TEXT MINING AND KNOWLEDGE MAPPING OF POSTGRADUATE THESES ON GENERATIONS IN TURKEY

Celalettin Yanık; Melih Engin

Makale detayları

TEXT MINING AND KNOWLEDGE MAPPING OF POSTGRADUATE THESES ON GENERATIONS IN TURKEY

Yazarlar:

Celalettin Yanık | Melih Engin

Yayıncı:

Bandirma Onyedi Eylul University

Ana Başlıklar:

Aile ve Hanehalkı Çalışmaları

Dergi:

Yönetim ve Ekonomi Araştırmaları Dergisi Vol.22 Issue 4, pp.186-203

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001335814

pISSN:

2148-029X

Anahtar kelimeler:

Özet:

 In the realm of social sciences, the concept of generation represents one of the most contentious areas. The problem lies not in the concept itself, but rather in the meanings attributed to it. The meanings attributed to the concept are used to establish marketing principles by comparing a group of individuals that are taken into consideration or based within a specific category with the basic characteristics that are assumed to have opposite qualities of this group. In this study, keywords were collected from the theses containing the word generation that were downloaded from the website where graduate theses belonging to the Council of Higher Education are published. In addition to the descriptive statistical findings on the year, university, and subject data of the theses, an association analysis of the keywords of these theses was performed using the Apriori algorithm. The research findings revealed that the majority of graduate theses on generation are masters theses, their popularity is increasing, and the keyword generation is associated with various fields such as behavior, difference, business, social relations, media, and conflict.

 In the realm of social sciences, the concept of generation represents one of the most contentious areas. The problem lies not in the concept itself, but rather in the meanings attributed to it. The meanings attributed to the concept are used to establish marketing principles by comparing a group of individuals that are taken into consideration or based within a specific category with the basic characteristics that are assumed to have opposite qualities of this group. In this study, keywords were collected from the theses containing the word generation that were downloaded from the website where graduate theses belonging to the Council of Higher Education are published. In addition to the descriptive statistical findings on the year, university, and subject data of the theses, an association analysis of the keywords of these theses was performed using the Apriori algorithm. The research findings revealed that the majority of graduate theses on generation are masters theses, their popularity is increasing, and the keyword generation is associated with various fields such as behavior, difference, business, social relations, media, and conflict.

 In the realm of social sciences, the concept of generation represents one of the most contentious areas. The problem lies not in the concept itself, but rather in the meanings attributed to it. The meanings attributed to the concept are used to establish marketing principles by comparing a group of individuals that are taken into consideration or based within a specific category with the basic characteristics that are assumed to have opposite qualities of this group. In this study, keywords were collected from the theses containing the word generation that were downloaded from the website where graduate theses belonging to the Council of Higher Education are published. In addition to the descriptive statistical findings on the year, university, and subject data of the theses, an association analysis of the keywords of these theses was performed using the Apriori algorithm. The research findings revealed that the majority of graduate theses on generation are masters theses, their popularity is increasing, and the keyword generation is associated with various fields such as behavior, difference, business, social relations, media, and conflict.

 In the realm of social sciences, the concept of generation represents one of the most contentious areas. The problem lies not in the concept itself, but rather in the meanings attributed to it. The meanings attributed to the concept are used to establish marketing principles by comparing a group of individuals that are taken into consideration or based within a specific category with the basic characteristics that are assumed to have opposite qualities of this group. In this study, keywords were collected from the theses containing the word generation that were downloaded from the website where graduate theses belonging to the Council of Higher Education are published. In addition to the descriptive statistical findings on the year, university, and subject data of the theses, an association analysis of the keywords of these theses was performed using the Apriori algorithm. The research findings revealed that the majority of graduate theses on generation are masters theses, their popularity is increasing, and the keyword generation is associated with various fields such as behavior, difference, business, social relations, media, and conflict.

Makale detayları

TEXT MINING AND KNOWLEDGE MAPPING OF POSTGRADUATE THESES ON GENERATIONS IN TURKEY

Yazarlar:

Celalettin Yanık | Melih Engin

Yayıncı:

Bandirma Onyedi Eylul University

Ana Başlıklar:

Aile ve Hanehalkı Çalışmaları

Dergi:

Yönetim ve Ekonomi Araştırmaları Dergisi Vol.22 Issue 4, pp.186-203

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001335814

pISSN:

2148-029X

Generation

Text Mining

Apriori

Türkiye

Sayı

Makale detayları

TEXT MINING AND KNOWLEDGE MAPPING OF POSTGRADUATE THESES ON GENERATIONS IN TURKEY

Yazarlar: Celalettin Yanık | Melih Engin

Yayıncı: Bandirma Onyedi Eylul University

Ana Başlıklar: Aile ve Hanehalkı Çalışmaları

Dergi: Yönetim ve Ekonomi Araştırmaları Dergisi Vol.22 Issue 4, pp.186-203

Belge Tipi: Makale

Yayın Tarihi: 1/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001335814

pISSN: 2148-029X

Generation

Text Mining

Apriori

Türkiye

Sayı

Yazarlar:

Celalettin Yanık | Melih Engin

Yayıncı:

Bandirma Onyedi Eylul University

Ana Başlıklar:

Aile ve Hanehalkı Çalışmaları

Dergi:

Yönetim ve Ekonomi Araştırmaları Dergisi Vol.22 Issue 4, pp.186-203

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001335814

pISSN:

2148-029X