Showing papers by "Duncan J. Watts published in 2008"
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TL;DR: This work forms a temporal notion of "distance" in the underlying social network by measuring the minimum time required for information to spread from one node to another - a concept that draws on the notion of vector-clocks from the study of distributed computing systems.
Abstract: Social networks are of interest to researchers in part because they are thought to mediate the flow of information in communities and organizations. Here we study the temporal dynamics of communication using on-line data, including e-mail communication among the faculty and staff of a large university over a two-year period. We formulate a temporal notion of "distance" in the underlying social network by measuring the minimum time required for information to spread from one node to another -- a concept that draws on the notion of vector-clocks from the study of distributed computing systems. We find that such temporal measures provide structural insights that are not apparent from analyses of the pure social network topology. In particular, we define the network backbone to be the subgraph consisting of edges on which information has the potential to flow the quickest. We find that the backbone is a sparse graph with a concentration of both highly embedded edges and long-range bridges -- a finding that sheds new light on the relationship between tie strength and connectivity in social networks.
317 citations
24 Aug 2008
TL;DR: In this article, the authors study the temporal dynamics of communication using on-line data, including e-mail communication among the faculty and staff of a large university over a two-year period.
Abstract: Social networks are of interest to researchers in part because they are thought to mediate the flow of information in communities and organizations. Here we study the temporal dynamics of communication using on-line data, including e-mail communication among the faculty and staff of a large university over a two-year period. We formulate a temporal notion of "distance" in the underlying social network by measuring the minimum time required for information to spread from one node to another - a concept that draws on the notion of vector-clocks from the study of distributed computing systems. We find that such temporal measures provide structural insights that are not apparent from analyses of the pure social network topology. In particular, we define the network backbone to be the subgraph consisting of edges on which information has the potential to flow the quickest. We find that the backbone is a sparse graph with a concentration of both highly embedded edges and long-range bridges - a finding that sheds new light on the relationship between tie strength and connectivity in social networks.
312 citations
TL;DR: It is found that most songs experienced self-ful- filling prophecies, in which perceived—but initially false—popularity became real over time, and the distortion of market information reduced the correlation between appeal and popularity, and led to fewer overall downloads.
Abstract: Individuals influence each others' decisions about cultural products such as songs, books, and movies; but to what extent can the perception of success become a "self-fulfilling prophecy"? We have explored this question experimentally by artificially inverting the true popularity of songs in an online "music market," in which 12,207 participants listened to and downloaded songs by unknown bands. We found that most songs experienced self-fulfilling prophecies, in which perceived-but initially false-popularity became real over time. We also found, however, that the inversion was not self-fulfilling for the market as a whole, in part because the very best songs recovered their popularity in the long run. Moreover, the distortion of market information reduced the correlation between appeal and popularity, and led to fewer overall downloads. These results, although partial and speculative, suggest a new approach to the study of cultural markets, and indicate the potential of web-based experiments to explore the social psychological origin of other macro-sociological phenomena.
242 citations
TL;DR: In this paper, the authors address the general question of how social influence determines collective outcomes for large populations of individuals faced with binary decisions, and define conditions under which the behavior of individuals making binary decisions can be described in terms of what they call an influence-response function: a one-dimensional function of the weighted number of individuals choosing each of the alternatives.
Abstract: In this paper we address the general question of how social influence determines collective outcomes for large populations of individuals faced with binary decisions. First, we define conditions under which the behavior of individuals making binary decisions can be described in terms of what we call an influence-response function: a one-dimensional function of the (weighted) number of individuals choosing each of the alternatives. And second, we demonstrate that, under the assumptions of global and anonymous interactions, general knowledge of the influence-response functions is sufficient to compute equilibrium, and even non-equilibrium, properties of the collective dynamics. By enabling us to treat in a consistent manner classes of decisions that have previously been analyzed separately, our framework allows us to find similarities between apparently quite different kinds of decision situations, and conversely to identify important differences between decisions that would otherwise appear very similar.
124 citations
30 Sep 2008
TL;DR: In this article, the authors present the Six Degrees: The New Science of Networks (Sociology, W3233, Spring 2006) and the syllabus of the course.
Abstract: Six Degrees: The New Science of Networks (Sociology, W3233, Spring 2006)
Original URL: http://cdg.columbia.edu/cdg/courses/spring06/sixDegrees/syllabus.jsp
7 citations