Multiple Regression to Analyse Social Graph of Brand Awareness

Yahya Peranginangin, Andry Alamsyah

Abstract


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.


Keywords


machine learning; brand awareness; social network analysis; regression;

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DOI: http://dx.doi.org/10.12928/telkomnika.v15i1.3460

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