Quantifying discrepancies in opinion spectra from online and offline networks

Online social media such as Twitter are widely used for mining public opinions and sentiments on various issues and topics. The sheer volume of the data generated and the eager adoption by the online-savvy public are helping to raise the profile of online media as a convenient source of news and public opinions on social and political issues as well. Due to the uncontrollable biases in the population who heavily use the media, however, it is often difficult to measure how accurately the online sphere reflects the offline world at large, undermining the usefulness of online media. One way of identifying and overcoming the online-offline discrepancies is to apply a common analytical and modeling framework to comparable data sets from online and offline sources and cross-analyzing the patterns found therein. In this paper we study the political spectra constructed from Twitter and from legislators' voting records as an example to demonstrate the potential limits of online media as the source for accurate public opinion mining.Comment: 10 pages, 4 figure

Clustering properties of a generalised critical Euclidean network

Many real-world networks exhibit scale-free feature, have a small diameter and a high clustering tendency. We have studied the properties of a growing network, which has all these features, in which an incoming node is connected to its $i$th predecessor of degree $k_i$ with a link of length $\ell$ using a probability proportional to $k^\beta_i \ell^{\alpha}$. For $\alpha > -0.5$, the network is scale free at $\beta = 1$ with the degree distribution $P(k) \propto k^{-\gamma}$ and $\gamma = 3.0$ as in the Barab\'asi-Albert model ($\alpha =0, \beta =1$). We find a phase boundary in the $\alpha-\beta$ plane along which the network is scale-free. Interestingly, we find scale-free behaviour even for $\beta > 1$ for $\alpha < -0.5$ where the existence of a new universality class is indicated from the behaviour of the degree distribution and the clustering coefficients. The network has a small diameter in the entire scale-free region. The clustering coefficients emulate the behaviour of most real networks for increasing negative values of $\alpha$ on the phase boundary.Comment: 4 pages REVTEX, 4 figure

Crossover from Endogenous to Exogenous Activity in Open-Source Software Development

We have investigated the origin of fluctuations in the aggregated behaviour of an open-source software community. In a recent series of papers, de Menezes and co-workers have shown how to separate internal dynamics from external fluctuations by capturing the simultaneous activity of many system's components. In spite of software development being a planned activity, the analysis of fluctuations reveals how external driving forces can be only observed at weekly and higher time scales. Hourly and higher change frequencies mostly relate to internal maintenance activities. There is a crossover from endogenous to exogenous activity depending on the average number of file changes. This new evidence suggests that software development is a non-homogeneous design activity where stronger efforts focus in a few project files. The crossover can be explained with a Langevin equation associated to the cascading process, where changes to any file trigger additional changes to its neighbours in the software network. In addition, analysis of fluctuations enables us to detect whether a software system can be decomposed in several subsystems with different development dynamics.Comment: 7 pages, 4 figures, submitted to Europhysics Letter

Modeling the Internet's Large-Scale Topology

Network generators that capture the Internet's large-scale topology are crucial for the development of efficient routing protocols and modeling Internet traffic. Our ability to design realistic generators is limited by the incomplete understanding of the fundamental driving forces that affect the Internet's evolution. By combining the most extensive data on the time evolution, topology and physical layout of the Internet, we identify the universal mechanisms that shape the Internet's router and autonomous system level topology. We find that the physical layout of nodes form a fractal set, determined by population density patterns around the globe. The placement of links is driven by competition between preferential attachment and linear distance dependence, a marked departure from the currently employed exponential laws. The universal parameters that we extract significantly restrict the class of potentially correct Internet models, and indicate that the networks created by all available topology generators are significantly different from the Internet

Diffusive Capture Process on Complex Networks

We study the dynamical properties of a diffusing lamb captured by a diffusing lion on the complex networks with various sizes of $N$. We find that the life time $of a lamb scales as \sim N$ and the survival probability $S(N\to \infty,t)$ becomes finite on scale-free networks with degree exponent $\gamma>3$. However, $S(N,t)$ for $\gamma<3$ has a long-living tail on tree-structured scale-free networks and decays exponentially on looped scale-free networks. It suggests that the second moment of degree distribution $is the relevant factor for the dynamical properties in diffusive capture process. We numerically find that the normalized number of capture events at a node with degree$k$,$n(k)$, decreases as$n(k)\sim k^{-\sigma}$. When$\gamma<3$,$n(k)$still increases anomalously for$k\approx k_{max}$. We analytically show that$n(k)$satisfies the relation$n(k)\sim k^2P(k)$and the total number of capture events$N_{tot}$is proportional to$, which causes the $\gamma$ dependent behavior of $S(N,t)$ and $.Comment: 9 pages, 6 figure

Dynamical surface structures in multi-particle-correlated surface growths

We investigate the scaling properties of the interface fluctuation width for the $Q$-mer and $Q$-particle-correlated deposition-evaporation models. These models are constrained with a global conservation law that the particle number at each height is conserved modulo $Q$. In equilibrium, the stationary roughness is anomalous but universal with roughness exponent $\alpha=1/3$, while the early time evolution shows nonuniversal behavior with growth exponent $\beta$ varying with models and $Q$. Nonequilibrium surfaces display diverse growing/stationary behavior. The $Q$-mer model shows a faceted structure, while the $Q$-particle-correlated model a macroscopically grooved structure.Comment: 16 pages, 10 figures, revte

Weighted Evolving Networks

Many biological, ecological and economic systems are best described by weighted networks, as the nodes interact with each other with varying strength. However, most network models studied so far are binary, the link strength being either 0 or 1. In this paper we introduce and investigate the scaling properties of a class of models which assign weights to the links as the network evolves. The combined numerical and analytical approach indicates that asymptotically the total weight distribution converges to the scaling behavior of the connectivity distribution, but this convergence is hampered by strong logarithmic corrections.Comment: 5 pages, 3 figure

Modulated Scale-free Network in the Euclidean Space

A random network is grown by introducing at unit rate randomly selected nodes on the Euclidean space. A node is randomly connected to its $i$-th predecessor of degree $k_i$ with a directed link of length $\ell$ using a probability proportional to $k_i \ell^{\alpha}$. Our numerical study indicates that the network is Scale-free for all values of $\alpha > \alpha_c$ and the degree distribution decays stretched exponentially for the other values of $\alpha$. The link length distribution follows a power law: $D(\ell) \sim \ell^{\delta}$ where $\delta$ is calculated exactly for the whole range of values of $\alpha$.Comment: 4 pages, 4 figures. To be published in Physical Review