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The Detection of Brand Identity and Image Using Semantic Network Analysis

The Detection of Brand Identity and Image Using Semantic Network Analysis
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Author(s): Euntack Im (Soongsil University, South Korea), Dukjin Kim (Soongsil University, South Korea), Minhye Jwa (Soongsil University, South Korea) and Gwangyong Gim (Soongsil University, South Korea)
Copyright: 2022
Volume: 10
Issue: 2
Pages: 13
Source title: International Journal of Software Innovation (IJSI)
Editor(s)-in-Chief: Roger Y. Lee (Central Michigan University, USA) and Lawrence Chung (The University of Texas at Dallas, USA)
DOI: 10.4018/IJSI.289597

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Abstract

In Philip Kotler’s Hyper-connected, social-based market 4.0, consumers and businesses are formed in horizontal relationships through countless channels, and consumers decide whether to consume their products or services through their individuality and awareness of the people around them. Therefore, the importance of the brand as a company's intangible asset is growing. This paper tried to analyze brand identity based on Kapferer brand identity prism model. Based on Kapferer's theory that strong brands come from the combination of brand identity and image, it tried to identify whether brand identity and brand image match through semantic network analysis by using text extracted from social media and web page of Samsung Electronics, which ranked 7th in global brand value in 2017. As a result of the analysis, it was confirmed that the brand identity and the image were consistent and that there was no significant difference.

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