SocialBrands:公众在社交媒体上对品牌认知的视觉分析

Xiaotong Liu, Anbang Xu, Liang Gou, Haibin Liu, R. Akkiraju, Han-Wei Shen
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引用次数: 16

摘要

公众对一个品牌的看法对其表现至关重要。虽然社交媒体已经显示出塑造公众对品牌认知的巨大潜力,但现有的工具对领域用户来说并不直观和解释,因为它们无法为品牌认知提供全面的分析框架。在本文中,我们提出了SocialBrands,这是一种新颖的视觉分析工具,供品牌经理了解公众在社交媒体上对品牌的看法。social - brands利用市场营销文献中的品牌人格框架和社会计算方法,从社交媒体上的三个驱动因素(用户形象、员工形象和官方公告)计算品牌的个性,并构建一个解释品牌个性与驱动因素之间关系的证据网络。然后将这些计算结果与新的交互式可视化相结合,以帮助品牌经理了解个性特征及其驱动因素。我们通过在企业背景下与品牌经理进行的一系列用户研究,证明了SocialBrands的有用性和有效性。设计课程也来源于我们的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SocialBrands: Visual analysis of public perceptions of brands on social media
Public perceptions of a brand is critical to its performance. While social media has demonstrated a huge potential to shape public perceptions of brands, existing tools are not intuitive and explanatory for domain users to use as they fail to provide a comprehensive analysis framework for perceptions of brands. In this paper, we present SocialBrands, a novel visual analysis tool for brand managers to understand public perceptions of brands on social media. Social-Brands leverages brand personality framework in marketing literature and social computing approaches to compute the personality of brands from three driving factors (user imagery, employee imagery, and official announcement) on social media, and construct an evidence network explaining the association between brand personality and driving factors. These computational results are then integrated with new interactive visualizations to help brand managers understand personality traits and their driving factors. We demonstrate the usefulness and effectiveness of SocialBrands through a series of user studies with brand managers in an enterprise context. Design lessons are also derived from our studies.
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