Linguistic and Contextual Analysis of SNS Posts for Approval Desire

Erina Murata, Kiichi Tago, Qun Jin*

*Corresponding author for this work

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

Abstract

In recent years, SNS has become a service that everyone uses. In this study, we analyze Twitter, one of the most popular SNSs, which allows users to post their daily events and feelings within 140 characters and is used by people all over the world. In this study, we investigate the relationship between SNS posts and latent approval needs. The linguistic features of tweets and their contextual features are analyzed using information such as the frequency of posts and the number of characters in tweets, and the degree of desire for approval is defined and quantified based on the results of the analysis of tweets. The experiment results show that the agreement between the naïve Bayes classifier and human ratings was about 60%. It is found that users with a high percentage of posts for approval desire tend to post less frequently and with a higher average number of characters. This indicates that it may be because these users post for approval desire when it is important or when they really want to say something.

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
Pages332-344
Number of pages13
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

  • Approval desire
  • Internet psychology
  • Naïve Bayes
  • SNS
  • Text mining
  • Twitter

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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