Social media as a living laboratory for researchers: the relationship between linguistics and online user responses

IF 5.9 3区 管理学 Q1 BUSINESS Internet Research Pub Date : 2023-12-15 DOI:10.1108/intr-01-2023-0064
Aulona Ulqinaku, Selma Kadić-Maglajlić, Gülen Sarial-Abi
{"title":"Social media as a living laboratory for researchers: the relationship between linguistics and online user responses","authors":"Aulona Ulqinaku, Selma Kadić-Maglajlić, Gülen Sarial-Abi","doi":"10.1108/intr-01-2023-0064","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>Today, individuals use social media to express their opinions and feelings, which offers a living laboratory to researchers in various fields, such as management, innovation, technology development, environment and marketing. It is therefore necessary to understand how the language used in user-generated content and the emotions conveyed by the content affect responses from other social media users.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>In this study, almost 700,000 posts from Twitter (as well as Facebook, Instagram and forums in the appendix) are used to test a conceptual model grounded in signaling theory to explain how the language of user-generated content on social media influences how other users respond to that communication.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>Extending developments in linguistics, this study shows that users react negatively to content that uses self-inclusive language. This study also shows how emotional content characteristics moderate this relationship. The additional information provided indicates that while most of the findings are replicated, some results differ across social media platforms, which deserves users' attention.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>This article extends research on Internet behavior and social media use by providing insights into how the relationship between self-inclusive language and emotions affects user responses to user-generated content. Furthermore, this study provides actionable guidance for researchers interested in capturing phenomena through the social media landscape.</p><!--/ Abstract__block -->","PeriodicalId":54925,"journal":{"name":"Internet Research","volume":"3 1","pages":""},"PeriodicalIF":5.9000,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet Research","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1108/intr-01-2023-0064","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose

Today, individuals use social media to express their opinions and feelings, which offers a living laboratory to researchers in various fields, such as management, innovation, technology development, environment and marketing. It is therefore necessary to understand how the language used in user-generated content and the emotions conveyed by the content affect responses from other social media users.

Design/methodology/approach

In this study, almost 700,000 posts from Twitter (as well as Facebook, Instagram and forums in the appendix) are used to test a conceptual model grounded in signaling theory to explain how the language of user-generated content on social media influences how other users respond to that communication.

Findings

Extending developments in linguistics, this study shows that users react negatively to content that uses self-inclusive language. This study also shows how emotional content characteristics moderate this relationship. The additional information provided indicates that while most of the findings are replicated, some results differ across social media platforms, which deserves users' attention.

Originality/value

This article extends research on Internet behavior and social media use by providing insights into how the relationship between self-inclusive language and emotions affects user responses to user-generated content. Furthermore, this study provides actionable guidance for researchers interested in capturing phenomena through the social media landscape.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
社交媒体作为研究人员的活实验室:语言学与在线用户反应之间的关系
如今,个人使用社交媒体来表达自己的观点和感受,这为管理、创新、技术开发、环境和营销等各个领域的研究人员提供了一个活生生的实验室。因此,有必要了解用户生成内容中使用的语言以及内容所传达的情绪如何影响其他社交媒体用户的反应。设计/方法/方法在这项研究中,来自Twitter(以及Facebook、Instagram和附录中的论坛)的近70万篇帖子被用来测试一个基于信号理论的概念模型,以解释社交媒体上用户生成内容的语言如何影响其他用户对该交流的反应。随着语言学的发展,这项研究表明,用户对使用自我包容语言的内容反应消极。本研究也显示了情绪内容特征如何调节这种关系。提供的额外信息表明,虽然大多数发现是重复的,但有些结果在社交媒体平台上有所不同,这值得用户注意。原创性/价值本文通过深入了解自我包容语言和情感之间的关系如何影响用户对用户生成内容的反应,扩展了对互联网行为和社交媒体使用的研究。此外,本研究为有兴趣通过社交媒体景观捕捉现象的研究人员提供了可操作的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Internet Research
Internet Research 工程技术-电信学
CiteScore
11.20
自引率
10.20%
发文量
85
审稿时长
>12 weeks
期刊介绍: This wide-ranging interdisciplinary journal looks at the social, ethical, economic and political implications of the internet. Recent issues have focused on online and mobile gaming, the sharing economy, and the dark side of social media.
期刊最新文献
Can digital transformation alleviate corporate fraud? Evidence from China Gameful systems for corporate sustainability: systematic review, conceptual framework and research agenda on gamification and sustainable employee behavior in companies Why do people customize avatars in the metaverse? Curiosity and SOR model perspective “I am sorry for judging you”: conceptualizing sentiment reversal among followers in case of falsely alleged social media influencer transgression Unveiling factors and contingencies influencing exhaustion in professional esports players: evidence from China
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1