Metin Madenciliği Yöntemiyle Dijital Katılım Analizi ve 2017 Türkiye Sosyal Medya Referandumu

Abstract

Sosyal ağlar günümüzde pek çok alanda toplulukları yönlendirici unsur haline gelmiştir. Twitter bu ağlar içerisinde anlık gündem belirleyen en önemli platformlardan birisidir. Özellikle son on yılda dünyanın her ülkesinde siyasi süreçlerde de sosyal ağlardan faydalanılmaktadır. Gerek siyasi partilerin propagandalarını yönetmeleri gerekse de halkın görüşlerini dile getirmesi açısından sosyal ağlar önemli platformlar haline gelmiştir. Buradan yola çıkarak Türkiye’de 2017 yılında gerçekleştirilen Referandum sürecinde Twitter üzerinde bir metin madenciliği çalışması gerçekleştirilmiştir. Çalışmada toplumun Twitter aracılığıyla paylaştığı görüşler incelenmiş ve siyasi süreçlerin etkililiğinin ortaya çıkarılması amaçlanmıştır. Bu amaç doğrultusunda referandumun tercih seçenekleri olan evet/hayır görüşleri, siyasi partileri ve siyasi parti liderlerini içeren görüşlerin oranları karşılıklı olarak analiz edilmiştir. Bu analizlerle, sosyal siber istihbaratta örnek teşkil edebilecek bir çalışma gerçekleştirilmiş ve politika belirleyiciler için karar destek sistemlerinin potansiyelleri ortaya çıkarılmıştır.

Keywords

• Sosyal Medya Analizi
• Metin Madenciliği
• Referandum
• Büyük Veri
• Veri Analizi

Analysis of Digital Participation with Text Mining Method and 2017 Turkey Social Media Referendum

Abstract

Social networks have recently become a guiding factor for communities in many areas. Twitter is one of the most important platforms on the social network for setting instant agendas among these networks. Especially in the last decade, social networks have been used in political processes globally. Social networks have become important platforms for political parties to manage their propaganda and for the public to express their opinion. Based on this, a text mining study was carried out on Twitter during Turkey’s 2017 referendum process. In the study, public opinions posted on Twitter were examined to reveal the effectiveness of political processes. For this purpose, the ratios of yes/no opinions, political parties, and political party leaders were analyzed, which are the preferred options of the referendum. With these analyses, an empirical study on social-cyber intelligence was carried out, and the potential of decision support systems for policymakers was revealed.

Keywords

• Social Media Analysis
• Text Mining
• Referendum
• Big Data
• Data Analysis

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