文章基本信息

标题：Multiple Regression to Analyse Social Graph of Brand Awareness
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作者：Yahya Peranginangin ; Andry Alamsyah
期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2017
卷号：15
期号：1
页码：336-340
DOI：10.12928/telkomnika.v15i1.3460
语种：English
出版社：Universitas Ahmad Dahlan
摘要：Social Network Analysis (SNA) has become a common tool to conduct social and business research. In marketing SNA is used to measure word of mouth of a marketing campaign. For an example, a good marketing campaign should create intensive conversation between users in social media. In this paper we use SNA metrics to find out if we can predict brand awareness. We crawl conversation data from Twitter to form seven graph of seven brand in Indonesia. We use multiple regression method, an extension of linear regression, to analyse network properties to get insight on how network structure affect brand awareness of a product. Even though this research is still in early stage, but we manage to discover that a good network structure in knowledge dissemination case (such as word of mouth) eventually differ with the one in brand awareness.
其他摘要：Social Network Analysis (SNA) has become a common tool to conduct social and business research. In marketing SNA is used to measure word of mouth of a marketing campaign. For an example, a good marketing campaign should create intensive conversation between users in social media. In this paper we use SNA metrics to find out if we can predict brand awareness. We crawl conversation data from Twitter to form seven graph of seven brand in Indonesia. We use multiple regression method, an extension of linear regression, to analyse network properties to get insight on how network structure affect brand awareness of a product. Even though this research is still in early stage, but we manage to discover that a good network structure in knowledge dissemination case (such as word of mouth) eventually differ with the one in brand awareness.
关键词：: brand awareness; SNA; regression; graph