利用监督机器学习研究社交媒体上的战略多样性交流:开发、验证和未来研究方向

IF 4.1 3区 管理学 Q2 BUSINESS Public Relations Review Pub Date : 2024-02-10 DOI:10.1016/j.pubrev.2024.102431
Joep Hofhuis , João Gonçalves , Pytrik Schafraad , Biyao Wu
{"title":"利用监督机器学习研究社交媒体上的战略多样性交流:开发、验证和未来研究方向","authors":"Joep Hofhuis ,&nbsp;João Gonçalves ,&nbsp;Pytrik Schafraad ,&nbsp;Biyao Wu","doi":"10.1016/j.pubrev.2024.102431","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, we present a digital tool named <em>Diversity Perspectives in Social Media</em> (DivPSM) which conducts automated content analysis of strategic diversity communication in organizational social media posts, using supervised machine-learning. DivPSM is trained to identify whether a post makes mention of diversity or a diversity-related issue, and to subsequently code for the presence of three diversity dimensions (cultural/ethnic/racial, gender, and LHGBTQ+ diversity) and three diversity perspectives (the moral, market, and innovation perspectives). In Study 1, we describe the training and validation of the instrument, and examine how it performs compared to human coders. Our findings confirm that DivPSM is sufficiently reliable for use in future research. In study 2, we illustrate the type of data that DivPSM generates, by analyzing the prevalence of strategic diversity communication in social media posts (<em>n</em> = 84,561) of large organizations in the Netherlands. Our results show that in this context gender diversity is most prevalent, followed by LHGBTQ+ and cultural/ethnic/racial diversity. Furthermore, gender diversity is often associated with the innovation perspective, whereas LHGBTQ+ diversity is more often associated with the moral perspective. Cultural/ethnic/racial diversity does not show strong associations with any of the perspectives. Theoretical implications and directions for future research are discussed at the end of the paper.</p></div>","PeriodicalId":48263,"journal":{"name":"Public Relations Review","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0363811124000109/pdfft?md5=8db86f796719a420acecfa9ceca0512c&pid=1-s2.0-S0363811124000109-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Examining strategic diversity communication on social media using supervised machine learning: Development, validation and future research directions\",\"authors\":\"Joep Hofhuis ,&nbsp;João Gonçalves ,&nbsp;Pytrik Schafraad ,&nbsp;Biyao Wu\",\"doi\":\"10.1016/j.pubrev.2024.102431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this paper, we present a digital tool named <em>Diversity Perspectives in Social Media</em> (DivPSM) which conducts automated content analysis of strategic diversity communication in organizational social media posts, using supervised machine-learning. DivPSM is trained to identify whether a post makes mention of diversity or a diversity-related issue, and to subsequently code for the presence of three diversity dimensions (cultural/ethnic/racial, gender, and LHGBTQ+ diversity) and three diversity perspectives (the moral, market, and innovation perspectives). In Study 1, we describe the training and validation of the instrument, and examine how it performs compared to human coders. Our findings confirm that DivPSM is sufficiently reliable for use in future research. In study 2, we illustrate the type of data that DivPSM generates, by analyzing the prevalence of strategic diversity communication in social media posts (<em>n</em> = 84,561) of large organizations in the Netherlands. Our results show that in this context gender diversity is most prevalent, followed by LHGBTQ+ and cultural/ethnic/racial diversity. Furthermore, gender diversity is often associated with the innovation perspective, whereas LHGBTQ+ diversity is more often associated with the moral perspective. Cultural/ethnic/racial diversity does not show strong associations with any of the perspectives. Theoretical implications and directions for future research are discussed at the end of the paper.</p></div>\",\"PeriodicalId\":48263,\"journal\":{\"name\":\"Public Relations Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-02-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0363811124000109/pdfft?md5=8db86f796719a420acecfa9ceca0512c&pid=1-s2.0-S0363811124000109-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Public Relations Review\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0363811124000109\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Public Relations Review","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0363811124000109","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0

摘要

在本文中,我们介绍了一种名为 "社交媒体中的多样性视角"(DivPSM)的数字工具,该工具利用监督机器学习对组织社交媒体帖子中的战略性多样性交流进行自动内容分析。通过对 DivPSM 的训练,可以识别帖子中是否提到了多样性或与多样性相关的问题,然后对三个多样性维度(文化/民族/种族、性别和 LHGBTQ+ 多样性)和三种多样性视角(道德、市场和创新视角)的存在进行编码。在研究 1 中,我们介绍了该工具的培训和验证情况,并考察了它与人工编码员相比的表现。我们的研究结果证实,DivPSM 具有足够的可靠性,可用于未来的研究。在研究 2 中,我们通过分析荷兰大型组织的社交媒体帖子(n = 84,561)中战略多样性交流的普遍性,说明了 DivPSM 生成的数据类型。我们的结果表明,在这种情况下,性别多样性最为普遍,其次是 LHGBTQ+ 和文化/民族/种族多样性。此外,性别多样性通常与创新视角相关,而 LHGBTQ+ 多样性则更多地与道德视角相关。文化/民族/种族多样性与任何一种视角都没有很强的关联。本文最后讨论了理论意义和未来研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Examining strategic diversity communication on social media using supervised machine learning: Development, validation and future research directions

In this paper, we present a digital tool named Diversity Perspectives in Social Media (DivPSM) which conducts automated content analysis of strategic diversity communication in organizational social media posts, using supervised machine-learning. DivPSM is trained to identify whether a post makes mention of diversity or a diversity-related issue, and to subsequently code for the presence of three diversity dimensions (cultural/ethnic/racial, gender, and LHGBTQ+ diversity) and three diversity perspectives (the moral, market, and innovation perspectives). In Study 1, we describe the training and validation of the instrument, and examine how it performs compared to human coders. Our findings confirm that DivPSM is sufficiently reliable for use in future research. In study 2, we illustrate the type of data that DivPSM generates, by analyzing the prevalence of strategic diversity communication in social media posts (n = 84,561) of large organizations in the Netherlands. Our results show that in this context gender diversity is most prevalent, followed by LHGBTQ+ and cultural/ethnic/racial diversity. Furthermore, gender diversity is often associated with the innovation perspective, whereas LHGBTQ+ diversity is more often associated with the moral perspective. Cultural/ethnic/racial diversity does not show strong associations with any of the perspectives. Theoretical implications and directions for future research are discussed at the end of the paper.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
8.00
自引率
19.00%
发文量
90
期刊介绍: The Public Relations Review is the oldest journal devoted to articles that examine public relations in depth, and commentaries by specialists in the field. Most of the articles are based on empirical research undertaken by professionals and academics in the field. In addition to research articles and commentaries, The Review publishes invited research in brief, and book reviews in the fields of public relations, mass communications, organizational communications, public opinion formations, social science research and evaluation, marketing, management and public policy formation.
期刊最新文献
Artificial intelligence for internal communication: Strategies, challenges, and implications Communicating strategic CEO activism to promote employee prosocial behaviors: Understanding the mediating role of employee prosocial sensemaking Optimizing organizational corrective communication: The effects of correction placement timing, refutation detail level, and corrective narrative type on combating crisis misinformation narratives “If it can be done, it will be done:” AI Ethical Standards and a dual role for public relations Streaming disasters on TikTok: Examining social mediated crisis communication, public engagement, and emotional responses during the 2023 Maui wildfire
×
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