Marka Kişiliğinin Büyük Veri Kapsamında Duygu Analizi Yöntemiyle Belirlenmesi: Hızlı Sonuç Almaya Odaklanmış Bir Uygulama
Determining Brand Personality Through Sentiment Analysis Method in the Scope of Big Data: A Rapid Results-Oriented Application
Author(s): Nebi Seren, Murat Hakan AltıntaşSubject(s): Business Economy / Management, Marketing / Advertising, Tourism, Socio-Economic Research
Published by: Orhan Sağçolak
Keywords: Machine Learning; Data Tagging; Sentiment Analysis; Brand Personality;
Summary/Abstract: Purpose - The aim of this research is to uncover customers' thoughts about the brand in tourism businesses more quickly using the sentiment analysis method. Two applications have been developed in line with this objective to expedite the labeling of customer reviews and to reveal the brand personalities of businesses more rapidly. Design/methodology/approach –The data used in this study was collected from internet pages over a three-month period. However, these comments not only include those made in the last three months but also encompass earlier comments about the business. A total of 1075 comments are utilized in this study. The data obtained from online comments were analyzed using the sentiment analysis method. Findings - As a result of sentiment analysis, the brand personality dimensions proposed by Aaker (1997) were tailored to tourism businesses, and it was determined which brand personality the comments indicated. The faster processing of data, which is the main goal of this study, is supported by the two applications developed. Discussion - This study attempts to highlight the importance of rapidly collecting and processing data for repeated analytical studies. The benefits that flexibility, such as obtaining data from desired sectors, within desired date ranges, and from desired sources, can provide to businesses are emphasized. This study introduces a different approach to brand personality dimensions for tourism businesses, based on the existing literature.
Journal: İşletme Araştırmaları Dergisi
- Issue Year: 15/2023
- Issue No: 4
- Page Range: 2763-2779
- Page Count: 17
- Language: Turkish