SOSYAL MEDYA VE YEREL SEÇİMLER: AK PARTİ #gönülbelediyeciliği ETİKETİ ÜZERİNE BİR ANALİZ

Bu makale, 31 Mart 2019'da yapılacak olan yerel seçimlerde, bir kampanya ve iletişim aracı olarak mikroblog platformu Twitter'a odaklanmaktadır. Seçimle ilgili tivitler için çok katmanlı ampirik analiz yöntemi kullanılmıştır. Etiketler dijital alanın ana unsuru olarak sadece Twitter’da değil aynı zamanda diğer platformlarca da kullanılmaktadır. Ayrıca, insanlar etiketleri çevrimdışı alanda da (haber başlıkları, seçim sloganları, reklamlar gibi) kullanmaya başlamışlardır. Çalışmada #gönülbelediyeciliği etiketi altınadaki tivitler analiz edilmiştir. Bu çalışma Türk seçmeninin Twitter’da etkileşim sürecini keşfetmeyi amaçlamaktadır. Bu nedenle seçim kampanyası sürecinde; Twitter’da etiketler, influencerlar ve tivitlerin coğrafi dağılım ile arasındaki ilişkiler analiz edilmiştir. 9 Mart 2019 ve 16 Mart 2019 tarihleri arasında, Twitter ortamında yer alan #gönülbelediyeciliği etiketi taranmış ve elde edilen veri seti ve bulgular web içerik analizi aracılığı ile değerlendirilmiştir. 

SOCIAL MEDIA AND LOCAL ELECTIONS: AN ANALYSIS ON THE AK PARTY’S #gönülbelediyeciliği HASHTAG

This article focuses on Twitter, it’s a microblogging platform using for election campaign and communication during Turkey’s local election, held on 31st March 2019. Election-related tweets analyzed with the multi-layered empirical methodology. Hashtags as a key element of the digital landscape are not only appearing Twitter but also the other platforms. Also, people started to use hashtags in an offline environment (news covers, election slogans, advertising etc). In this research analyzed the collected tweets under the hashtag of #gönülbelediyeciliği. This paper aims to explore the Turkish voters' engagement process on Twitter. For this reason during the local election campaign; hashtags, influencers and geographical distribution of tweets were analyzed. The #gönülbelediyeciliği hashtag was searched in Turkish Twitter environment, between 9th March 2019, and 16th March 2019. Web content analysis method was used to evaluate the data sets and the findings were evaluated by this method.

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