Title:
Affected States: Analysis and Sonification of Twitter Music Trends

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Ash, Kingsley
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Abstract
This paper describes an approach to the sonification of real- time twitter music trend data realized for the ICAD 2012 Sonification Competition: Listening to the World Listening. The paper will discuss the techniques used to create the sonification and the motivations behind them, including details of the data analysis, mapping strategies, visual display and sonification output. The system analyses the Twitter Music Trends data feed, which aggregates music listening data from Twitter by artist, as well as the Echo Nest REST API to determine the perceived emotional affect and prevailing descriptions of a selection of the latest trending artists. The resulting data is visualized and sonified in real-time to facilitate analysis and generate an appealing visual and auditory display of the resulting data. Experience with the system suggests that it is successful in allowing users to determine perceived emotional affect and quality for a number of artists simultaneously, and could allow further investigation into the correlation between these factors. The system also generates appealing visual music that reaches beyond the practice of scientific investigation to reach out to a wider audience.
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Leeds Metropolitan University
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2012-06
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