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GAP: Geometric Aggregation of Popularity Metrics

Information Technologies Institute, Centre of Research and Technology Hellas, 6th km Harilaou-Thermi, 57001 Thessaloniki, Greece
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Information 2020, 11(6), 323; https://doi.org/10.3390/info11060323
Received: 13 May 2020 / Revised: 8 June 2020 / Accepted: 11 June 2020 / Published: 15 June 2020
Estimating and analyzing the popularity of an entity is an important task for professionals in several areas, e.g., music, social media, and cinema. Furthermore, the ample availability of online data should enhance our insights into the collective consumer behavior. However, effectively modeling popularity and integrating diverse data sources are very challenging problems with no consensus on the optimal approach to tackle them. To this end, we propose a non-linear method for popularity metric aggregation based on geometrical shapes derived from the individual metrics’ values, termed Geometric Aggregation of Popularity metrics (GAP). In this work, we particularly focus on the estimation of artist popularity by aggregating web-based artist popularity metrics. Finally, even though the most natural choice for metric aggregation would be a linear model, our approach leads to stronger rank correlation and non-linear correlation scores compared to linear aggregation schemes. More precisely, our approach outperforms the simple average method in five out of seven evaluation measures. View Full-Text
Keywords: metric aggregation; multivariate analysis; popularity estimation metric aggregation; multivariate analysis; popularity estimation
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Koutlis, C.; Schinas, M.; Papadopoulos, S.; Kompatsiaris, I. GAP: Geometric Aggregation of Popularity Metrics. Information 2020, 11, 323.

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