3,215 research outputs found
Competition and Success in the Meme Pool: a Case Study on Quickmeme.com
The advent of social media has provided data and insights about how people
relate to information and culture. While information is composed by bits and
its fundamental building bricks are relatively well understood, the same cannot
be said for culture. The fundamental cultural unit has been defined as a
"meme". Memes are defined in literature as specific fundamental cultural
traits, that are floating in their environment together. Just like genes
carried by bodies, memes are carried by cultural manifestations like songs,
buildings or pictures. Memes are studied in their competition for being
successfully passed from one generation of minds to another, in different ways.
In this paper we choose an empirical approach to the study of memes. We
downloaded data about memes from a well-known website hosting hundreds of
different memes and thousands of their implementations. From this data, we
empirically describe the behavior of these memes. We statistically describe
meme occurrences in our dataset and we delineate their fundamental traits,
along with those traits that make them more or less apt to be successful
On the Asymptotic Behavior of D-Solutions to the Displacement Problem of Linear Elastostatics in Exterior Domains
We study the asymptotic behavior of solutions with finite energy to the displacement
problem of linear elastostatics in a three-dimensional exterior Lipschitz domain
Locally Convex Words and Permutations
We introduce some new classes of words and permutations characterized by the
second difference condition , which we
call the -convexity condition. We demonstrate that for any sized alphabet
and convexity parameter , we may find a generating function which counts
-convex words of length . We also determine a formula for the number of
0-convex words on any fixed-size alphabet for sufficiently large by
exhibiting a connection to integer partitions. For permutations, we give an
explicit solution in the case and show that the number of 1-convex and
2-convex permutations of length are and ,
respectively, and use the transfer matrix method to give tight bounds on the
constants and . We also providing generating functions similar to
the the continued fraction generating functions studied by Odlyzko and Wilf in
the "coins in a fountain" problem.Comment: 20 pages, 4 figure
The Impact of Projection and Backboning on Network Topologies
Bipartite networks are a well known strategy to study a variety of phenomena.
The commonly used method to deal with this type of network is to project the
bipartite data into a unipartite weighted graph and then using a backboning
technique to extract only the meaningful edges. Despite the wide availability
of different methods both for projection and backboning, we believe that there
has been little attention to the effect that the combination of these two
processes has on the data and on the resulting network topology. In this paper
we study the effect that the possible combinations of projection and backboning
techniques have on a bipartite network. We show that the 12 methods group into
two clusters producing unipartite networks with very different topologies. We
also show that the resulting level of network centralization is highly affected
by the combination of projection and backboning applied
Discovering Communities of Community Discovery
Discovering communities in complex networks means grouping nodes similar to
each other, to uncover latent information about them. There are hundreds of
different algorithms to solve the community detection task, each with its own
understanding and definition of what a "community" is. Dozens of review works
attempt to order such a diverse landscape -- classifying community discovery
algorithms by the process they employ to detect communities, by their
explicitly stated definition of community, or by their performance on a
standardized task. In this paper, we classify community discovery algorithms
according to a fourth criterion: the similarity of their results. We create an
Algorithm Similarity Network (ASN), whose nodes are the community detection
approaches, connected if they return similar groupings. We then perform
community detection on this network, grouping algorithms that consistently
return the same partitions or overlapping coverage over a span of more than one
thousand synthetic and real world networks. This paper is an attempt to create
a similarity-based classification of community detection algorithms based on
empirical data. It improves over the state of the art by comparing more than
seventy approaches, discovering that the ASN contains well-separated groups,
making it a sensible tool for practitioners, aiding their choice of algorithms
fitting their analytic needs
Advanced C and D techniques and application study
A study was conducted to identify a broad base of payload control and display requirements for space missions. The subjects discussed are: (1) functional requirements and allocation analysis, (2) control and display generic device matrix, (3) control functional requirements, and (4) display functional requirements. Specific applications of payload control and display requirements for various disciplines are defined
- …