D 2014

Viral Video Diffusion in a Fixed Social Network: An Agent-based Model

KVASNIČKA, Michal

Basic information

Original name

Viral Video Diffusion in a Fixed Social Network: An Agent-based Model

Name in Czech

Šíření virálního videa fixní sociální sítí: multiagentový model

Authors

KVASNIČKA, Michal (203 Czech Republic, guarantor, belonging to the institution)

Edition

Holland, Procedia Economics and Finance 12 ( 2014), p. 334-342, 9 pp. 2014

Publisher

Elsevier

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

50200 5.2 Economics and Business

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14560/14:00076474

Organization unit

Faculty of Economics and Administration

ISSN

UT WoS

000345439100040

Keywords (in Czech)

virální video; viralní marketing; sociální síť; multiagentový model

Keywords in English

viral video; viral marketing; social network; agent-based model

Tags

International impact, Reviewed
Změněno: 12/8/2020 14:12, Mgr. Michal Petr

Abstract

V originále

Agent-based computational papers on viral marketing have been so far focused on the study of the word-of-mouth knowledge diffusion, and hence merged the decisions to adopt a product and to share information about it. This approach does not seem to capture well the properties of viral videos which are shared with no regard whether the sender has adopted the product. This paper presents the first model of such knowledge diffusion. The model consists of an artificial social network (a mix of small world and power network) that mimics the properties of empirical social networks and a model of node activation where every node that viewed the viral video shares it with a random subset of her neighbors just once. The results of the simulation show that there is a phase transition: in one phase, almost no agents view the viral video, in the other one, a great part of the whole population does. When the second phase occurs, the diffusion of the knowledge in time resembles that of Bass model. What phase occurs and how many agents view the content depend above all on how “catchy” the video is. Other marketing practices as selecting the seed of the first addressed agents are of secondary importance. The marketer can choose between addressing fewer more connected agents or more agents with fewer connections. If the video is “catchy”, then a small number of the first addressed agents is sufficient even when the agents are selected randomly.

Links

MUNI/A/0781/2013, interní kód MU
Name: Regulace trhu dopravních služeb – modely, metody a aplikace (Acronym: ReDoS)
Investor: Masaryk University, Category A