Journals / Acta Infologica / 2021 / Cilt: 5 - Sayı: 2

A Study To Develop A Turkish Sentiment Lexicon On Brand Image

Marka İmajı Üzerine Türkçe Duygu Sözlüğü Geliştirme Çalışması

Pages
415–433
Publication Date
2022-09-04
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The brand image lexicon was created with 9535 words which express sentiment in the domain of brand image among the 31,671 words used most frequently.

📌 3 Key Takeaways

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Objective & Hypothesis:In recent years, sentiment analysis has emerged as one of the most useful methods for businesses in order to determine the comments and thoughts of users, to reveal their opinion and emotions about brands.
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Key Findings & Data:In order to achieve this aim, 113 Turkish theses in the higher education institution (YÖK) related to brand image were scanned, and the most frequently mentioned words in them were tried to be determined with the sentiment analysis method by R programming language.
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Conclusion & Impact:The brand image lexicon was created with 9535 words which express sentiment in the domain of brand image among the 31,671 words used most frequently.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In recent years, sentiment analysis has emerged as one of the most useful methods for businesses in order to determine the comments and thoughts of users, to reveal their opinion and emotions about brands. From a methodological perspective, the fact that general lexicons do not adequately represent brand terms in the domain of brand image, that there is no sentiment lexicon in Turkish in the context of the brand, and the fact that there are very few studies that reveal the brand image with sentiment analysis reveal the deficiency in this domain. In this context, the purpose of this research is to create a Turkish lexicon that is necessary for sentiment analysis in order to determine the perception of the image of the brand in users’ minds. In order to achieve this aim, 113 Turkish theses in the higher education institution (YÖK) related to brand image were scanned, and the most frequently mentioned words in them were tried to be determined with the sentiment analysis method by R programming language. The total number of words obtained in the data set of the field of brand image was observed as 1,738,596. Among these words, the most frequently used words in the field of brand image were obtained as 31,671. The brand image lexicon was created with 9535 words which express sentiment in the domain of brand image among the 31,671 words used most frequently.

Özet

Son yıllarda kullanıcıların yorum ve düşüncelerini belirleyebilmek, markalar hakkındaki düşünce ve duygularını ortaya çıkarabilmek amacı ile duygu analizi, işletmeler açısından en kullanışlı yöntemlerden birisi olarak karşımıza çıkmaktadır. Yöntem bilimsel bakış açısıyla genel sözlüklerin marka imajı alanına ait marka terimlerini yeteri kadar temsil edememesi, Türkçe olarak marka bağlamında duygu sözlüğünün yer almaması ve marka imajını duygu analizi ile ortaya koyan çalışmaların son derece az olması, bu alandaki eksikliği ortaya koymaktadır. Bu kapsamda bu araştırmanın amacı markaların kullanıcıların zihnindeki imaj algısını belirleyebilmek adına duygu analizi için gerekli olan bir Türkçe sözlük oluşturmaktır. Bu amacı gerçekleştirmek için, marka imajı ile ilgili yükseköğretim kurumundaki (YÖK) 113 Türkçe tez taranarak, içerisinde en çok geçen kelimeler R programlama dili kullanılarak, duygu analizi yöntemi ile tespit edilmeye çalışılmıştır. Marka imajı alanına ait veri setinde toplamda elde edilen kelime sayısı 1.738.596 adet olarak gözlemlenmiştir. Bu kelimeler içerisinde marka imajı alanında en sık kullanılanlar ise 31.671 adet kelime olarak elde edilmiştir. En sık kullanılan 31.671 kelimenin içerisinde marka imajı alanında duygu ifade eden 9535 adet kelime ile marka imajı sözlüğünü oluşturulmuştur.

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Cite This Article

AKCAN, E. Ö. (2022). A Study To Develop A Turkish Sentiment Lexicon On Brand Image. Acta Infologica, Cilt: 5 - Sayı: 2, 415–433. https://ajindex.com/articles/425983

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