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;
DOI:
http://doi.org/10.12928/telkomnika.v15i1.3460
Refbacks
There are currently no refbacks.
This work is licensed under a
Creative Commons Attribution-ShareAlike 4.0 International License .
TELKOMNIKA Telecommunication, Computing, Electronics and Control ISSN: 1693-6930, e-ISSN: 2302-9293Universitas Ahmad Dahlan , 4th Campus Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191 Phone: +62 (274) 563515, 511830, 379418, 371120 Fax: +62 274 564604
<div class="statcounter"><a title="Web Analytics" href="http://statcounter.com/" target="_blank"><img class="statcounter" src="//c.statcounter.com/10241713/0/0b6069be/0/" alt="Web Analytics"></a></div> View TELKOMNIKA Stats