TY - GEN
T1 - Collecting, organizing, and sharing pins in pinterest
T2 - 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2014
AU - Han, Jinyoung
AU - Choi, Daejin
AU - Chun, Byung Gon
AU - Kwon, Ted Taekyoung
AU - Kim, Hyun Chul
AU - Choi, Yanghee
PY - 2014
Y1 - 2014
N2 - Pinterest, a popular social curating service where people collect, organize, and share content (pins in Pinterest), has gained great attention in recent years. Despite the increasing interest in Pinterest, little research has paid attention to how people collect, manage, and share pins in Pinterest. In this paper, to shed insight on such issues, we study the following questions. How do people collect and manage pins by their tastes in Pinterest? What factors do mainly drive people to share their pins in Pinterest? How do the characteristics of users (e.g., gender, popularity, country) or properties of pins (e.g., category, topic) play roles in propagating pins in Pinterest? To answer these questions, we have conducted a measurement study on patterns of pin curating and sharing in Pinterest. By keeping track of all the newly posted and shared pins in each category (e.g., animal, kids, women's fashion) from June 5 to July 18, 2013, we built 350 K pin propagation trees for 3 M users. With the dataset, we investigate: (1) how users collect and curate pins, (2) how users share their pins and why, and (3) how users are related by shared pins of interest. Our key finding is that pin propagation in Pinterest is mostly driven by pin's properties like its topic, not by user's characteristics like her number of followers. We further show that users in the same community in the interest graph (i.e., representing the relations among users) of Pinterest share pins (i) in the same category with 94% probability and (ii) of the same URL where pins come from with 89% probability. Finally, we explore the implications of our findings for predicting how pins are shared in Pinterest.
AB - Pinterest, a popular social curating service where people collect, organize, and share content (pins in Pinterest), has gained great attention in recent years. Despite the increasing interest in Pinterest, little research has paid attention to how people collect, manage, and share pins in Pinterest. In this paper, to shed insight on such issues, we study the following questions. How do people collect and manage pins by their tastes in Pinterest? What factors do mainly drive people to share their pins in Pinterest? How do the characteristics of users (e.g., gender, popularity, country) or properties of pins (e.g., category, topic) play roles in propagating pins in Pinterest? To answer these questions, we have conducted a measurement study on patterns of pin curating and sharing in Pinterest. By keeping track of all the newly posted and shared pins in each category (e.g., animal, kids, women's fashion) from June 5 to July 18, 2013, we built 350 K pin propagation trees for 3 M users. With the dataset, we investigate: (1) how users collect and curate pins, (2) how users share their pins and why, and (3) how users are related by shared pins of interest. Our key finding is that pin propagation in Pinterest is mostly driven by pin's properties like its topic, not by user's characteristics like her number of followers. We further show that users in the same community in the interest graph (i.e., representing the relations among users) of Pinterest share pins (i) in the same category with 94% probability and (ii) of the same URL where pins come from with 89% probability. Finally, we explore the implications of our findings for predicting how pins are shared in Pinterest.
KW - Content Propagation
KW - Online Social Network
KW - Pinterest
KW - Repin
KW - Social Curating
UR - https://www.scopus.com/pages/publications/84904329754
U2 - 10.1145/2591971.2591996
DO - 10.1145/2591971.2591996
M3 - Conference contribution
AN - SCOPUS:84904329754
SN - 9781450327893
T3 - SIGMETRICS 2014 - Proceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
SP - 15
EP - 27
BT - SIGMETRICS 2014 - Proceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
PB - Association for Computing Machinery
Y2 - 16 June 2014 through 20 June 2014
ER -