Twitter消息能帮助企业减轻道德丑闻的影响吗?我们对92个“违规者”丑闻前的推文进行了主题模型研究

IF 3.1 Q2 BUSINESS Society and Business Review Pub Date : 2021-01-20 DOI:10.1108/SBR-10-2020-0122
Shivani Raheja, M. Chipulu
{"title":"Twitter消息能帮助企业减轻道德丑闻的影响吗?我们对92个“违规者”丑闻前的推文进行了主题模型研究","authors":"Shivani Raheja, M. Chipulu","doi":"10.1108/SBR-10-2020-0122","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis paper aims to examine whether Twitter messaging can help mitigate the harm corporations suffer in the aftermath of ethical scandals.\n\n\nDesign/methodology/approach\nThis paper applies Web Application Programming Interfaces (API) on the Guardian and New York Times news archives to find corporations that suffered scandals between 2014 and 2019, revealing 92 publicly listed companies in the UK. Using Twitter API and the Python library, Getoldtweets, this paper extracts historical, pre-scandal – i.e. pre-2014 – tweets of the 92 firms. The paper topic-models the tweets data using Latent Dirichlet Allocation (LDA). This paper then subjects the topics to multidimensional scaling (MDS) to examine commonalities among them.\n\n\nFindings\nLDA reveals 10 topics, which group under 5 themes; these are product marketing, urgent signalling of “greenness”, customer relationship management, corporate strategy and news feeds. MDS suggests that the topics further congregate into two meta-themes of future-oriented versus immediate and individual versus global.\n\n\nPractical implications\nProvided they are sincere and legitimate, corporations’ tweets on global issues with a green agenda should help cushion the impact of ethical scandals. Overall, however, the findings suggest that Twitter messaging could be a double-edged sword, and underscore the importance of strategy.\n\n\nOriginality/value\nThe paper offers a first exploration of the relevance of corporate Twitter messaging in mitigating ethical scandals.\n","PeriodicalId":44608,"journal":{"name":"Society and Business Review","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Can Twitter messaging help corporations mitigate the impact of ethical scandals? We topic-model pre-scandal tweets of 92 ‘offenders’ to investigate\",\"authors\":\"Shivani Raheja, M. Chipulu\",\"doi\":\"10.1108/SBR-10-2020-0122\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThis paper aims to examine whether Twitter messaging can help mitigate the harm corporations suffer in the aftermath of ethical scandals.\\n\\n\\nDesign/methodology/approach\\nThis paper applies Web Application Programming Interfaces (API) on the Guardian and New York Times news archives to find corporations that suffered scandals between 2014 and 2019, revealing 92 publicly listed companies in the UK. Using Twitter API and the Python library, Getoldtweets, this paper extracts historical, pre-scandal – i.e. pre-2014 – tweets of the 92 firms. The paper topic-models the tweets data using Latent Dirichlet Allocation (LDA). This paper then subjects the topics to multidimensional scaling (MDS) to examine commonalities among them.\\n\\n\\nFindings\\nLDA reveals 10 topics, which group under 5 themes; these are product marketing, urgent signalling of “greenness”, customer relationship management, corporate strategy and news feeds. MDS suggests that the topics further congregate into two meta-themes of future-oriented versus immediate and individual versus global.\\n\\n\\nPractical implications\\nProvided they are sincere and legitimate, corporations’ tweets on global issues with a green agenda should help cushion the impact of ethical scandals. Overall, however, the findings suggest that Twitter messaging could be a double-edged sword, and underscore the importance of strategy.\\n\\n\\nOriginality/value\\nThe paper offers a first exploration of the relevance of corporate Twitter messaging in mitigating ethical scandals.\\n\",\"PeriodicalId\":44608,\"journal\":{\"name\":\"Society and Business Review\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2021-01-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Society and Business Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/SBR-10-2020-0122\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Society and Business Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/SBR-10-2020-0122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 3

摘要

目的本文旨在研究推特信息是否有助于减轻企业在道德丑闻后所遭受的伤害。设计/方法论/方法本文在《卫报》和《纽约时报》的新闻档案中应用Web应用程序编程接口(API)来寻找2014年至2019年间遭受丑闻的公司,揭示了英国92家上市公司,丑闻之前,即2014年之前,92家公司的推特。本文使用潜在狄利克雷分配(LDA)对推特数据进行建模。然后,本文对这些主题进行多维标度(MDS),以检验它们之间的共性。FindingsLDA揭示了10个主题,分为5个主题;这些是产品营销、“绿色”的紧急信号、客户关系管理、企业战略和新闻提要。MDS认为,这些主题进一步聚集成两个元主题,即面向未来与即时以及个人与全球。实际含义如果企业在全球问题上发布的带有绿色议程的推文是真诚和合法的,应该有助于缓解道德丑闻的影响。然而,总的来说,研究结果表明,推特消息可能是一把双刃剑,并强调了战略的重要性。原创性/价值该论文首次探讨了企业推特信息在缓解道德丑闻方面的相关性。
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
Can Twitter messaging help corporations mitigate the impact of ethical scandals? We topic-model pre-scandal tweets of 92 ‘offenders’ to investigate
Purpose This paper aims to examine whether Twitter messaging can help mitigate the harm corporations suffer in the aftermath of ethical scandals. Design/methodology/approach This paper applies Web Application Programming Interfaces (API) on the Guardian and New York Times news archives to find corporations that suffered scandals between 2014 and 2019, revealing 92 publicly listed companies in the UK. Using Twitter API and the Python library, Getoldtweets, this paper extracts historical, pre-scandal – i.e. pre-2014 – tweets of the 92 firms. The paper topic-models the tweets data using Latent Dirichlet Allocation (LDA). This paper then subjects the topics to multidimensional scaling (MDS) to examine commonalities among them. Findings LDA reveals 10 topics, which group under 5 themes; these are product marketing, urgent signalling of “greenness”, customer relationship management, corporate strategy and news feeds. MDS suggests that the topics further congregate into two meta-themes of future-oriented versus immediate and individual versus global. Practical implications Provided they are sincere and legitimate, corporations’ tweets on global issues with a green agenda should help cushion the impact of ethical scandals. Overall, however, the findings suggest that Twitter messaging could be a double-edged sword, and underscore the importance of strategy. Originality/value The paper offers a first exploration of the relevance of corporate Twitter messaging in mitigating ethical scandals.
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
5.60
自引率
18.80%
发文量
35
期刊最新文献
Environmental catastrophes and organizational ambidexterity: lessons from the Covid-19 experience Organizational stakeholders and environmental sustainability investment: does China’s regional heterogeneity matter? Religious-ethnic entrepreneurs planting seeds: a novel research agenda Bringing home the bacon: do politicians on boards increase firms’ government contracts? The effect of CEOs’ being the only children in the family on their CSR engagement
×
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