SEARCH · Searcharxiv

Results for “physics.soc-ph”

Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 721 records · Page 40Linked to original sources

arXiv2013

Evolution of Communities with Focus on Stability (extended abstract)

The detection of communities is an important tool used to analyze the social graph of mobile phone users. Within each community, customers are susceptible of attracting new ones, retaining old ones and/or accepting new products or services through the leverage of mutual influences. The communities of users are smaller units, easier to grasp, and allow for example the computation of role analysis -- based on the centrality of an actor within his community. The problem of finding communities in static graphs has been widely studied. However, from the point of view of a telecom analyst, to be really useful, the detected communities must evolve as the social graph of communications changes over time -- for example, in order to perform marketing actions on communities and track the results of those actions over time. Additionally the behaviors of communities of users over time can be used to predict future activity that interests the telecom operators, such as subscriber churn or handset adoption. Similary group evolution can provide insights for designing strategies, such as the early warning of group churn. Stability is a crucial issue: the analysis performed on a given community will be lost, if the analyst cannot keep track of this community in the following time steps. This is the particular use case that we tackle in this paper: tracking the evolution of communities in dynamic scenarios with focus on stability. We propose two modifications to a widely used static community detection algorithm. We then describe experiments to study the stability and quality of the resulting partitions on real-world social networks, represented by monthly call graphs for millions of subscribers.

cs.SI↗

arXiv2013

Tracing the origin of a scientific legend by Reference Publication Year Spectroscopy (RPYS): the legend of the Darwin finches

In a previews paper we introduced the quantitative method named Reference Publication Year Spectroscopy (RPYS). With this method one can determine the historical roots of research fields and quantify their impact on current research. RPYS is based on the analysis of the frequency with which references are cited in the publications of a specific research field in terms of the publication years of these cited references. In this study, we illustrate that RPYS can also be used to reveal the origin of scientific legends. We selected Darwin finches as an example for illustration. Charles Darwin, the originator of evolutionary theory, was given credit for finches he did not see and for observations and insights about the finches he never made. We have shown that a book published in 1947 is the most-highly cited early reference cited within the relevant literature. This book had already been revealed as the origin of the term Darwin finches by Sulloway through careful historical analysis.

stat.AP↗

arXiv2013

Sinkless: A Preliminary Study of Stress Propagation in Group Project Social Networks using a Variant of the Abelian Sandpile Model

We perform social network analysis on 53 students split over three semesters and 13 groups, using conventional measures like eigenvector centrality, betweeness centrality, and degree centrality, as well as defining a variant of the Abelian Sandpile Model (ASM) with the intention of modeling stress propagation in the college classroom. We correlate the results of these analyses with group project grades received; due to a small or poorly collected dataset, we are unable to conclude that any of these network measures relates to those grades. However, we are successful in using this dataset to define a discrete, recursive, and more generalized variant of the ASM. Abelian Sandpile Model, College Grades, Self-organized Criticality, Sinkless Sandpile Model, Social Network Analysis, Stress Propagation

cs.SI↗

arXiv2013

John Cage's Number Pieces as Stochastic Processes: a Large-Scale Analysis

The Number Pieces are a corpus of works by composer John Cage, which rely on a particular time-structure used for determining the temporal location of sounds, named the "time-bracket". The time-bracket system is an inherently stochastic process, which complicates the analysis of the Number Pieces as it leads to a large number of possibilities in terms of sonic content instead of one particular fixed performance. The purpose of this paper is to propose a statistical approach of the Number Pieces by assimilating them to stochastic processes. Two Number Pieces, "Four" and "Five", are studied here in terms of pitch-class set content: the stochastic processes at hand lead to a collection of random variables indexed over time giving the distribution of the possible pitch-class sets. This approach allows for a static and dynamic analysis of the score encompassing all the possible outcomes during the performance of these works.

physics.soc-ph↗

arXiv2013

Event Evolution Tracking from Streaming Social Posts

Online social post streams such as Twitter timelines and forum discussions have emerged as important channels for information dissemination. They are noisy, informal, and surge quickly. Real life events, which may happen and evolve every minute, are perceived and circulated in post streams by social users. Intuitively, an event can be viewed as a dense cluster of posts with a life cycle sharing the same descriptive words. There are many previous works on event detection from social streams. However, there has been surprisingly little work on tracking the evolution patterns of events, e.g., birth/death, growth/decay, merge/split, which we address in this paper. To define a tracking scope, we use a sliding time window, where old posts disappear and new posts appear at each moment. Following that, we model a social post stream as an evolving network, where each social post is a node, and edges between posts are constructed when the post similarity is above a threshold. We propose a framework which summarizes the information in the stream within the current time window as a ``sketch graph'' composed of ``core'' posts. We develop incremental update algorithms to handle highly dynamic social streams and track event evolution patterns in real time. Moreover, we visualize events as word clouds to aid human perception. Our evaluation on a real data set consisting of 5.2 million posts demonstrates that our method can effectively track event dynamics in the whole life cycle from very large volumes of social streams on the fly.

cs.SI↗

arXiv2014

A Quantum Probability Explanation in Fock Space for Borderline Contradictions

The construction of a consistent theory for structuring and representing how concepts combine and interact is one of the main challenges for the scholars involved in cognitive studies. All traditional approaches are still facing serious hindrances when dealing with combinations of concepts and concept vagueness. One of the main consequences of these difficulties is the existence of borderline cases which is hardly explainable from the point of view of classical (fuzzy set) logic and probability theory. Resting on a quantum-theoretic approach which successfully models conjunctions and disjuncions of two concepts, we propound a quantum probability model in Fock space which accords with the experimental data collected by Alxatib and Pelletier (2011) on borderline contradictions. Our model allows one to explain the occurrence of the latter contradictions in terms of genuine quantum effects, such as contextuality, superposition, interference and emergence. In particular, we claim that it is the specific mechanism of `emergence of a new concept' that is responsible of these deviations from classical logical thinking in the cognitive studies on human thought. This result seems to be compatible with a recent interesting application of quantum probabilistic modeling in the study of borderline vagueness (Blutner, Pothos & Bruza, 2012), and analogies and differences with it are sketched here.

physics.soc-ph↗

arXiv2013

A model for generating tunable clustering coefficients independent of the number of nodes in scale free and random networks

Probabilistic networks display a wide range of high average clustering coefficients independent of the number of nodes in the network. In particular, the local clustering coefficient decreases with the degree of the subtending node in a complicated manner not explained by any current models. While a number of hypotheses have been proposed to explain some of these observed properties, there are no solvable models that explain them all. We propose a novel growth model for both random and scale free networks that is capable of predicting both tunable clustering coefficients independent of the network size, and the inverse relationship between the local clustering coefficient and node degree observed in most networks.

physics.soc-ph↗

arXiv2013

Reliability measures for indexed semi-Markov chains applied to wind energy production

The computation of the dependability measures is a crucial point in the planning and development of a wind farm. In this paper we address the issue of energy production by wind turbine by using an indexed semi-Markov chain as a model of wind speed. We present the mathematical model, we describe the data and technical characteristics of a commercial wind turbine (Aircon HAWT-10kW). We show how to compute some of the main dependability measures such as reliability, availability and maintainability functions. We compare the results of the model with real energy production obtained from data available in the Lastem station (Italy) and sampled every 10 minutes.

physics.data-an↗

arXiv2013

Science and the Future: Introduction

The contradiction between physical and economical sciences concerning the growth of the production/consumption mechanism is analyzed. It is then shown that if one wishes to keep the security level stable or to enhance it in a growing economy the cost of security grows faster than the gross wealth. The result is a typical evolution in which the net wealth increases up to a maximum, then abruptly collapses. Besides this, any system of relations based on a growing volume of exchanges is bound to go progressively out of control. The voluntary blindness of the ruling classes toward these facts is leading our societies to a disaster. This fate is not inescapable provided we learn to dismantle the myth of perpetual growth.

physics.soc-ph↗

arXiv2013

Dynamics of Trends and Attention in Chinese Social Media

There has been a tremendous rise in the growth of online social networks all over the world in recent years. It has facilitated users to generate a large amount of real-time content at an incessant rate, all competing with each other to attract enough attention and become popular trends. While Western online social networks such as Twitter have been well studied, the popular Chinese microblogging network Sina Weibo has had relatively lower exposure. In this paper, we analyze in detail the temporal aspect of trends and trend-setters in Sina Weibo, contrasting it with earlier observations in Twitter. We find that there is a vast difference in the content shared in China when compared to a global social network such as Twitter. In China, the trends are created almost entirely due to the retweets of media content such as jokes, images and videos, unlike Twitter where it has been shown that the trends tend to have more to do with current global events and news stories. We take a detailed look at the formation, persistence and decay of trends and examine the key topics that trend in Sina Weibo. One of our key findings is that retweets are much more common in Sina Weibo and contribute a lot to creating trends. When we look closer, we observe that most trends in Sina Weibo are due to the continuous retweets of a small percentage of fraudulent accounts. These fake accounts are set up to artificially inflate certain posts, causing them to shoot up into Sina Weibo's trending list, which are in turn displayed as the most popular topics to users.

cs.SI↗

arXiv2013

Community Specific Temporal Topic Discovery from Social Media

Studying temporal dynamics of topics in social media is very useful to understand online user behaviors. Most of the existing work on this subject usually monitors the global trends, ignoring variation among communities. Since users from different communities tend to have varying tastes and interests, capturing community-level temporal change can improve the understanding and management of social content. Additionally, it can further facilitate the applications such as community discovery, temporal prediction and online marketing. However, this kind of extraction becomes challenging due to the intricate interactions between community and topic, and intractable computational complexity. In this paper, we take a unified solution towards the community-level topic dynamic extraction. A probabilistic model, CosTot (Community Specific Topics-over-Time) is proposed to uncover the hidden topics and communities, as well as capture community-specific temporal dynamics. Specifically, CosTot considers text, time, and network information simultaneously, and well discovers the interactions between community and topic over time. We then discuss the approximate inference implementation to enable scalable computation of model parameters, especially for large social data. Based on this, the application layer support for multi-scale temporal analysis and community exploration is also investigated. We conduct extensive experimental studies on a large real microblog dataset, and demonstrate the superiority of proposed model on tasks of time stamp prediction, link prediction and topic perplexity.

cs.SI↗

arXiv2013

Evolution of Communities with Focus on Stability

Community detection is an important tool for analyzing the social graph of mobile phone users. The problem of finding communities in static graphs has been widely studied. However, since mobile social networks evolve over time, static graph algorithms are not sufficient. To be useful in practice (e.g. when used by a telecom analyst), the stability of the partitions becomes critical. We tackle this particular use case in this paper: tracking evolution of communities in dynamic scenarios with focus on stability. We propose two modifications to a widely used static community detection algorithm: we introduce fixed nodes and preferential attachment to pre-existing communities. We then describe experiments to study the stability and quality of the resulting partitions on real-world social networks, represented by monthly call graphs for millions of subscribers.

cs.SI↗

arXiv2013

Epidemic Thresholds with External Agents

We study the effect of external infection sources on phase transitions in epidemic processes. In particular, we consider an epidemic spreading on a network via the SIS/SIR dynamics, which in addition is aided by external agents - sources unconstrained by the graph, but possessing a limited infection rate or virulence. Such a model captures many existing models of externally aided epidemics, and finds use in many settings - epidemiology, marketing and advertising, network robustness, etc. We provide a detailed characterization of the impact of external agents on epidemic thresholds. In particular, for the SIS model, we show that any external infection strategy with constant virulence either fails to significantly affect the lifetime of an epidemic, or at best, sustains the epidemic for a lifetime which is polynomial in the number of nodes. On the other hand, a random external-infection strategy, with rate increasing linearly in the number of infected nodes, succeeds under some conditions to sustain an exponential epidemic lifetime. We obtain similar sharp thresholds for the SIR model, and discuss the relevance of our results in a variety of settings.

cs.SI↗

arXiv2013

Harbinger: An Analyzing and Predicting System for Online Social Network Users' Behavior

Online Social Network (OSN) is one of the hottest innovations in the past years, and the active users are more than a billion. For OSN, users' behavior is one of the important factors to study. This demonstration proposal presents Harbinger, an analyzing and predicting system for OSN users' behavior. In Harbinger, we focus on tweets' timestamps (when users post or share messages), visualize users' post behavior as well as message retweet number and build adjustable models to predict users' behavior. Predictions of users' behavior can be performed with the discovered behavior models and the results can be applied to many applications such as tweet crawler and advertisement.

cs.SI↗

arXiv2013

Clustering online social network communities using genetic algorithms

To analyze the activities in an Online Social network (OSN), we introduce the concept of "Node of Attraction" (NoA) which represents the most active node in a network community. This NoA is identified as the origin/initiator of a post/communication which attracted other nodes and formed a cluster at any point in time. In this research, a genetic algorithm (GA) is used as a data mining method where the main objective is to determine clusters of network communities in a given OSN dataset. This approach is efficient in handling different type of discussion topics in our studied OSN - comments, emails, chat expressions, etc. and can form clusters according to one or more topics. We believe that this work can be useful in finding the source for spread of this GA-based clustering of online interactions and reports some results of experiments with real-world data and demonstrates the performance of proposed approach.

cs.SI↗

arXiv2013

Modelling the income distribution in the European Union: An application for the initial analysis of the recent worldwide financial crisis

By using methods of statistical physics, we focus on the quantitative analysis of the economic income data descending from different databases. To explain our approach, we introduce the necessary theoretical background, the extended Yakovenko et al. (EY) model. This model gives an analytical description of the annual household incomes of all society classes in the European Union (i.e., the low-, medium-, and high-income ones) by a single unified formula based on unified formalism. We show that the EY model is very useful for the analyses of various income datasets, in particular, in the case of a smooth matching of two different datasets. The completed database which we have constructed using this matching emphasises the significance of the high-income society class in the analysis of all household incomes. For instance, the Pareto exponent, which characterises this class, defines the Zipf law having an exponent much lower than the one characterising the medium-income society class. This result makes it possible to clearly distinguish between medium- and high-income society classes. By using our approach, we found that the high-income society class almost disappeared in 2009, which defines this year as the most difficult for the EU. To our surprise, this is a contrast with 2008, considered the first year of a worldwide financial crisis, when the status of the high-income society class was similar to that of 2010. This, perhaps, emphasises that the crisis in the EU was postponed by about one year in comparison with the United States.

q-fin.GN↗

arXiv2013

Evolutionary game theory and the tower of Babel of cooperation: Altruism, free-riding, parasitism and the structure of the interactions in a world with finite resources

The study of the evolution of cooperative behaviours --which provide benefits to others-- and altruism --which provides benefits to others at a cost to oneself-- has been on the core of the evolutionary game theoretical framework since its foundation. The fast development of the theory during the last years has improved our knowledge of the issue, but carried attached a diversification of concepts which affected communication between scientists. Furthermore, the main root of conflict in the struggle for life identified by Darwin, the limited amount of resources present in any ecosystem, which is assumed to keep a constant population size in most game theoretical studies, has only recently been taken into account as explicitly influencing the evolutionary process. This review concerns about both issues, the conceptual diversification during the last years and the new results of the resource dependent models. In extenso: After a historical introduction, a review of the most important concepts is carried out. Then it is shown that pairwise interactions and additive fitness determine prisoner's dilemmas (PDs) or harmony games, that two altruists interacting together may determine a PD, and that the interaction environment of the most cooperative and less selfish individual in any population is always a PD. After that, it is shown that in addition to altruists versus free-riders, the combination of free-riders and parasites determines a fundamentally different PD. Computer simulations are then carried out to show that random exploration of parasitism, free-riding and altruism enables coexistence of the three strategies without the need of reciprocating, punishing or rewarding strategies. To finish, the problem of the limitation of resources is reviewed, showing that...

q-bio.PE↗

arXiv2013

Policy Network Approach to Coordinated Disaster Response

In this paper, we explore the formation of network relationships among disaster relief agencies during the process of responding to an unexpected event. The relationship is investigated through variables derived from the policy network theory, and four cases from three developed countries such as (i) Hurricane Katrina in the US; (ii) Typhoon Maemi in South Korea; (iii) Kobe; and, (iv) Tohoku Earthquake in Japan that failed to cope with extreme events forms the basis for case study presented here. We argue that structural characteristics of multi-jurisdictional coordination may facilitate or impede in responding to a complex nature of recent disaster. We further highlight the promise of policy network approach in facilitating the development of multi-jurisdictional coordination process which may provide new avenue to improve the communication and coordination of hierarchical command control driven organizations with the local community. Our proposed novel approach in investigating the usefulness of network approach through media content analysis for emergency may provide opportunity as a countermeasure to a traditional hierarchical coordination, which may give further insights in establishing a more effective network for emergency.

cs.SI↗