113 research outputs found
Complex Beauty
Complex systems and their underlying convoluted networks are ubiquitous, all
we need is an eye for them. They pose problems of organized complexity which
cannot be approached with a reductionist method. Complexity science and its
emergent sister network science both come to grips with the inherent complexity
of complex systems with an holistic strategy. The relevance of complexity,
however, transcends the sciences. Complex systems and networks are the focal
point of a philosophical, cultural and artistic turn of our tightly
interrelated and interdependent postmodern society. Here I take a different,
aesthetic perspective on complexity. I argue that complex systems can be
beautiful and can the object of artification - the neologism refers to
processes in which something that is not regarded as art in the traditional
sense of the word is changed into art. Complex systems and networks are
powerful sources of inspiration for the generative designer, for the artful
data visualizer, as well as for the traditional artist. I finally discuss the
benefits of a cross-fertilization between science and art
The skewness of computer science
Computer science is a relatively young discipline combining science,
engineering, and mathematics. The main flavors of computer science research
involve the theoretical development of conceptual models for the different
aspects of computing and the more applicative building of software artifacts
and assessment of their properties. In the computer science publication
culture, conferences are an important vehicle to quickly move ideas, and
journals often publish deeper versions of papers already presented at
conferences. These peculiarities of the discipline make computer science an
original research field within the sciences, and, therefore, the assessment of
classical bibliometric laws is particularly important for this field. In this
paper, we study the skewness of the distribution of citations to papers
published in computer science publication venues (journals and conferences). We
find that the skewness in the distribution of mean citedness of different
venues combines with the asymmetry in citedness of articles in each venue,
resulting in a highly asymmetric citation distribution with a power law tail.
Furthermore, the skewness of conference publications is more pronounced than
the asymmetry of journal papers. Finally, the impact of journal papers, as
measured with bibliometric indicators, largely dominates that of proceeding
papers.Comment: I applied the goodness-of-fit methodology proposed in: A. Clauset, C.
R. Shalizi, M. E. J. Newman. Power-law distributions in empirical data. SIAM
Review 51, 661-703 (2009
PageRank: Standing on the shoulders of giants
PageRank is a Web page ranking technique that has been a fundamental
ingredient in the development and success of the Google search engine. The
method is still one of the many signals that Google uses to determine which
pages are most important. The main idea behind PageRank is to determine the
importance of a Web page in terms of the importance assigned to the pages
hyperlinking to it. In fact, this thesis is not new, and has been previously
successfully exploited in different contexts. We review the PageRank method and
link it to some renowned previous techniques that we have found in the fields
of Web information retrieval, bibliometrics, sociometry, and econometrics
A theory on power in networks
The eigenvector centrality equation is a successful
compromise between simplicity and expressivity. It claims that central actors
are those connected with central others. For at least 70 years, this equation
has been explored in disparate contexts, including econometrics, sociometry,
bibliometrics, Web information retrieval, and network science. We propose an
equally elegant counterpart: the power equation , where
is the vector whose entries are the reciprocal of those of . It
asserts that power is in the hands of those connected with powerless others. It
is meaningful, for instance, in bargaining situations, where it is advantageous
to be connected to those who have few options. We tell the parallel, mostly
unexplored story of this intriguing equation
HITS hits art
The blockchain art market is partitioned around the roles of artists and
collectors and highly concentrated among few prominent figures. We hence
propose to adapt Kleinberg's authority/hub HITS method to rate artists and
collectors in the art context. This seems a reasonable choice since the
original method deftly defines its scores in terms of a mutual recursive
relationship between authorities/artists - the miners of information/art, and
hubs/collectors - the assemblers of such information/art.
We evaluated the proposed method on the collector-artist network of SuperRare
gallery, the major crypto art marketplace. We found that the proposed artist
and collector metrics are weakly correlated with other network science metrics
like degree and strength. This hints the possibility of coupling different
measures in order to profile active users of the gallery and suggests
investment strategies with different risk/reward ratios for collectors as well
as marketing strategies with different targets for artists
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