Identifying the perceptive users for online social systems

PLoS One. 2017 Jul 13;12(7):e0178118. doi: 10.1371/journal.pone.0178118. eCollection 2017.

Abstract

In this paper, the perceptive user, who could identify the high-quality objects in their initial lifespan, is presented. By tracking the ratings given to the rewarded objects, we present a method to identify the user perceptibility, which is defined as the capability that a user can identify these objects at their early lifespan. Moreover, we investigate the behavior patterns of the perceptive users from three dimensions: User activity, correlation characteristics of user rating series and user reputation. The experimental results for the empirical networks indicate that high perceptibility users show significantly different behavior patterns with the others: Having larger degree, stronger correlation of rating series and higher reputation. Furthermore, in view of the hysteresis in finding the rewarded objects, we present a general framework for identifying the high perceptibility users based on user behavior patterns. The experimental results show that this work is helpful for deeply understanding the collective behavior patterns for online users.

MeSH terms

  • Humans
  • Internet
  • Interpersonal Relations*
  • Models, Psychological*
  • Models, Statistical
  • Online Systems
  • Social Media
  • Social Support

Grants and funding

This work is supported by the National Natural Science Foundation of China (Grant Nos. 71271126, 61374177, 71371125), the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, the Shuguang Program Project of Shanghai Educational Committee (Grant No. 14SG42).