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arXiv2013

Learning an Integrated Distance Metric for Comparing Structure of Complex Networks

Graph comparison plays a major role in many network applications. We often need a similarity metric for comparing networks according to their structural properties. Various network features - such as degree distribution and clustering coefficient - provide measurements for comparing networks from different points of view, but a global and integrated distance metric is still missing. In this paper, we employ distance metric learning algorithms in order to construct an integrated distance metric for comparing structural properties of complex networks. According to natural witnesses of network similarities (such as network categories) the distance metric is learned by the means of a dataset of some labeled real networks. For evaluating our proposed method which is called NetDistance, we applied it as the distance metric in K-nearest-neighbors classification. Empirical results show that NetDistance outperforms previous methods, at least 20 percent, with respect to precision.

cs.SI↗

arXiv2013

Political Stability and Military Intervention in Egypt

Policy choices in the wake of recent mass protests in Egypt will determine the likelihood of civil war in the short run and the prospects for democracy in the long run. Economic conditions can be improved by international action to reduce grain-based biofuel production and finance employment generation. Creating the conditions for stable democracy requires accepting power-sharing mechanisms in which the military will have an important role.

physics.soc-ph↗

arXiv2013

Convex relaxation for finding planted influential nodes in a social network

We consider the problem of maximizing influence in a social network. We focus on the case that the social network is a directed bipartite graph whose arcs join senders to receivers. We consider both the case of deterministic networks and probabilistic graphical models, that is, the so-called "cascade" model. The problem is to find the set of the $k$ most influential senders for a given integer $k$. Although this problem is NP-hard, there is a polynomial-time approximation algorithm due to Kempe, Kleinberg and Tardos. In this work we consider convex relaxation for the problem. We prove that convex optimization can recover the exact optimizer in the case that the network is constructed according to a generative model in which influential nodes are planted but then obscured with noise. We also demonstrate computationally that the convex relaxation can succeed on a more realistic generative model called the "forest fire" model.

math.OC↗

arXiv2013

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.

cs.SI↗

arXiv2013

Influence of media on collective debates

The information system (T.V., newspapers, blogs, social network platforms) and its inner dynamics play a fundamental role on the evolution of collective debates and thus on the public opinion. In this work we address such a process focusing on how the current inner strategies of the information system (competition, customer satisfaction) once combined with the gossip may affect the opinions dynamics. A reinforcement effect is particularly evident in the social network platforms where several and incompatible cultures coexist (e.g, pro or against the existence of chemical trails and reptilians, the new world order conspiracy and so forth). We introduce a computational model of opinion dynamics which accounts for the coexistence of media and gossip as separated but interdependent mechanisms influencing the opinions evolution. Individuals may change their opinions under the contemporary pressure of the information supplied by the media and the opinions of their social contacts. We stress the effect of the media communication patterns by considering both the simple case where each medium mimics the behavior of the most successful one (in order to maximize the audience) and the case where there is polarization and thus competition among media reported information (in order to preserve and satisfy their segmented audience). Finally, we first model the information cycle as in the case of traditional main stream media (i.e, when every medium knows about the format of all the others) and then, to account for the effect of the Internet, on more complex connectivity patterns (as in the case of the web based information). We show that multiple and polarized information sources lead to stable configurations where several and distant opinions coexist.

physics.soc-ph↗

arXiv2013

Thermalized Non-Equilibrated Matter against Random Matrix Theory, Quantum Chaos and Direct Interaction: Warming up

The idea of a thermalized non-equilibrated state of matter offers a conceptually new understanding of the strong angular asymmetry. In this compact review we present some clarifications, corrections and further developments of the approach, and provide a brief account of results previously discussed but not reported in the literature. The cross symmetry compound nucleus $S$-matrix correlations are obtained (i) starting from the unitary $S$-matrix representation, (ii) by explicitly taking into account a process of energy equilibration, and (iii) without taking the thermodynamic limit of an infinite number of particles in the thermalized system. It is conjectured that the long phase memory is due to the exponentially small total spin off-diagonal resonance intensity correlations. This manifestly implies that the strong angular asymmetry intimately relates to extremely small deviations of the eigenfunction distribution from Gaussian law. The spin diagonal resonance intensity correlations determine a new time/energy scale for a validity of random matrix theory. Its definition does not involve overlaps of the many-body interacting configurations with shell model non-interacting states and thus is conceptually different from the physical meaning (inverse energy relaxation time) of the spreading widths introduced by Wigner. Exact Gaussian distribution of the resonance wave functions corresponds to the instantaneous phase relaxation. We invite the nuclear reaction community for the competition to describe, as the first challenge, the strong forward peaking in the typically evaporation part of the proton spectra. This is necessary to initiate revealing long-term misconduct in the heavily cross-disciplinary field, also important for nuclear industry applications.

quant-ph↗

arXiv2013

South African Riots: Repercussion of the Global Food Crisis and US Drought

High and volatile global food prices have led to food riots and played a critical role in triggering the Arab Spring revolutions in recent years. The severe drought in the US in the summer of 2012 led to a new increase in food prices. Through the fall, they remained at a threshold above which the riots and revolutions had predominantly occurred. Global prices at this level create conditions where an exacerbating local circumstance can trigger unrest. Global corn (maize) prices reached new highs, and countries that depend mostly on maize are more likely to experience high local food prices and associated pressures toward social unrest. Here we analyze the conditions in South Africa, which is a heavily maize-dependent country. Coinciding with increased consumer food indices this summer, massive labor strikes in mining and agriculture have led to the greatest single incident of social violence since the fall of apartheid in 1994. Worker demands for dramatic pay increases reflect that their wages have not kept up with drastic increases in the prices of necessities, especially food. Without attention to the global food price situation, more incidents of food-based social instability are likely to arise. Other countries that have manifested food-related protests and riots in 2012 include Haiti and Argentina. Moreover, these cases of unrest are just the most visible symptom of widespread suffering of poor populations worldwide due to elevated food prices. Policy decisions that would directly impact food prices are decreasing the conversion of maize to ethanol in the US, and reimposing regulations on commodity futures markets to prevent excessive speculation, which we have shown causes bubbles and crashes in these markets. Absent such policy actions, governments and companies should track and mitigate the impact of high and volatile food prices on citizens and employees.

physics.soc-ph↗

arXiv2013

Mathematical models for epidemic spreading on complex networks

We propose a model for epidemic spreading on a finite complex network with a restriction to at most one contamination per time step. Because of a highly discrete character of the process, the analysis cannot use the continous approximation, widely exploited for most of the models. Using discrete approach we investigate the epidemic threshold and the quasi-stationary distribution. The main result is a theorem about mixing time for the process, which scales like logarithm of the network size and which is proportional to the inverse of the distance from the epidemic threshold. In order to present the model in the full context, we review modern approach to epidemic spreading modeling based on complex networks and present necessary information about random networks, discrete-time Markov chains and their quasi-stationary distributions.

physics.soc-ph↗

arXiv2013

On house renovation and coauthoring (with a little excursus on the Holy Grail of bibliometrics)

More than a paper, this is just a little divertissement about coauthoring, the Hirsch h-index, and bibliometric evaluation in general. Without pretending to yield any general conclusions, what I found rummaging through the physics literature made me think quite a bit. I hope the same will happen to my readers, even it they will likely be much less than 25, which is the audience one of the greatest Italian writers (whom, is left to the reader to single out) addresses to.

physics.soc-ph↗

arXiv2013

Online Communities: Visualization and Formalization

Online communities have increased in size and importance dramatically over the last decade. The fact that many communities are online means that it is possible to extract information about these communities and the connections between their members much more easily using software tools, despite their potentially very large size. The links between members of the community can be presented visually and often this can make patterns in the structure of sub-communities immediately obvious. The links and structures of layered communities can also be formalized to gain a better understanding of their modelling. This paper explores these links with some specific examples, including visualization of these relationships and a formalized model of communities using the Z notation. It also considers the development of such communities within the Community of Practice social science framework. Such approaches may be applicable for communities associated with cybersecurity and could be combined for a better understanding of their development.

cs.SI↗

arXiv2013

Is there currently a scientific revolution in scientometrics?

The author of this letter to the editor would like to set forth the argument that scientometrics is currently in a phase in which a taxonomic change, and hence a revolution, is taking place. One of the key terms in scientometrics is scientific impact which nowadays is understood to mean not only the impact on science but the impact on every area of society.

cs.DL↗

arXiv2013

Incentives, Quality, and Risks: A Look Into the NSF Proposal Review Pilot

The National Science Foundation (NSF) will be experimenting with a new distributed approach to reviewing proposals, whereby a group of principal investigators (PIs) or proposers in a subfield act as reviewers for the proposals submitted by the same set of PIs. To encourage honesty, PIs' chances for getting funded are tied to the quality of their reviews (with respect to the reviews provided by the entire group), in addition to the quality of their proposals. Intuitively, this approach can more fairly distribute the review workload, discourage frivolous proposal submission, and encourage high quality reviews. On the other hand, this method has already raised concerns about the integrity of the process and the possibility of strategic manipulation. In this paper, we take a closer look at three specific issues in an attempt to gain a better understanding of the strengths and limitations of the new process beyond first impressions and anecdotal evidence. We start by considering the benefits and drawbacks of bundling the quality of PIs' reviews with the scientific merit of their proposals. We then consider the issue of collusion and favoritism. Finally, we examine whether the new process puts controversial proposals at a disadvantage. We conclude that some benefits of using review quality as an incentive mechanism may outweigh its drawbacks. On the other hand, even a coalition of two PIs can cause significant harm to the process, as the built-in incentives are not strong enough to deter collusion. While we also confirm the common suspicion that the process is skewed toward non-controversial proposals, the more unexpected finding is that among equally controversial proposals, those of lower quality get a leg up through this process. Thus the process not only favors non-controversial proposals, but in some sense, mediocrity. We also discuss possible ways to improve this review process.

cs.GT↗

arXiv2013

Network Topologies of Financial Market During the Global Financial Crisis

We consider the effects of the global financial crisis through a local Korean financial market around the 2008 crisis. We analyze 185 individual stock prices belonging to the KOSPI (Korea Composite Stock Price Index), cosidering three time periods: the time before, during, and after the crisis. The complex networks generate from the fully connected correlation network by using the cross-correlation coefficients among the stock price time series of the companies. We generate the threshold networks (TN), the minimal spanning tees (MST), and the hierarchical network (HN) from the fully connected cross-correlation networks. By assigning a threshold value of the cross-correlation coefficient, we obtain the threshold networks. We observe the power law of the degree distribution in the limited range of the threshold. The degree distribution of the largest cluster in the threshold networks during the crisis is fatter than other periods. The clustering coefficient of the threshold networks follows the power law in the scaling range. We also generate the minimal spanning trees from the fully connected correlation networks. The MST during the crisis period shrinks in comparison to the periods before and after the crisis. The cophenetic correlation coefficient increases during the crisis, indicating that the hierarchical structure increases during this period. When the crisis hit the market, the companies behave synchronously and their correlations become stronger than the normal period.

q-fin.GN↗

arXiv2013

Temporal influence over the Last.fm social network

Several recent results show the influence of social contacts to spread certain properties over the network, but others question the methodology of these experiments by proposing that the measured effects may be due to homophily or a shared environment. In this paper we justify the existence of the social influence by considering the temporal behavior of Last.fm users. In order to clearly distinguish between friends sharing the same interest, especially since Last.fm recommends friends based on similarity of taste, we separated the timeless effect of similar taste from the temporal impulses of immediately listening to the same artist after a friend. We measured strong increase of listening to a completely new artist in a few hours period after a friend compared to non-friends representing a simple trend or external influence. In our experiment to eliminate network independent elements of taste, we improved collaborative filtering and trend based methods by blending with simple time aware recommendations based on the influence of friends. Our experiments are carried over the two-year "scrobble" history of 70,000 Last.fm users.

cs.SI↗

arXiv2013

Structure and Dynamics of Coauthorship, Citation, and Impact within CSCW

CSCW has stabilized as an interdisciplinary venue for computer, information, cognitive, and social scientists but has also undergone significant changes in its format in recent years. This paper uses methods from social network analysis and bibliometrics to re-examine the structures of CSCW a decade after its last systematic analysis. Using data from the ACM Digital Library, we analyze changes in structures of coauthorship and citation between 1986 and 2013. Statistical models reveal significant but distinct patterns between papers and authors in how brokerage and closure in these networks affects impact as measured by citations and downloads. Specifically, impact is unduly influenced by structural position, such that ideas introduced by those in the core of the CSCW community (e.g., elite researchers) are advantaged over those introduced by peripheral participants (e.g., newcomers). This finding is examined in the context of recent changes to the CSCW conference that may have the effect of upsetting the preference for contributions from the core.

cs.DL↗

arXiv2013

Clustering Chinese Regional Cultures with Online-gaming Data

To identify cluster of societies is not easy in subject to the availability of data. In this study, from the prospective of computational social science, we propose a novel method to cluster Chinese regional cultures. Using millions of geotagged online-gaming data of Chinese internet users playing online card and board games with regional features, 336 Chinese cities are grouped into several main clusters. The geographic boundaries of clusters coincide with the boundaries of provincial regions. The north regions in China have more geographical proximity, when regional variations in south regions are more evident.

cs.CY↗

arXiv2013

Improving Data Forwarding in Mobile Social Networks with Infrastructure Support: A Space-Crossing Community Approach

In this paper, we study two tightly coupled issues: space-crossing community detection and its influence on data forwarding in Mobile Social Networks (MSNs) by taking the hybrid underlying networks with infrastructure support into consideration. The hybrid underlying network is composed of large numbers of mobile users and a small portion of Access Points (APs). Because APs can facilitate the communication among long-distance nodes, the concept of physical proximity community can be extended to be one across the geographical space. In this work, we first investigate a space-crossing community detection method for MSNs. Based on the detection results, we design a novel data forwarding algorithm SAAS (Social Attraction and AP Spreading), and show how to exploit the space-crossing communities to improve the data forwarding efficiency. We evaluate our SAAS algorithm on real-life data from MIT Reality Mining and UIM. Results show that space-crossing community plays a positive role in data forwarding in MSNs in terms of deliver ratio and delay. Based on this new type of community, SAAS achieves a better performance than existing social community-based data forwarding algorithms in practice, including Bubble Rap and Nguyen's Routing algorithms.

cs.SI↗

arXiv2013

The normalization of citation counts based on classification systems

If we want to assess whether the paper in question has had a particularly high or low citation impact compared to other papers, the standard practice in bibliometrics is to normalize citations in respect of the subject category and publication year. A number of proposals for an improved procedure in the normalization of citation impact have been put forward in recent years. Against the background of these proposals this study describes an ideal solution for the normalization of citation impact: in a first step, the reference set for the publication in question is collated by means of a classification scheme, where every publication is associated with a single principal research field or subfield entry (e. g. via Chemical Abstracts sections) and a publication year. In a second step, percentiles of citation counts are calculated for this set and used to assign the normalized citation impact score to the publications (and also to the publication in question).

cs.DL↗