Models of influence in online social networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092751" target="_blank" >RIV/61989100:27240/14:86092751 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1002/int.21631" target="_blank" >http://dx.doi.org/10.1002/int.21631</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/int.21631" target="_blank" >10.1002/int.21631</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Models of influence in online social networks

Popis výsledku v původním jazyce

Online social networks gained their popularity from relationships users can build with each other. These social ties play an important role in asserting users' behaviors in a social network. For example, a user might purchase a product that his friend recently bought. Such phenomenon is called social influence, which is used to study users' behavior when the action of one user can affect the behavior of his neighbors in a social network. Social influence is increasingly investigated nowadays as it can help spreading messages widely, particularly in the context of marketing, to rapidly promote products and services based on social friends' behavior in the network. This wide interest in social influence raises the need to develop models to evaluate the rate of social influence. In this paper, we discuss metrics used to measure influence probabilities. Then, we reveal means to maximize social influence by identifying and using the most influential users in a social network. Along with the

Název v anglickém jazyce

Models of influence in online social networks

Popis výsledku anglicky

Online social networks gained their popularity from relationships users can build with each other. These social ties play an important role in asserting users' behaviors in a social network. For example, a user might purchase a product that his friend recently bought. Such phenomenon is called social influence, which is used to study users' behavior when the action of one user can affect the behavior of his neighbors in a social network. Social influence is increasingly investigated nowadays as it can help spreading messages widely, particularly in the context of marketing, to rapidly promote products and services based on social friends' behavior in the network. This wide interest in social influence raises the need to develop models to evaluate the rate of social influence. In this paper, we discuss metrics used to measure influence probabilities. Then, we reveal means to maximize social influence by identifying and using the most influential users in a social network. Along with the

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Intelligent Systems

ISSN

0884-8173

e-ISSN

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Svazek periodika

29

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

23

Strana od-do

161-183

Kód UT WoS článku

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EID výsledku v databázi Scopus

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