Who creates trends in online social media.

The crowd or opinion leaders?

Leihan Zhang, Jichang Zhao and Ke Xu1

Amir Razmjou

Computer Science Student (MSc)

Azad University of Mahshahr (2007)

Business Intelligence Developer

Microsoft CRM WISP – Firewall Developer Microchip Embedded

Programmer

Brief Introduction

Swarm IntelligenceNetwork SecurityCloud InfrastructureComplex Networks

Influential hypothesis (Past)In the 1940s and 1950s, Paul Lazarsfeld, Elihu Katz, and colleagues (Katz and Lazarsfeld 1955; Lazarsfeld, Berelson, and Gaudet 1968) formulated a breakthrough theory of public opinion formation

Information Diffusion? (Now)

We are going to challenge Influential hypothesis by comparison of two Paradigms in two different eras

Influential hypothesis

Small minority of “opinion leaders”– stars, act as intermediaries between the mass media and the majority of society (circles)Two‐step flow• The “dominant paradigm” of media

sociology in 70s

In business and marketing, the idea that a small group of influential opinion leaders may accelerate or block the adoption of a product is central to a large number of studies

Individuals may be influenced more by exposure to each other than to the media

Duncan J. Watts 2007

Shortcomings of Influential hypothesis • Most devoted to inspection of underlying mechanism

not considering the time dimension.• It’s doesn’t belong to information age.

• The Internet• Micro-Blogging• While at the same time, the big-data of behavioral

records in online social media• Lehmann: Not taking into account external factors,

geographical location of people, their mood. • The traditional two-step flow theory is not applicable in

online social networks and the role of influential might be over-emphasized

• High popularity do not always imply high influence but relationship among ordinary users and the readiness of the social network to accept a novel item

• Harrigan et al. also find that it is the network structure not hubs that can substantially increase social the spreading of a message.

LOST IN TIME AND SPACE

Frequency of slang words over time

Innovator

Early Majority

Early Adaptors

Late Majority

Laggard

• The jump in the occupation of users with of number of followers around 10^5 in p1 represents the failed diffusion.

• crowd’s participation in the early stage of the propagation can produce a massive diffusion. On the contrary, domination of opinion leaders in the early stage cannot guarantee the

• All the results are averaged over the entire set of slang words

• How come that contribution of users decreases substantially after specific number of followers?

How did we find the effective number followers? (~232)

It again demonstrates the fact that ordinary users occupy greater

proportion than opinion leaders for p2

The threshold we find here is close to Dunbar’s number

CDF curve of p2 exceeds the curve of p1 for small #Follower

It is in agreement with the existing hypothesis that a global trend is beginning from many small-scale trends and the population number of an efficient group launching small-scale trends shall be less than Dunbar’s number

Questions?