Using Natural Language Processing to Identify Effective Influencers

IF 2.4 4区 管理学 Q3 BUSINESS
Xing Fang, Tian-jia Wang
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引用次数: 1

Abstract

Identifying the right influencers for brands is often the starting point for a successful influencer campaign. However, influencer identification is understudied, and most previous studies have only discussed visible characteristics of influencers and their social networks, overlooking content-based metrics. Combining interdisciplinary theories and techniques from marketing, linguistics, and computer science, we propose a data-driven automated text analysis framework to identify characteristics of effective influencers using influencer posts. Specifically, we propose a model that incorporates influencer personality traits captured by natural language processing, accounting for traditional covariates, such as network structure and follower engagement. In addition, we use a dataset that attributes influencer social media activities to customer purchases to address fake engagement and showcase our automated textual analysis. The proposed framework can help marketers develop influencer profiles and predict optimal influencers for their campaigns.
利用自然语言处理识别有效影响者
为品牌识别合适的影响者通常是成功的影响者活动的起点。然而,影响者识别研究不足,以前的大多数研究只讨论了影响者及其社交网络的可见特征,而忽略了基于内容的指标。结合市场营销、语言学和计算机科学的跨学科理论和技术,我们提出了一个数据驱动的自动文本分析框架,以使用影响者帖子来识别有效影响者的特征。具体来说,我们提出了一个模型,该模型结合了自然语言处理所捕捉到的影响者人格特征,考虑了传统的协变量,如网络结构和追随者参与度。此外,我们使用一个数据集,将有影响力的社交媒体活动归因于客户购买,以解决虚假参与问题,并展示我们的自动文本分析。所提出的框架可以帮助营销人员开发影响者档案,并预测其活动的最佳影响者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.00
自引率
6.70%
发文量
38
期刊介绍: The International Journal of Market Research is the essential professional aid for users and providers of market research. IJMR will help you to: KEEP abreast of cutting-edge developments APPLY new research approaches to your business UNDERSTAND new tools and techniques LEARN from the world’s leading research thinkers STAY at the forefront of your profession
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