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New Keys for the Diffusion of Information in Social Networks
11 September 2009
Universidad Carlos III de Madrid - Oficina de Información Científica
The spread of information in social networks, something of crucial importance in awareness and marketing campaigns or the spreading of rumours and viruses, for example, is largely determined by the great heterogeneity of internauts in their response time, according to the researchers. Traditional models estimated that internauts respond in approximately one day and that, as such, it took one day for information to be transmitted. However, this study, based on an actual experiment by IBM to observe and quantify the spread of business information in social networks, points out that it occurs at two speeds due to user activity. “Those who respond very quickly to e-mails, technology addicts who are always connected, are the ones responsible for spreading certain rumours or campaigns quickly via Internet,” notes Esteban Moro, professor of Mathematics at the UC3M.
In this light, if information is so interesting that it reaches many people, the diffusion is faster because these people quickly forward the message. This explains why some computer viruses quickly spread via e-mail in a matter of hours, despite the fact that the email response time is one day. However, if information is not so interesting, the diffusion is slower because it is controlled by those persons who take a long time to respond; this causes some rumours or bits of information to remain dormant in social networks a long time after they are released. The study has been published by Esteban Moro and José Luis Iribarren, interactive marketing manager of IBM for Europe, in Physical Review Letters, one of the most famous interdisciplinary scientific journals in Physics.
The Mathematics of the Spread of Information
The mathematical models that these researchers have created explain why viral campaigns take so long to work and even assess their possible impact. “With this experience, we have been able to predict, within a small margin of error, how many people will receive the information and how long it will take to reach them. It is the first time that we have come up with quantitative models which enable us to predict what is happening,” states Moro. The quality of the data allows for a mathematical modelling of viral campaigns via branching processes which, for their part, add the researchers, corroborate the predominant role of heterogeneity in social networks where the spread of information is concerned.
To reach these conclusions, the promoters of the study analyzed the results of a set of viral marketing campaigns designed by Iribarren for IBM. Over 30,000 people from 11 European countries participated in the campaigns, which consisted of the classical model of recommending a friend. A news bulletin from the company itself was released so that people could subscribe via a form which, after completed, included the option of recommending the subscription to another person. To increase recommendation, there was a contest which featured a prize draw for a laptop computer among those who had forwarded the information. This campaign also served to verify that citizens of Mediterranean countries, especially Spain and Italy, are more willing to put down their personal data on this type of form than people from Northern European countries, who are much more reluctant to comply with these on-line requirements.
Dinámica temporal de la mayor cascada de propagación viral (en España). Cada gráfico representa una foto de la cascada a diferentes tiempos. Los círculos representan los participantes en las campañas y las flechas describen como se propagó el mensaje. Los colores son sencillamente una ayuda para interpretar los diferentes estadíos de la propagación
Final state of the propagation cascade shown in the previous graph. The circle in black represents the person who initiated the viral propagation. The gray circles are those persons who received the message and forwarded it to other persons, and the white circles are those who received the message but did not forward it.