Detecting the influencer on social networks using passion point and measures of information propagation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10245624" target="_blank" >RIV/61989100:27240/20:10245624 - isvavai.cz</a>

Alternative codes found

RIV/61989100:27740/20:10245624

Result on the web

<a href="https://www.mdpi.com/2071-1050/12/7/3064" target="_blank" >https://www.mdpi.com/2071-1050/12/7/3064</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/su12073064" target="_blank" >10.3390/su12073064</a>

Result language

angličtina

Original language name

Detecting the influencer on social networks using passion point and measures of information propagation

Original language description

Influencer marketing is a modern method that uses influential users to approach goal customers easily and quickly. An online social network is a useful platform to detect the most effective influencer for a brand. Thus, we have an issue: how can we extract user data to determine an influencer? In this paper, a model for representing a social network based on users, tags, and the relationships among them, called the SNet model, is presented. A graph-based approach for computing the impact of users and the speed of information propagation, and measuring the favorite brand of a user and sharing the similar brand characteristics, called a passion point, is proposed. Therefore, we consider two main influential measures, including the extent of the influence on other people by the relationships between users and the concern to user&apos;s tags, and the tag propagation through social pulse on the social network. Based on these, the problem of determining the influencer of a specific brand on a social network is solved. The results of this method are used to run the influencer marketing strategy in practice and have obtained positive results. (C) 2020 by the authors.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10200 - Computer and information sciences

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

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

Name of the periodical

Sustainability

ISSN

2071-1050

e-ISSN

—

Volume of the periodical

12

Issue of the periodical within the volume

7

Country of publishing house

CH - SWITZERLAND

Number of pages

16

Pages from-to

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UT code for WoS article

000531558100489

EID of the result in the Scopus database

2-s2.0-85083559736