Türkiye havayolu ağında yolcu hareketlerinin kitle kaynak verisi kullanılarak mekansal analizi

Abstract

Havacılık sektöründe yaşanan gelişmeler modern insanın seyahat alışkanlıklarını tamamen değiştirmiştir. Uzaklık mefhumu dahi mesafe birimleri yerine zamanla ölçülür hale gelmiştir. Bunun yanında modern insanın artık ayrılmaz parçası olan bir diğer unsur da sosyal medyadır. Sosyal medya kullanımındaki artışın varlığı ve kalıcılığı artık genel kültür olarak yerleşmiştir. Bu paylaşımlar bir veri okyanusunu oluşturan damlalara benzetilebilir. Farklı kaynaklardan paylaşılan milyarlarca içerik, metin, konum bilgisi işlenmeyi bekleyen bu veri okyanusunu oluşturur. Bu veri akışı, insana yeni bir rolü de biçmiştir. Artık `sıradan` insan yalnızca veriyi tüketen değil, üreten konumundadır. Bu akış değişikliği yeni bir kavramı da gündeme getirmiştir; `Kitle Kaynak Verisi`. Kim tarafından üretildiği artık `pek` de önemli olmayan, kalabalıkların ürettiği bu veri yepyeni imkanlar doğurmaktadır. Değişen alışkanlıklar ve teknolojideki gelişimler sonucu konum bilgisi içeren sosyal medya paylaşımları yeni araştırma olanakları sunmaktadır. Günlük yaşam rutinlerinin internet ortamında yoğun şekilde paylaşıldığı bu dönemde, hava taşımacılığı ile yapılan seyahatler de sosyal medya paylaşımlarına konu olmaktadır. Bir yolculuğun başlangıcı ve bitişi halka açık bu sosyal medya paylaşımları üzerinden görülebilir. Bu çalışmada da kitle kaynak verisi kullanılarak, Türkiye'deki hava taşımacılığı ağlarının ve havalimanlarının performansı incelenmeye çalışılmıştır. Kitle kaynak veri kaynağı olarak, son yıllarda kullanımı giderek artmış olan mikro blog platformu Twitter seçilmiştir. Twitter platformunda konum bilgisi ile paylaşılan tweetler, yaklaşık 4 aylık süre boyunca bir veri tabanında toplanmış, coğrafi filtreler uygulanarak havalimanlarında yapılan paylaşımlar süzülmüş ve harita üzerinde görselleştirilmiştir. Bu veri kümeleri ışığında bir dizi analiz yapılarak, bu süre zarfında sosyal medya kullanıcıları tarafından üretilen bu verinin, hava taşımacılığı ağını kullanan kullanıcıların hareketlerini, ağda harcadıkları süreleri, terminal içi hareketlerini, havalimanına ulaşırken harcadıkları süreleri ve havalimanı tercihlerini tespit etmede kullanılıp kullanılamayacağı araştırılmıştır.

Advances in the aviation industry have completely changed the travel habits of modern people. Even the notion of distance has become measurable over time rather than distance units. In addition, social media is another element which is an integral part of modern man. The existence and persistence of the increase in the use of social media has become common knowledge. Every individual produce and share a certain amount of data about itself. These data can be likened to drops that form an ocean of data. Billions of content, text, and location information shared from different sources, make up this ocean of data waiting to be processed. This data flow has also given a new role to man. Now the `ordinary` person is not only consuming data, but producing it. This change in flow has brought up a new concept; `Crowd Sourcing Data`. This data produced by the crowds, which is no longer important who has produced it, creates new opportunities. As a result of changing habits and developments in technology, social media sharing including location information offers new research opportunities. During this period, where daily life routines are shared intensively on the internet, air travel is also becomes a subject to social media sharing. The beginning and end of a journey can be seen through these public shares. In this study, using crowdsourcing data, air transport networks and airports performance in Turkey were examined. As the source of the mass data, Twitter, a micro blogging platform, has been chosen whose usage has increased in recent years. The tweets, which were shared with the location information on the Twitter platform, were collected in a database for a period of about 4 months, and the shares made at the airports were filtered and mapped by applying geographical filters. In the light of these data, a series of analyzes were conducted to determine whether this data produced by social media users could be used to determine the movements of the users using the air transport network, the time they spent on the network, the movements within the terminal, the time they spent while reaching the airport and some parameters effecting their airport preferences. Turkey is one of the fastest developing countries in the world in the aviation sector. The number of airports that have doubled in the last decade and the sector volume which has grown more than 20 times are the most important indicators of this. Due to its geographical location as a `hub` in nature, Turkey seeming to maintain this position in aviation. Therefore, its weight in the air transport network is also quite high. Although subject to audits and standards of international organizations, each country is obliged to conduct its own internal audits. In this context, taking into consideration Turkey's place in the world of civil aviation, air transport network and the efficiency of airports in Turkey is an important issue that should be studied in itself. However by the nature of the industry, sharing data is an issue itself. At this point crowd sourcing data offers new opportunities and changing the understanding of the industry.In this study, using crowdsourcing data major airports in Turkey, according to some performance indicators established by the European aviation organizations were investigated. Current aviation trends and the vision drawn by ICAO and Eurocontrol were taken into consideration while determining the analysis topics. Similar studies have been evaluated within the scope of literature review. In this context, 5 different analysis subjects were identified and location tagged tweets were used for these analyzes. In this sense, the study both points to concrete conclusions and sheds light on the analyzes that can be worshiped.Along with the data source, the softwares and programming languages have been used during the study are open sourced as well. Increasing trend on using open sourced data inevitably leads some changes in the aviation industry as well. This is one of the contributions of the study.All of the analyzes carried out during the study has been conducted using open sourced software and programming languages. Data has been collected, using Python programming language, stored in PostgreSQL database, analyzed using pandas and R programming language. The maps created as a result of those analyzes and purpose of visualization have been created using QGIS software. As a result while indicating some recent trends in the aviation industry, this study investigates and lights the ways to use crowd sourcing data for further analyzes. Among with the analyzes carried out the study manifests the belief that the data should be open for the good of the public.