Influence and Passivity in Social Media

9 Pages Posted: 4 Aug 2010

See all articles by Daniel M. Romero

Daniel M. Romero

Hewlett-Packard Laboratories, Bristol

Wojciech Galuba

École Polytechnique Fédérale de Lausanne

Sitaram Asur

Hewlett-Packard Laboratories, Palo Alto

Bernardo A. Huberman

CableLabs

Date Written: August 4, 2010

Abstract

The ever-increasing amount of information owing through Social Media forces the members of these networks to compete for attention and influence by relying on other peopleto spread their message. A large study of information propagation within Twitter reveals that the majority of users act as passive information consumers and do not forward the content to the network. Therefore, in order for individuals to become influential they must not only obtain attention and thus be popular, but also overcome user passivity. We propose an algorithm that determines the influence and passivity of users based on their information forwarding activity. An evaluation performed with a 2.5 million user dataset shows that our influence measure is a good predictor of URL clicks, outperforming several other measures that do not explicitly take user passivity into account. We also explicitly demonstrate that high popularity does not necessarily imply high influence and vice-versa.

Suggested Citation

Romero, Daniel M. and Galuba, Wojciech and Asur, Sitaram and Huberman, Bernardo A., Influence and Passivity in Social Media (August 4, 2010). Available at SSRN: https://ssrn.com/abstract=1653135 or http://dx.doi.org/10.2139/ssrn.1653135

Daniel M. Romero

Hewlett-Packard Laboratories, Bristol ( email )

Bristol
United Kingdom

Wojciech Galuba

École Polytechnique Fédérale de Lausanne ( email )

Station 5
Odyssea 1.04
1015 Lausanne, CH-1015
Switzerland

Sitaram Asur

Hewlett-Packard Laboratories, Palo Alto ( email )

1501 Page Mill Road
Palo Alto, CA 94301
United States

Bernardo A. Huberman (Contact Author)

CableLabs ( email )

400 W California Ave
Sunnyvale, CA 94086
United States

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