社交媒体中的品牌语言:利用社交媒体对话的话题建模来推动品牌战略

IF 6.8 1区 管理学 Q1 BUSINESS
V. Swaminathan, H. A. Schwartz, Rowan Menezes, Shawndra Hill
{"title":"社交媒体中的品牌语言:利用社交媒体对话的话题建模来推动品牌战略","authors":"V. Swaminathan, H. A. Schwartz, Rowan Menezes, Shawndra Hill","doi":"10.1177/10949968221088275","DOIUrl":null,"url":null,"abstract":"This article highlights how social media data and language analysis can help managers understand brand positioning and brand competitive spaces to enable them to make various strategic and tactical decisions about brands. The authors use the output of topic models at the brand level to evaluate similarities between brands and to identify potential cobrand partners. In addition to using average topic probabilities to assess brands’ relationships to each other, they incorporate a differential language analysis framework, which implements scientific inference with multi-test-corrected hypothesis testing, to evaluate positive and negative topic correlates of brand names. The authors highlight the various applications of these approaches in decision making for brand management, including the assessment of brand positioning and future cobranding partnerships, design of marketing communication, identification of new product introductions, and identification of potential negative brand associations that can pose a threat to a brand's image. Moreover, they introduce a new metric, “temporal topic variability,” that can serve as an early warning of future changes in consumer preference. The authors evaluate social media analytic contributions against offline survey data. They demonstrate their approach with a sample of 193 brands, representing a broad set of categories, and discuss its implications.","PeriodicalId":48260,"journal":{"name":"Journal of Interactive Marketing","volume":null,"pages":null},"PeriodicalIF":6.8000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"The Language of Brands in Social Media: Using Topic Modeling on Social Media Conversations to Drive Brand Strategy\",\"authors\":\"V. Swaminathan, H. A. Schwartz, Rowan Menezes, Shawndra Hill\",\"doi\":\"10.1177/10949968221088275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article highlights how social media data and language analysis can help managers understand brand positioning and brand competitive spaces to enable them to make various strategic and tactical decisions about brands. The authors use the output of topic models at the brand level to evaluate similarities between brands and to identify potential cobrand partners. In addition to using average topic probabilities to assess brands’ relationships to each other, they incorporate a differential language analysis framework, which implements scientific inference with multi-test-corrected hypothesis testing, to evaluate positive and negative topic correlates of brand names. The authors highlight the various applications of these approaches in decision making for brand management, including the assessment of brand positioning and future cobranding partnerships, design of marketing communication, identification of new product introductions, and identification of potential negative brand associations that can pose a threat to a brand's image. Moreover, they introduce a new metric, “temporal topic variability,” that can serve as an early warning of future changes in consumer preference. The authors evaluate social media analytic contributions against offline survey data. They demonstrate their approach with a sample of 193 brands, representing a broad set of categories, and discuss its implications.\",\"PeriodicalId\":48260,\"journal\":{\"name\":\"Journal of Interactive Marketing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2022-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Interactive Marketing\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1177/10949968221088275\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Interactive Marketing","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1177/10949968221088275","RegionNum":1,"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: 5

摘要

这篇文章强调了社交媒体数据和语言分析如何帮助管理者了解品牌定位和品牌竞争空间,从而使他们能够做出关于品牌的各种战略和战术决策。作者在品牌层面使用主题模型的输出来评估品牌之间的相似性,并确定潜在的共同品牌合作伙伴。除了使用平均主题概率来评估品牌之间的关系外,他们还结合了一个差异语言分析框架,该框架通过多重检验校正的假设检验实现科学推断,以评估品牌名称的积极和消极主题相关性。作者强调了这些方法在品牌管理决策中的各种应用,包括评估品牌定位和未来的品牌合作伙伴关系,设计营销沟通,识别新产品介绍,以及识别可能对品牌形象构成威胁的潜在负面品牌联想。此外,他们引入了一个新的度量标准,“时间主题可变性”,可以作为消费者偏好未来变化的早期预警。作者根据线下调查数据评估了社交媒体分析的贡献。他们以193个品牌为样本,展示了他们的方法,代表了广泛的类别,并讨论了其含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Language of Brands in Social Media: Using Topic Modeling on Social Media Conversations to Drive Brand Strategy
This article highlights how social media data and language analysis can help managers understand brand positioning and brand competitive spaces to enable them to make various strategic and tactical decisions about brands. The authors use the output of topic models at the brand level to evaluate similarities between brands and to identify potential cobrand partners. In addition to using average topic probabilities to assess brands’ relationships to each other, they incorporate a differential language analysis framework, which implements scientific inference with multi-test-corrected hypothesis testing, to evaluate positive and negative topic correlates of brand names. The authors highlight the various applications of these approaches in decision making for brand management, including the assessment of brand positioning and future cobranding partnerships, design of marketing communication, identification of new product introductions, and identification of potential negative brand associations that can pose a threat to a brand's image. Moreover, they introduce a new metric, “temporal topic variability,” that can serve as an early warning of future changes in consumer preference. The authors evaluate social media analytic contributions against offline survey data. They demonstrate their approach with a sample of 193 brands, representing a broad set of categories, and discuss its implications.
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
20.20
自引率
5.90%
发文量
39
期刊介绍: The Journal of Interactive Marketing aims to explore and discuss issues in the dynamic field of interactive marketing, encompassing both online and offline topics related to analyzing, targeting, and serving individual customers. The journal seeks to publish innovative, high-quality research that presents original results, methodologies, theories, and applications in interactive marketing. Manuscripts should address current or emerging managerial challenges and have the potential to influence both practice and theory in the field. The journal welcomes conceptually rigorous approaches of any type and does not favor or exclude specific methodologies.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信