Final Draft. Brand Clustering. Literature & Language Case Study

Brand Clustering
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I. Introduction
Many individuals document and share their sentiments on brands, news, and products in Social Network Services. Therefore, social media, for example, LinkedIn, Twitter, and Facebook play a significant role in gathering, transferring, and sharing sentiments of people. Many firms are keen to discover these collective sentiments about their brands or products. Since customers are inclined to share opinions regarding firms’ products or brands candidly on the internet – particularly on social media, collecting and mining options has become a crucial factor for marketers who are attempting to identify customer preference.
II. Discussion
In a study conducted by Hye-Ryeon Yong, Ha-Na Kang, and Hyun-Seok Hwang, a framework for clustering corporate brands, based on social metrics – the number of brand names mentioned together on microblog and Twitter, is proposed. Since marketers always want to know how customers perceive their products, this study is aimed at assisting marketers to develop further insight into customer preference (Hwang et al., 2016).
As suggested by Yong, Kang, and Hwang, a brand name is clustered by calculating the distance of paired brand names based on the total number of brand names mentioned together (Hwang et al., 2016). These distances are then transformed to project the brand names onto a two-dimensional and a three-dimensional space using Multi-Dimensional Scaling. After the projection of the brand names, the brand clusters are determined using k-means clustering, which identifies the characteristic of each cluster (Hwang et al., 2016). As stated by Yong, Kang, and Hwang, the biggest challenge in cluster branding is how data is collected and analyzed from social media. The collected data does not easily determine the characteristics of the customers. Instead, it simply shows the brand name which affects the outcome and dependability of the research.
In a separate research, I discovered that Channel, Dior, Bobbi Brown, and YSL are frequently mentioned positively. The frequency of po...