Japanese language.MethodsTweets were collected using the Twitter academic research application programming interface filtered for the following keywords: "#きこもり," "#ひきこもり," "#hikikomori," "#ニート," "#ひきこもり," "#," and "#." The Bidirectional Encoder Representations From Transformers language model was used to analyze all Japanese-language posts collected. Themes and subthemes were then inductively coded for in-depth exploration of topic clusters relevant to first- and secondhand experiences with hikikomori syndrome.ResultsWe collected 2,018,822 tweets, which were narrowed down to 379,265 (18.79%) tweets in Japanese from January 2021 to January 2023. After examining the topic clusters output by the Bidirectional Encoder Representations From Transformers model, 4 topics were determined to be relevant to the study aims. A total of 400 of the most highly interacted with tweets from these topic clusters were manually annotated for inclusion and exclusion, of which 148 (37%) tweets from 89 unique users were identified as relevant to hikikomori experiences. Of these 148 relevant tweets, 71 (48%) were identified as firsthand accounts, and 77 (52%) were identified as secondhand accounts. Within firsthand reports, the themes identified included seeking social support, personal anecdotes, debunking misconceptions, and emotional ranting. Within secondhand reports, themes included seeking social support, personal anecdotes, seeking and giving advice, and advocacy against the negative stigma of hikikomori.ConclusionsThis study provides new insights into experiences reported by web-based users regarding hikikomori syndrome specific to Japanese-speaking populations. Although not yet found in diagnostic manuals classifying mental disorders, the rise of web-based lifestyles as a consequence of the COVID-19 pandemic has increased the importance of discussions regarding hikikomori syndrome in web-based spaces. The results indicate that social media platforms may represent a web-based space for those experiencing hikikomori syndrome to engage in social interaction, advocacy against stigmatization, and participation in a community that can be maintained through a web-based barrier and minimized sense of social anxiety.

Dataset Information

Appraisal of the Fairness Moral Foundation Predicts the Language Use Involving Moral Issues on Twitter Among Japanese.

Publications

Appraisal of the Fairness Moral Foundation Predicts the Language Use Involving Moral Issues on Twitter Among Japanese.

Similar Datasets

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