Master of Arts
Dr. Scott Schaffer
This visually thematic qualitative case analysis seeks to advance cyber-sociology by analyzing the hyper-under-attended relationship between interfaces and discourses. Here, the interface under investigation is the Apple App Store, examined for the ways in which the platform is discursively encoded with particular ideologies, ideals, desires and narratives downloaded onto users as they download applications. Such is explored via a two-part research question inquiring: Which type of applications enjoy the most promotion on the Apple App Store and what cyber-architectural tools are herein used to optically exalt them? To investigate this, an iOS 11-operating iPhone was used to frequent the store’s “Today” section over a period of twelve weeks — a segment of the platform manually curated by Apple employees. Data was analyzed on Microsoft Excel, coded by an overarching theme of self-optimization, as well as the subsidiary themes of self-reliance, self-improvement, corporeal regulation, social capital, and non-self-optimization miscellaneous. Findings reveal that promotion on the App Store is not neutrally distributed, as applications oscillating around the behaviour of self-optimization takes promotive spotlight over play-centric and/or miscellaneous mobile programs. Stanfill’s (2015) “interface-as-discourse” framework theoretically informs this paper, with her work later situated in intertextual conversation with Han’s (2010) “achievement societies” and “auto-exploitation”. A discussion section introduces the neologisms “iDeologies” and “technographing” to conceptualize results. This paper concludes with an emphasis on the significance of the interface-discourse nexus to sociology, as these virtual platforms – shot through with top-down ideologies picked bottom-up– complicate the canon’s structure-versus-agency debate in its failure to be slotted into the binary.
Yusuf, Ismahan, "An App a Day Keeps the Doctor Away: A Visual Case Analysis of the Self-Optimization Ideologies Downloaded onto Apple Users as They Download Applications" (2019). MA Research Paper. 32.