Sercan Şengün

Sercan Şengün (2016 BİLGİ Communication PhD graduate) graduated from Visual Communication Design (B.A.), Film and Television (M.A.), and is currently a Ph.D. candidate of Communication Science in İstanbul Bilgi University. He is also a game designer, an acting member of Turkish Game Developers Association (Oyunder) and a lecturer in Bahçeşehir University Game Design Master’s Degree. His work could be followed from his website; www.sercansengun.com

Research interests: video game studies, video game design, interactive narratives, gamification.

Ph.D. thesis title: Narra Ludens: Explaining Video Game Narrative Engagement Through Player Types

Abstract: This study aims to understand the behaviours of video game players regarding different narrative components inside video games. A branch of academic game studies called player type resarch seeks to understand why and how different players engage with video games. Various previous player type research offered a category of gamers commonly known as “narrative” or “fantasy” player type, yet failed to address the behaviours of this type in detail. To explain narrative players, the methodology of textual analysis on user reviews was chosen. The study gathered 1690 user reviews from Steam platform about 18 video games that were determined as the most popular games with narrative components in the first quarter of 2016. The reviews were run through a semantic cluster and a valence analysis. Initially they were divided into clusters of narrative components, then the valence scores of each components were calculated. This provided the quantitative data of what components were leading the players’ perceptions of the games, and how the players approached to each cluster sentimentally. However to understand the player types, a proximity analysis was performed on valence/cluster data. This analysis outlined five narrative player types. Tracing back to manually analysing selected reviews of these types, the types were named and their behaviours were explained through the clusters that they demonstrated low, high, and median valence scores to.

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