Identifying the perceptive users for online social systems.

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 o...

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Main Authors: Jian-Guo Liu, Xiao-Lu Liu, Qiang Guo, Jing-Ti Han
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5509131?pdf=render
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author Jian-Guo Liu
Xiao-Lu Liu
Qiang Guo
Jing-Ti Han
author_facet Jian-Guo Liu
Xiao-Lu Liu
Qiang Guo
Jing-Ti Han
author_sort Jian-Guo Liu
collection DOAJ
description 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.
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spelling doaj.art-893a8691fb4b4182a6d1f1a26c46c3eb2022-12-22T00:31:21ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01127e017811810.1371/journal.pone.0178118Identifying the perceptive users for online social systems.Jian-Guo LiuXiao-Lu LiuQiang GuoJing-Ti HanIn 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.http://europepmc.org/articles/PMC5509131?pdf=render
spellingShingle Jian-Guo Liu
Xiao-Lu Liu
Qiang Guo
Jing-Ti Han
Identifying the perceptive users for online social systems.
PLoS ONE
title Identifying the perceptive users for online social systems.
title_full Identifying the perceptive users for online social systems.
title_fullStr Identifying the perceptive users for online social systems.
title_full_unstemmed Identifying the perceptive users for online social systems.
title_short Identifying the perceptive users for online social systems.
title_sort identifying the perceptive users for online social systems
url http://europepmc.org/articles/PMC5509131?pdf=render
work_keys_str_mv AT jianguoliu identifyingtheperceptiveusersforonlinesocialsystems
AT xiaoluliu identifyingtheperceptiveusersforonlinesocialsystems
AT qiangguo identifyingtheperceptiveusersforonlinesocialsystems
AT jingtihan identifyingtheperceptiveusersforonlinesocialsystems