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The effects of visual congruence on increasing consumers’ brand engagement: An empirical investigation of influencer marketing on instagram using deep-learning algorithms for automatic image classification
Computers in Human Behavior ( IF 9.0 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.chb.2020.106443
Young Anna Argyris , Zuhui Wang , Yongsuk Kim , Zhaozheng Yin

Abstract Influencers are non-celebrity individuals who gain popularity on social media by posting visually attractive content (e.g., photos and videos) and by interacting with other users (i.e., Followers) to create a sense of authenticity and friendship. Brands partner with Influencers to garner engagement from their target consumers in a new marketing strategy known as “Influencer marketing.” Nonetheless, the theoretical underpinnings of such remains unknown. We suggest a new conceptual framework of “Visual-Congruence-induced Social Influence (VCSI),” which contextualizes the Similarity-Attraction Model in the Social Influence literature. Using VCSI, we delineate how Influencers use visual congruence as representations of shared interests in a specific area to build strong bonds with Followers. This intimate affiliation catalyzes (i.e., mediates) the positive effects of visual congruence on Followers’ brand engagement. To test these hypotheses, we conducted in vivo observations of Influencer marketing on Instagram. We collected >45,000 images and social media usage behaviors over 26 months. We then applied deep-learning algorithms to automatically classify each image and used social media analytics to disclose hidden associations between visual elements and brand engagement. Our hypothesis testing results provide empirical support for VCSI, advancing theories into the rapidly growing fields of multimodal content and Influencer marketing.

中文翻译:

视觉一致性对增加消费者品牌参与度的影响:使用深度学习算法进行自动图像分类的 instagram 影响者营销的实证调查

摘要 影响者是非名人,他们通过发布具有视觉吸引力的内容(例如照片和视频)以及与其他用户(即关注者)互动以营造真实感和友谊感而在社交媒体上获得人气。品牌与影响者合作,以一种称为“影响者营销”的新营销策略吸引目标消费者的参与。尽管如此,这种理论的基础仍然未知。我们提出了一个新的概念框架“视觉一致性引起的社会影响(VCSI)”,它将社会影响文献中的相似性吸引模型置于语境中。使用 VCSI,我们描绘了影响者如何使用视觉一致性作为特定领域共同兴趣的表示,以与追随者建立牢固的联系。这种亲密关系催化(即,调解)视觉一致性对追随者品牌参与的积极影响。为了验证这些假设,我们对 Instagram 上的影响者营销进行了体内观察。我们在 26 个月内收集了超过 45,000 张图片和社交媒体使用行为。然后,我们应用深度学习算法对每张图像进行自动分类,并使用社交媒体分析来揭示视觉元素与品牌参与度之间的隐藏关联。我们的假设检验结果为 VCSI 提供了实证支持,将理论推向了快速发展的多模式内容和影响者营销领域。26 个月内的 000 张图片和社交媒体使用行为。然后,我们应用深度学习算法对每张图像进行自动分类,并使用社交媒体分析来揭示视觉元素与品牌参与度之间的隐藏关联。我们的假设检验结果为 VCSI 提供了实证支持,将理论推向了快速发展的多模式内容和影响者营销领域。26 个月内的 000 张图片和社交媒体使用行为。然后,我们应用深度学习算法对每张图像进行自动分类,并使用社交媒体分析来揭示视觉元素与品牌参与度之间的隐藏关联。我们的假设检验结果为 VCSI 提供了实证支持,将理论推向了快速发展的多模式内容和影响者营销领域。
更新日期:2020-11-01
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