10,858 research outputs found
A Data-driven Study of Influences in Twitter Communities
This paper presents a quantitative study of Twitter, one of the most popular
micro-blogging services, from the perspective of user influence. We crawl
several datasets from the most active communities on Twitter and obtain 20.5
million user profiles, along with 420.2 million directed relations and 105
million tweets among the users. User influence scores are obtained from
influence measurement services, Klout and PeerIndex. Our analysis reveals
interesting findings, including non-power-law influence distribution, strong
reciprocity among users in a community, the existence of homophily and
hierarchical relationships in social influences. Most importantly, we observe
that whether a user retweets a message is strongly influenced by the first of
his followees who posted that message. To capture such an effect, we propose
the first influencer (FI) information diffusion model and show through
extensive evaluation that compared to the widely adopted independent cascade
model, the FI model is more stable and more accurate in predicting influence
spreads in Twitter communities.Comment: 11 page
Binary Independent Component Analysis with OR Mixtures
Independent component analysis (ICA) is a computational method for separating
a multivariate signal into subcomponents assuming the mutual statistical
independence of the non-Gaussian source signals. The classical Independent
Components Analysis (ICA) framework usually assumes linear combinations of
independent sources over the field of realvalued numbers R. In this paper, we
investigate binary ICA for OR mixtures (bICA), which can find applications in
many domains including medical diagnosis, multi-cluster assignment, Internet
tomography and network resource management. We prove that bICA is uniquely
identifiable under the disjunctive generation model, and propose a
deterministic iterative algorithm to determine the distribution of the latent
random variables and the mixing matrix. The inverse problem concerning
inferring the values of latent variables are also considered along with noisy
measurements. We conduct an extensive simulation study to verify the
effectiveness of the propose algorithm and present examples of real-world
applications where bICA can be applied.Comment: Manuscript submitted to IEEE Transactions on Signal Processin
Horizon thermodynamics in theory
We investigate whether the new horizon first law proposed recently still work
in theory. We identify the entropy and the energy of black hole as
quantities proportional to the corresponding value of integration, supported by
the fact that the new horizon first law holds true as a consequence of
equations of motion in theories. The formulas for the entropy and energy
of black hole found here are in agreement with the results obtained in
literatures. For applications, some nontrivial black hole solutions in
theories have been considered, the entropies and the energies of black holes in
these models are firstly computed, which may be useful for future researches.Comment: 8 pages, no figur
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