Creating Brand Image Profile by Social Media Analysis

Authors

  • İbrahim Sabuncu Yalova University https://orcid.org/0000-0001-8625-9256
  • Berivan Edeş Yalova University
  • Doruk Sıtkıbütün Yalova University
  • İlayda Girgin Yalova University
  • Kadir Zehir Yalova University

DOI:

https://doi.org/10.5195/emaj.2021.228

Keywords:

Social Media Analysis, Brand Image Profile, Text Mining, Net Brand Reputation, Twitter

Abstract

The purpose of creating a brand image profile is to measure the brand perception of consumers considering brand attributes. Thus, marketing decisions can be made based on the brand's strengths and weaknesses by determining them. The brand image profile is traditionally created using the attitude scales and surveys. However, alternative methods are needed since the questionnaires' responses are careless, the number of participants is relatively low and the cost per participant is high. In this study, as an alternative method, creating a brand image profile by analyzing social media data with artificial intelligence was made for the iPhone product. Firstly, the focus group study determined the attributes related to the last version of the iPhone. Then, between December 17th, 2019 and March 23rd, 2020, 87.227 tweets that include these attributes in English were collected from the Twitter social media platform through the RapidMiner data mining tool. Sentiment analysis was performed on collected tweets by the MeaningCloud text mining tool. In this analysis, positive and negative emotions were tried to be detected through artificial intelligence algorithms. Net Brand Reputation Score (NBR) was calculated using the positive and negative tweets amount for each attribute separately. Brand image profile was created by skew analysis using NBR values. As a result, it is thought that social media analysis can be a complementary method that can be used with traditional methods in creating a brand image profile. So, it is seen as an inevitable method to use in further studies to make sentiment analysis by processing raw data received from the Social Media platforms through artificial intelligence algorithms to transform the product label or the perspectives of an event into meaningful information.

Author Biography

İbrahim Sabuncu, Yalova University

Assist. Prof. Dr. İbrahim SABUNCU was born in Istanbul and graduated from Çukurova University, Department of Industrial Engineering, in 2002. In 2005, he completed his master's degree in Gaziantep University Industrial Engineering Department. Between 2003 and 2004, he worked as a research assistant in the same department. Between 2006-2014, he worked as a lecturer in the Department of Computer Engineering, Faculty of Engineering, Harran University. He completed his Ph.D. in International Trade and Finance at Yalova University, Institute of Social Sciences. He had worked as a research assistant at the Industrial Engineering Department of Yalova University from 2014 to 2017. Now he has been working as an Assistant Professor in the same department. He has studies and publications within the scope of customer analytics and social media analytics. He teaches analytical methods in marketing, customer relationship management, e-commerce, process management, marketing management, and system simulation.

References

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Published

2021-12-13

Issue

Vol. 11 No. 2 (2021)

Section

Articles

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