Mapping the Science World with Correlated Topic Modeling Analysis from Science-Related Posts on the Reddit Platform

Semanur Gürsoy; Özcan Özyurt

Makale detayları

Mapping the Science World with Correlated Topic Modeling Analysis from Science-Related Posts on the Reddit Platform

Yazarlar:

Semanur Gürsoy | Özcan Özyurt

Yayıncı:

Duzce University

Ana Başlıklar:

Makine Öğrenmesi Algoritmaları

Dergi:

Düzce Üniversitesi Bilim ve Teknoloji Dergisi Vol.12 Issue 3, pp.1664-1674

Belge Tipi:

Makale

Yayın Tarihi:

7/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001323942

pISSN:

2148-2446

Anahtar kelimeler:

Özet:

 The main source of technology in todays world is science. The world of science is being reshaped every day with the continuation of studies in the fields of science and technology. However, the development of technology causes the amount of data that cannot be processed with traditional methods on technological platforms to increase day by day. Making meaningful data meaningful by processing unmeaningful data will enable companies, institutions, and organizations to transform big data into highly beneficial tools. One of the most effective data mining techniques for processing and making sense of data is topic modeling. In this study, semantic content analysis of science-related posts on the Reddit platform was conducted using corelated topic modeling CTM, one of the topic modeling techniques. In the first nine months of 2022, the hidden meanings in Reddit posts and the correlation between these meanings were revealed, and the relevant results were shared. It is thought that the results obtained will be a source of ideas for people interested in science and scientists for their research.

 The main source of technology in todays world is science. The world of science is being reshaped every day with the continuation of studies in the fields of science and technology. However, the development of technology causes the amount of data that cannot be processed with traditional methods on technological platforms to increase day by day. Making meaningful data meaningful by processing unmeaningful data will enable companies, institutions, and organizations to transform big data into highly beneficial tools. One of the most effective data mining techniques for processing and making sense of data is topic modeling. In this study, semantic content analysis of science-related posts on the Reddit platform was conducted using corelated topic modeling CTM, one of the topic modeling techniques. In the first nine months of 2022, the hidden meanings in Reddit posts and the correlation between these meanings were revealed, and the relevant results were shared. It is thought that the results obtained will be a source of ideas for people interested in science and scientists for their research.

 The main source of technology in todays world is science. The world of science is being reshaped every day with the continuation of studies in the fields of science and technology. However, the development of technology causes the amount of data that cannot be processed with traditional methods on technological platforms to increase day by day. Making meaningful data meaningful by processing unmeaningful data will enable companies, institutions, and organizations to transform big data into highly beneficial tools. One of the most effective data mining techniques for processing and making sense of data is topic modeling. In this study, semantic content analysis of science-related posts on the Reddit platform was conducted using corelated topic modeling CTM, one of the topic modeling techniques. In the first nine months of 2022, the hidden meanings in Reddit posts and the correlation between these meanings were revealed, and the relevant results were shared. It is thought that the results obtained will be a source of ideas for people interested in science and scientists for their research.

 Günümüz dünyasında ulaşılan teknolojinin ana kaynağı bilimdir. Bilim ve teknoloji alanlarındaki çalışmaların devam etmesiyle bilim dünyası her geçen gün yeniden şekillenmektedir. Bununla birlikte, teknolojinin gelişmesi teknolojik platformlardaki geleneksel yöntemlerle işlenemeyen veri miktarının her geçen gün artmasına sebep olmaktadır. Anlamlandırılmamış verinin işlenerek anlamlı hale getirilmesi şirketler, kurum ve kuruluşlar için büyük verinin yüksek oranda fayda sağlayan araçlar haline dönüştürülmesine olanak sağlayacaktır. Verinin işlenerek anlamlı hale getirilmesinde en etkili veri madenciliği tekniklerinden biri konu modellemedir. Bu çalışmada konu modelleme tekniklerinden olan ilişkili konu modelleme İKM kullanılarak Reddit platformu üzerinde bilimle ilgili paylaşımların anlamsal içerik analizi yapılmıştır. 2022 yılının ilk dokuz ayına ait Reddit paylaşımlarındaki gizli anlamlar ve bu anlamlar arasındaki korelasyon ortaya koyulmuş ve ilgili sonuçlar paylaşılmıştır. Elde edilen sonuçların bilime ilgili insanlara ve bilim insanlarına araştırmaları için fikir kaynağı olacağı düşünülmektedir.

Makale detayları

Mapping the Science World with Correlated Topic Modeling Analysis from Science-Related Posts on the Reddit Platform

Yazarlar:

Semanur Gürsoy | Özcan Özyurt

Yayıncı:

Duzce University

Ana Başlıklar:

Makine Öğrenmesi Algoritmaları

Dergi:

Düzce Üniversitesi Bilim ve Teknoloji Dergisi Vol.12 Issue 3, pp.1664-1674

Belge Tipi:

Makale

Yayın Tarihi:

7/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001323942

pISSN:

2148-2446

Data Mining

Correlated Topic Modeling

Reddit

ScienceVeri Madenciliği

İlişkili Konu Modelleme

Reddit

Bilim

Sayı

Makale detayları

Yazarlar: Semanur Gürsoy | Özcan Özyurt

Yayıncı: Duzce University

Ana Başlıklar: Makine Öğrenmesi Algoritmaları

Dergi: Düzce Üniversitesi Bilim ve Teknoloji Dergisi Vol.12 Issue 3, pp.1664-1674

Belge Tipi: Makale

Yayın Tarihi: 7/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001323942

pISSN: 2148-2446

Sayı

Yazarlar:

Semanur Gürsoy | Özcan Özyurt

Yayıncı:

Duzce University

Ana Başlıklar:

Makine Öğrenmesi Algoritmaları

Dergi:

Düzce Üniversitesi Bilim ve Teknoloji Dergisi Vol.12 Issue 3, pp.1664-1674

Belge Tipi:

Makale

Yayın Tarihi:

7/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001323942

pISSN:

2148-2446