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Identification and impact of discoverers in online social systems.

ABSTRACT: Understanding the behavior of users in online systems is of essential importance for sociology, system design, e-commerce, and beyond. Most existing models assume that individuals in diverse systems, ranging from social networks to e-commerce platforms, tend to what is already popular. We propose a statistical time-aware framework to identify the users who differ from the usual behavior by being repeatedly and persistently among the first to collect the items that later become hugely popular. Since these users effectively discover future hits, we refer them as discoverers. We use the proposed framework to demonstrate that discoverers are present in a wide range of real systems. Once identified, discoverers can be used to predict the future success of new items. We finally introduce a simple network model which reproduces the discovery patterns observed in the real data. Our results open the door to quantitative study of detailed temporal patterns in social systems.

SUBMITTER: Medo M

PROVIDER: S-EPMC5043231 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Identification and impact of discoverers in online social systems.

Medo Matúš M Mariani Manuel S MS Zeng An A Zhang Yi-Cheng YC

Scientific reports 20160930

Understanding the behavior of users in online systems is of essential importance for sociology, system design, e-commerce, and beyond. Most existing models assume that individuals in diverse systems, ranging from social networks to e-commerce platforms, tend to what is already popular. We propose a statistical time-aware framework to identify the users who differ from the usual behavior by being repeatedly and persistently among the first to collect the items that later become hugely popular. Si ...[more]

PMID: 27687588

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Project description:BackgroundMedication is the most common intervention in health care, and the number of online consumer information systems within the pharmaceutical sector is increasing. However, online consumer information systems can be a barrier for users, imposing information asymmetries between stakeholders.ObjectiveThe objective of this study was to quantify and compare the usability of an online consumer medication information system (OCMIS) against a reference implementation based on an interoperable information model for patients, physicians, and pharmacists.MethodsQuantitative and qualitative data were acquired from patients, physicians, and pharmacists in this online usability study. We administered 3 use cases and a post hoc questionnaire per user. Quantitative usability data including effectiveness (task success), efficiency (task time), and user satisfaction (system usability scale [SUS]) was complemented by qualitative and demographic data. Users evaluated 6 existing systems and 1 reference implementation of an OCMIS.ResultsA total of 137 patients, 81 physicians, and 68 pharmacists participated in this study. Task success varied from 84% to 92% in patients, 66% to 100% in physicians, and 50% to 91% in pharmacists. Task completion time decreased over the course of the study for all but 2 OCMIS within the patient group. Due to an assumed nonnormal distribution of SUS scores, within-group comparison was done using the Kruskal-Wallis test. Patients showed differences in SUS scores (P=.02) and task time (P=.03), while physicians did not have significant differences in SUS scores (P=.83) and task time (P=.72). For pharmacists, a significant difference in SUS scores (P<.001) and task time (P=.007) was detected.ConclusionsThe vendor-neutral reference implementation based on an interoperable information model was proven to be a promising approach that was not inferior to existing solutions for patients and physicians. For pharmacists, it exceeded user satisfaction scores compared to other OCMIS. This data-driven approach based on an interoperable information model enables the development of more user-tailored features to increase usability. This fosters data democratization and empowers stakeholders within the pharmaceutical sector.

Dataset Information

Identification and impact of discoverers in online social systems.

Publications

Identification and impact of discoverers in online social systems.

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