Scale-free network. A scale-free network is a network whose degree distribution follows a power law, at least asymptotically. That is, the fraction P(k) of nodes in the network having k connections to other nodes goes for large values of k as where is a parameter whose value is typically in the range 2 < < 3, although occasionally it may lie outside these bounds.[1][2] History[edit] In studies of the networks of citations between scientific papers, Derek de Solla Price showed in 1965 that the number of links to papers—i.e., the number of citations they receive—had a heavy-tailed distribution following a Pareto distribution or power law, and thus that the citation network is scale-free. Barabási and Albert proposed a generative mechanism to explain the appearance of power-law distributions, which they called "preferential attachment" and which is essentially the same as that proposed by Price.
(that is, the number of edges incident to ) by . Characteristics[edit] Random network (a) and scale-free network (b). Network science interactive demos. Overview — NetworkX v1.4 documentation. University of Michigan, Center for the Complex Study of Systems. SoNIA - Social Network Image Animator. Social Network Image Animator What is it? SoNIA is a Java-based package for visualizing dynamic or longitudinal "network" data.
By dynamic, we mean that in addition to information about the relations (ties) between various entities (actors, nodes) there is also information about when these relations occur, or at least the relative order in which they occur. Our intention for SoNIA is to read-in dynamic network information from various formats, aid the user in constructing "meaningful" layouts, and export the resulting images or "movies" of the network, along with information about the techniques and parameter settings used to construct the layouts, and some form of statistic indicating the "accuracy" or degree of distortion present in the layout. This is all somewhat ambitious, but not impossible.
What else is SoNIA for? In addition, we hope that SoNIA will have other uses. Another mode of use that SoNIA supports is that of a "browser" for time-based network data. Authors. SocNetV - Downloads. Onr_soc_sci_culture_gwt_05jul.pdf (objeto application/pdf) Nicholas Christakis: How social networks predict epidemics. Studying Social Interaction. David R. Heise, Rudy Professor of Sociology Emeritus at Indiana University (heise at indiana dot edu), is a past editor of Sociological Methodology and of Sociological Methods & Research. His methodological research ranges from issues in quantitative modeling to computer applications in qualitative research to surveying norms and cultures. His social psychological research focuses on the affective and logical foundations of social interaction - in particular, Affect Control Theory (ACT) and Event Structure Analysis (ESA).
Heise has received Distinguished Career awards from three sections of the American Sociological Association - Social Psychology, Sociology of Emotions, and Mathematical Sociology. Heise's publications include books: two essays in the Encyclopedia of Sociology: and an essay in the International Encyclopedia of the Social and Behavioral Science: Among his recent papers and presentations are: