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Unformatted text preview: Information Dynamics in the Networked World Bernardo A. Huberman and Lada A. Adamic HP Labs, 1501 Page Mill Road, Palo Alto CA 94304, USA Abstract. We review three studies of information ﬂow in social networks that help reveal their underlying social structure, how information spreads among them and why small world experiments work. 1 Introduction The problem of information ﬂows in social organizations is relevant to issues of productivity, innovation and the sorting out of useful ideas from the general chatter of a community. How information spreads determines the speed by which individuals can act and plan their future activities. Moreover, information ﬂows take place within social networks whose nature is sometimes diﬃcult to establish. This is because the network itself is sometimes different from what one would infer from the formal structure of the group or organization. The advent of email as the predominant means of communication in the information society now offers a unique opportunity to observe the ﬂow of in- formation along both formal and informal channels. Not surprisingly, email has been established as an indicator of collaboration and knowledge exchange [1–5]. Email is also a good medium for social network research because it provides plentiful data on personal communication in an electronic form. This volume of data enables the discovery of shared interests and relationships where none were previously known . In this chapter we will review three studies that utilized networks exposed by email communication. In all three studies, the networks analyzed were derived from email messages sent through the Hewlett Packard Labs email server over the period of several months in 2002 and 2003. The first study, by Tyler et al. , develops an automated method applying a betweenness centrality algorithm to rapidly identify communities, both formal and informal, within the network. This approach also enables the identification of leadership roles within the com- munities. The automated analysis was complemented by a qualitative evaluation of the results in the field. The second study, by Wu et al.  analyzes email patterns to model infor- mation ﬂow in social groups, taking into account the observation that an item relevant to one person is more likely to be of interest to individuals in the same social circle than those outside of it. This is due to the fact that the similarity of node attributes in social networks decreases as a function of the graph dis- B.A. Huberman and L.A. Adamic, Information Dynamics in the Networked World, Lect. Notes Phys. 650 , 371–398 (2004) http://www.springerlink.com/ c ≥ Springer-Verlag Berlin Heidelberg 2004 372 B.A. Huberman and L.A. Adamic tance. An epidemic model on a scale-free network with this property has a finite threshold, implying that the spread of information is limited. These predictions were tested by measuring the spread of messages in an organization and also by numerical experiments that take into consideration the organizational distance...
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This note was uploaded on 12/27/2011 for the course CMPSC 290a taught by Professor Vandam during the Fall '09 term at UCSB.
- Fall '09