Exploring Twitter Dataset Content by Descriptive Analysis: An Application on Online Food Ordering

Yıldırım Güneş; Murat Arıkan

Makale detayları

Exploring Twitter Dataset Content by Descriptive Analysis: An Application on Online Food Ordering

Yazarlar:

Yıldırım Güneş | Murat Arıkan

Yayıncı:

Gazi University

Ana Başlıklar:

Bilgisayar Yazılımı

Dergi:

Bilişim Teknolojileri Dergisi Vol.16 Issue 2, pp.119-133

Belge Tipi:

Makale

Yayın Tarihi:

4/2023

Belge Dili:

Türkçe

Document ID (Org No.):

2001287844

pISSN:

1307-9697

Anahtar kelimeler:

Özet:

 Twitter is one of the online social networking sites where users opinions about any subject are circulating. The analysis of opinions drawn from Twitter has increaased remarkably in recent academic studies. Twitter is a valuable source of information with metadata of users and posts, as well as free-form text content that provides a source for new ideas. In this study, the data set collected on online meal ordering was analyzed with descriptive analysis tools; with the results obtained from here, a model called Exploration of Twitter Data Set Content by Descriptive Analysis, on how to extract customer opinions that businesses can use for improvementdevelopment purposes, is presented. In the model, methods that can be applied before and after the analysis are shown in order to save the analysis results from the effects of advertising texts. In this study, a total of 35 428 tweets posted between January 1, 2020 and December 31, 2020 were analyzed. At the end of the study, it has been determined that the main topics about online meal order on Twitter are; indecision about meal order, confidence in product and service, womens personal safety concerns, hospital meals are not liked, meals have to be shared with friends after ordering, working conditions of moto couriers, product presentation does not take place as expected, discountwildcard applications of businesses, regret after ordering meal at night, the effect of a television cooking program on orders and the relationship between online meal ordering and quarantine.

 Twitter is one of the online social networking sites where users opinions about any subject are circulating. The analysis of opinions drawn from Twitter has increaased remarkably in recent academic studies. Twitter is a valuable source of information with metadata of users and posts, as well as free-form text content that provides a source for new ideas. In this study, the data set collected on online meal ordering was analyzed with descriptive analysis tools; with the results obtained from here, a model called Exploration of Twitter Data Set Content by Descriptive Analysis, on how to extract customer opinions that businesses can use for improvementdevelopment purposes, is presented. In the model, methods that can be applied before and after the analysis are shown in order to save the analysis results from the effects of advertising texts. In this study, a total of 35 428 tweets posted between January 1, 2020 and December 31, 2020 were analyzed. At the end of the study, it has been determined that the main topics about online meal order on Twitter are; indecision about meal order, confidence in product and service, womens personal safety concerns, hospital meals are not liked, meals have to be shared with friends after ordering, working conditions of moto couriers, product presentation does not take place as expected, discountwildcard applications of businesses, regret after ordering meal at night, the effect of a television cooking program on orders and the relationship between online meal ordering and quarantine.

 Twitter is one of the online social networking sites where users opinions about any subject are circulating. The analysis of opinions drawn from Twitter has increaased remarkably in recent academic studies. Twitter is a valuable source of information with metadata of users and posts, as well as free-form text content that provides a source for new ideas. In this study, the data set collected on online meal ordering was analyzed with descriptive analysis tools; with the results obtained from here, a model called Exploration of Twitter Data Set Content by Descriptive Analysis, on how to extract customer opinions that businesses can use for improvementdevelopment purposes, is presented. In the model, methods that can be applied before and after the analysis are shown in order to save the analysis results from the effects of advertising texts. In this study, a total of 35 428 tweets posted between January 1, 2020 and December 31, 2020 were analyzed. At the end of the study, it has been determined that the main topics about online meal order on Twitter are; indecision about meal order, confidence in product and service, womens personal safety concerns, hospital meals are not liked, meals have to be shared with friends after ordering, working conditions of moto couriers, product presentation does not take place as expected, discountwildcard applications of businesses, regret after ordering meal at night, the effect of a television cooking program on orders and the relationship between online meal ordering and quarantine.

 Twitter, her konudaki kullanıcı görüşlerinin dolaşımda olduğu çevrimiçi paylaşım ağlarından biridir. Twitterdan çekilen kullanıcı görüşlerinin analizi son dönemde yapılan akademik çalışmalarda dikkat çekici şekilde artış göstermektedir. Twitter yeni fikirlere kaynaklık yapan serbest formdaki metin içeriklerinin yanı sıra kullanıcı ve gönderilere ait meta veri ile de değerli bir bilgi kaynağıdır. Bu çalışmada çevrimiçi yemek siparişi konusunda toplanan veri setinin tanımlayıcı analiz araçları ile analizi yapılmış; buradan elde edilen sonuçlarla, işletmelerin iyileştirmegeliştirme maksadıyla kullanabilecekleri müşteri görüşlerinin veri seti içinden nasıl çıkarılabileceğini gösteren ve Twitter Veri Seti İçeriğinin Tanımlayıcı Analiz İle Keşfi olarak adlandırılan bir model sunulmuştur. Modelde analiz sonuçlarının reklam içerikli metinlerin etkisinden kurtarılması için analiz öncesi ve sonrasında uygulanabilecek yöntemler gösterilmiştir. Bu çalışmada 1 Ocak-31 Aralık 2020 tarih aralığında paylaşılmış toplam 35 428 adet tweet analiz edilmiştir. Çalışma sonunda, çevrimiçi yemek siparişine ilişkin Twitterda yapılan paylaşımların ana gündem konularının; sipariş konusundaki kararsızlık, ürün ve hizmete duyulan güven, kadınların kişisel güvenlik endişesi, hastane yemeklerinin beğenilmemesi, sipariş sonrasında yemeklerin arkadaşlarla paylaşılmak zorunda kalınması, kuryelerin çalışma koşulları, ürün sunumunun beklenen şekilde gerçekleşmemesi, yemek siparişi üzerinden yardımlaşma, işletmelerin indirimlijoker uygulamaları, gece saatlerindeki yemek siparişi sonrasındaki pişmanlık, bir televizyon yemek programının siparişlere etkisi ve yemek siparişi ile karantina ilişkisi olduğu tespit edilmiştir.

Makale detayları

Exploring Twitter Dataset Content by Descriptive Analysis: An Application on Online Food Ordering

Yazarlar:

Yıldırım Güneş | Murat Arıkan

Yayıncı:

Gazi University

Ana Başlıklar:

Bilgisayar Yazılımı

Dergi:

Bilişim Teknolojileri Dergisi Vol.16 Issue 2, pp.119-133

Belge Tipi:

Makale

Yayın Tarihi:

4/2023

Belge Dili:

Türkçe

Document ID (Org No.):

2001287844

pISSN:

1307-9697

descriptive analysis

online meal ordering

online food ordering

content analysis

twitter analysistwitter analizi

tanımlayıcı analiz

çevrimiçi yemek siparişi

çevrimiçi gıda siparişi

içerik analizi

Sayı

Makale detayları

Yazarlar: Yıldırım Güneş | Murat Arıkan

Yayıncı: Gazi University

Ana Başlıklar: Bilgisayar Yazılımı

Dergi: Bilişim Teknolojileri Dergisi Vol.16 Issue 2, pp.119-133

Belge Tipi: Makale

Yayın Tarihi: 4/2023

Belge Dili: Türkçe

Document ID (Org No.): 2001287844

pISSN: 1307-9697

Sayı

Yazarlar:

Yıldırım Güneş | Murat Arıkan

Yayıncı:

Gazi University

Ana Başlıklar:

Bilgisayar Yazılımı

Dergi:

Bilişim Teknolojileri Dergisi Vol.16 Issue 2, pp.119-133

Belge Tipi:

Makale

Yayın Tarihi:

4/2023

Belge Dili:

Türkçe

Document ID (Org No.):

2001287844

pISSN:

1307-9697