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Well-established automatic analyses of texts mainly consider frequencies of linguistic units, e.g. letters, words, and bigrams. In a recent, alternative approach, medium and large-scale text structures were used in opposition to the belief that text structure is dominated by the language features. In this paper, we introduce a generalized similarity measure to compare texts which accounts for both the network structure of texts and the role of individual words in the networks. The similarity measure is used for authorship attribution of three collections of books, each composed of 8 authors and 10 books per author. High accuracy rates were obtained with typical values between 90 % and 98 . 75 % , much higher than with the traditional term frequency-inverse document frequency (tf-idf) approach for the same collections. These accuracies are also higher than those obtained solely with the topology of networks. We conclude that the different properties of specific words on the macroscopic scale structure of a whole text are as relevant as their frequency of appearance; conversely, considering the identity of nodes brings further knowledge about a piece of text represented as a network. [ABSTRACT FROM AUTHOR]

GitHub is a social collaborative coding platform on which software developers not only collaborate on codes but also share knowledge through blogs using GitHub Pages. In this article, we analyze the blogging behavior of software developers on GitHub Pages. The results show that both the commit number and the inter-event time of two consecutive blogging actions follow heavy-tailed distribution. We further observe a significant variety of activity among individual developers, and a strongly positive correlation between the activity and the power-law exponent of the inter-event time distribution. We also find a difference between the user behaviors of GitHub Pages and other online systems which is driven by the diversity of users and length of contents. In addition, our result shows an obvious difference between the majority of developers and elite developers in their burstiness property. [ABSTRACT FROM AUTHOR]

As the largest microblog service in China, Sina Weibo has attracted numerous automated applications (known as bots) due to its popularity and open architecture. We classify the active users from Sina Weibo into human, bot-based and hybrid groups based solely on the study of temporal features of their posting behavior. The anomalous burstiness parameter and time-interval entropy value are exploited to characterize automation. We also reveal different behavior patterns among the three types of users regarding their reposting ratio, daily rhythm and active days. Our findings may help Sina Weibo manage a better community and should be considered for dynamic models of microblog behaviors. [ABSTRACT FROM AUTHOR]

We study the variation of word frequencies in Russian literary texts. Our findings indicate that the standard deviation of a word’s frequency across texts depends on its average frequency according to a power law with exponent 1 2 < α < 1 , which shows that the rarer words have a relatively larger degree of frequency volatility (that is, higher “burstiness”). A latent factor model has been estimated to investigate the structure of the word frequency distribution. The findings suggest that the dependence of a word’s frequency volatility on its average frequency can be explained by the asymmetry in the distribution of latent factors. [ABSTRACT FROM AUTHOR]

Center of pressure (COP) signals have been widely used to investigate various aspects of human balance during quiet standing. Here, we compute a set of measures — including burstiness, memory and local variation — to quantify temporal patterns in COP zero-crossings. Specifically, we investigate the effect of stance type (bipedal and unipedal) on the proposed measures. Data were obtained from a group of 20 health and young subjects. The results suggest that these measures are able to detect differences in zero-crossing patterns between bipedal and unipedal stance. We also perform a test–retest reliability analysis for each measure and a pairwise correlation analysis for combinations of measures. Finally, we discuss some potential implications of our results for the study of human balance. • Statistical physics and complex systems tools are used to characterize temporal inhomogeneity in postural sway signals. • Differences between double leg and single leg conditions can be detected using burstiness, memory and local variation. • Zero-crossing patterns may provide information about the dynamics of human balance. [ABSTRACT FROM AUTHOR]

Abstract: Recently, extensive empirical evidence shows that the timing of human behaviors obeys non-Possion statistics with heavy-tailed interevent time distribution. In this paper, we empirically study the correspondence pattern of a great Chinese scientist, named Hsue-Shen Tsien. Both the interevent time distribution and response time distributions deviate from the Poisson statistics, showing an approximate power-law decaying. The two power-law exponents are more or less the same (about 2.1), which strongly support the hypothesis in [A. Vázquez, J.G. Oliveira, Z. Dezsö, K.-I. Goh, I. Kondor, A.-L. Barabási, Phys. Rev. E 73 (2006) 036127] that the response time distribution of the tasks could in fact drive the interevent time distribution, and both the two distributions should decay with the same exponent. Our result is against the claim in [A. Vázquez, J.G. Oliveira, Z. Dezsö, K.-I. Goh, I. Kondor, A.-L. Barabási, Phys. Rev. E 73 (2006) 036127], which suggests the human correspondence pattern belongs to a universality class with exponent 1.5. [Copyright &y& Elsevier]

The computation of teletraffic (traffic for short) delay bound is crucial to the guaranteed quality of service in computer communication networks. Traditional non-fractal bounds of traffic delay are loose so that network resources may be over-required for guaranteed quality of service. How to obtain a tighter bound of traffic delay, in fact, is an open problem. This paper gives a solution to that problem by proposing four fractal delay bounds of traffic. We will show that the present fractal delay bounds are tighter than the conventional non-fractal ones. • Fractal delay bound of traffic is proposed. • Present bound is tighter than conventional non-fractal one. • Formula to compute the fractal delay bound is presented. • Cast study with real traffic data is given. [ABSTRACT FROM AUTHOR]