Media marketers and researchers have shown great interest in what becomes a trend within social media sites. Their interests have focused on analyzing the items that become trends, and done so in the context of Youtube, Twitter, and Foursquare. Here we move away from these three platforms and consider a new mobile social-networking application with which users share pictures of "cool" things they find in the real-world. Besides, we shift focus from items to people. Specifically, we focus on those who generate trends (trend makers) and those who spread them (trend spotters). We analyze the complete dataset of user interactions, and characterize trend makers (spotters) by activity, geographical, and demographic features. We find that there are key characteristics that distinguish them from typical users. Also, we provide statistical models that accurately identify who is a trend maker (spotter). These contributions not only expand current studies on trends in social media but also promise to inform the design of recommender systems, and new products. Copyright 2013 ACM.

Trend makers and trend spotters in a mobile application

Dell'amico M.;
2013-01-01

Abstract

Media marketers and researchers have shown great interest in what becomes a trend within social media sites. Their interests have focused on analyzing the items that become trends, and done so in the context of Youtube, Twitter, and Foursquare. Here we move away from these three platforms and consider a new mobile social-networking application with which users share pictures of "cool" things they find in the real-world. Besides, we shift focus from items to people. Specifically, we focus on those who generate trends (trend makers) and those who spread them (trend spotters). We analyze the complete dataset of user interactions, and characterize trend makers (spotters) by activity, geographical, and demographic features. We find that there are key characteristics that distinguish them from typical users. Also, we provide statistical models that accurately identify who is a trend maker (spotter). These contributions not only expand current studies on trends in social media but also promise to inform the design of recommender systems, and new products. Copyright 2013 ACM.
2013
9781450313315
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1070974
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