Collecting, organizing, and sharing pins in pinterest: Interest-driven or social-driven?

Jinyoung Han, Daejin Choi, Byung Gon Chun, Ted Taekyoung Kwon, Hyun Chul Kim, Yanghee Choi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationSIGMETRICS 2014 - Proceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
PublisherAssociation for Computing Machinery
Pages15-27
Number of pages13
ISBN (Print)9781450327893
DOIs
StatePublished - 2014
Event2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2014 - Austin, TX, United States
Duration: 16 Jun 201420 Jun 2014

Publication series

NameSIGMETRICS 2014 - Proceedings of the 2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems

Conference

Conference2014 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2014
Country/TerritoryUnited States
CityAustin, TX
Period16/06/1420/06/14

Keywords

  • Content Propagation
  • Online Social Network
  • Pinterest
  • Repin
  • Social Curating

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