Evidence map›Paper›PMID 28704382›Full record

ArticlePloS one2017

Identifying the perceptive users for online social systems.

Jian-Guo Liu, Xiao-Lu Liu, Qiang Guo, Jing-Ti Han

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jian-Guo LiuData Science and Cloud Service Research Centre, Shanghai University of Finance and Economics, Shanghai 200433, PR China.ORCID http://orcid.org/0000-0002-5641-0266
Xiao-Lu LiuResearch Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, PR China.
Qiang GuoResearch Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093, PR China.
Jing-Ti HanData Science and Cloud Service Research Centre, Shanghai University of Finance and Economics, Shanghai 200433, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Interpersonal RelationsModels, PsychologicalHumansInternetModels, StatisticalOnline SystemsSocial MediaSocial Support

Identifiers

PMID28704382
PMCPMC5509131

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.