Abstract
This research seeks to answer the question of how information relevance arises in algorithmic media. The term algorithmic media is a generic term for digital applications that personalize information on the basis of algorithmic procedures. Information relevance in this context describes the process by which certain information achieve extended visibility. Current research in the area has given valuable insights into how algorithms shape everyday information practices and what their implications are on a broader social and cultural level. The principal understanding of algorithms critical social research is generally based on is a mathematical-theoretical one: algorithms are defined as mechanical step-by-step instructions. In relation to the research object of this study, however, it can be stated that algorithms operate by analyzing user behavior. The goal of
this research is therefore to establish a perspective that takes the crucial component of user behavior into account. It thereby aims to create an application-based understanding of information relevance in algorithmic media centered around the algorithm-user-relationship.
Theoretical starting point is the development of a communication perspective on information relevance in algorithmic media. Algorithms and users are hence conceptualized as communicative others that are connected by a communicative relationship. This communicative relationship is then investigated further empirically. Drawing on 25 expert interviews, analyzed following a qualitative coding process, four communicative dynamics that shape algorithm-user-communication were identified: (1) the functional-strategic dynamic; (2) the narrative dynamic; (3) the knowledge-awareness dynamic; and (4) the action dynamic. Combining the theoretical and empirical insights results in a morphological model that visualizes information relevance in algorithmic
media. With this model, this research contributes with a novel basis for examining and discussing algorithmic procedures in the digital realm.
this research is therefore to establish a perspective that takes the crucial component of user behavior into account. It thereby aims to create an application-based understanding of information relevance in algorithmic media centered around the algorithm-user-relationship.
Theoretical starting point is the development of a communication perspective on information relevance in algorithmic media. Algorithms and users are hence conceptualized as communicative others that are connected by a communicative relationship. This communicative relationship is then investigated further empirically. Drawing on 25 expert interviews, analyzed following a qualitative coding process, four communicative dynamics that shape algorithm-user-communication were identified: (1) the functional-strategic dynamic; (2) the narrative dynamic; (3) the knowledge-awareness dynamic; and (4) the action dynamic. Combining the theoretical and empirical insights results in a morphological model that visualizes information relevance in algorithmic
media. With this model, this research contributes with a novel basis for examining and discussing algorithmic procedures in the digital realm.
Original language | English |
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Publisher | Universität Erfurt |
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Number of pages | 213 |
Publication status | Published - 18 Dec 2017 |
Externally published | Yes |