BibSonomy publications for /user/andreab/wordWed Oct 17 03:42:22 CEST 2007Word statistics in Blogs and RSS feeds: Towards empirical universal evidence2007word blog imported statistics We focus on the statistics of word occurrences and of the waiting times between such occurrences in Blogs. Due to the heterogeneity of words' frequencies, the empirical analysis is performed by studying classes of "frequently-equivalent" words, i.e. by grouping words depending on their frequencies. Two limiting cases are considered: the dilute limit, i.e. for those words that are used less than once a day, and the dense limit for frequent words. In both cases, extreme events occur more frequently than expected from the Poisson hypothesis. These deviations from Poisson statistics reveal non-trivial time correlations between events that are associated with bursts of activities. The distribution of waiting times is shown to behave like a stretched exponential and to have the same shape for different sets of words sharing a common frequency, thereby revealing universal features.Thu May 10 17:38:17 CEST 2007Journal of Quantitative Linguistics129-40Dynamics of Text Generation with Realistic Zipf's Distribution.122005vocabulary d4.1 word dictionary distribution zipf tagora frequency growth montemurro simon Wed May 09 12:57:54 CEST 2007Biometrika3/4425On a class of skew distribution functions421955word zipf simon d4.1 distribution tagora frequency Tue May 08 15:54:13 CEST 2007Glottometrics49 - 60Zipf´s law against the text size: a half-rational model42002d4.1 glottometrics word tagora distribution frequency doubleslope mandelbrot entropy zipf Tue May 08 15:51:35 CEST 2007Glottometrics61 - 86How many words are there?42002frequency word doubleslope tagora glottometrics kornai entropy distribution d4.1 zipf mandelbrot Tue May 08 15:29:06 CEST 2007PNAS 788-791 3788--791 Least effort and the origins of scaling in human language1002003mandelbrot tagora zipf word frequency distribution d4.1 ksat language human Tue May 08 15:22:32 CEST 2007American Journal of Psychology311--314Some effects of intermittent silence701957tagora ditribution monkey zipf d4.1 frequency miller word typing Tue May 08 15:13:38 CEST 2007Jorunal of Quantitative Linguistics177-228Quantitative linguistics and complex system studies31996d4.1 zipf distribution word frequency tagora sc-words mandelbrot Tue May 08 15:13:05 CEST 2007Glottometrics87-99Frequency-rank distribution of words in large text samples: phenomenology and models42002glottometrics distribution mandelbrot d4.1 zipf tagora montemurro doubleslope frequency entropy word Tue May 08 14:59:04 CEST 2007LondonCommunication theoryAn infromational theory of the statistical structure of language4861953zipf mandelbrot tagora frequency d4.1 distribution word 1953 Thu May 03 17:23:36 CEST 2007Journal of General Psychology33251--256{The Meaning-Frequency Relationship of Words}19451945frequency d4.1 word zipf tagora distribution Thu May 03 17:22:10 CEST 2007Human Behavior and the Principle of Least Effort1949word distribution tagora frequency d4.1 zipf Thu May 03 17:19:57 CEST 2007ParisInstitut Stenographique de FranceLes Gammes Stenographiques1916d4.1 tagora estoup word zipf mandelbrot first distribution frequency Thu May 03 17:04:50 CEST 2007ScienceMarch300-+{Statistics of Vocabulary}671928first frequency mandelbrot d4.1 word distribution zipf tagora imported Wed May 02 15:44:08 CEST 2007Journal of Information Science4247-257An analysis of Zipf-Mandelbrot language measures and their application to artificial languages191993word zipf tagora imported d4.1 frequency distribution mandelbrot Studies of word frequency distributions have been used in linguisties for some time and are frequently used in information socnce research for such purposes as predicting numbers of key words or computing the significance of a word by its frequency of occurrence In this paper we provide a historical review of some of the developments in a particular aspect of word frequency analysis known as Zipf's Law but in fact first explicitly formulated by E U Condon, and later modified by B Mandelbrot. We present an exploratory analy sis of the use of Mandelbrot's parameters in discriminating among languages and language usage Some suggestions are made for using these parameters to characterize artificial (command) languages or the manner of use of these languages by different groups, for the purpose of enabling a computer interface to respond to users in a manner suited to their backgrounds or skills. Mon Apr 30 15:02:05 CEST 2007New York, NY, USAJ. Inf. Sci.4247--258An analysis of Zipf-Mandelbrot language measures and their application to artificial languages1919931993 word review imported frequency mandelbrot zipf distribution Sat Apr 28 16:11:21 CEST 2007Maximal nonsymmetric entropy leads naturally to Zipf's law20062006 imported distribution word mandelbrot zipf d4.1 tagora frequency Sat Apr 28 16:06:40 CEST 2007Glottometrics1--26Algorithmic information, complexity and Zipf's law42002d4.1 tagora entropy frequency distribution mandelbrot zipf word glottometrics Zipf’s law of word frequencies for language discourses is established with statistical rigor. Data show a departure from Zipf’s power law term at low frequencies. This is accounted by a modi-fying exponential term. Both arise naturally in a model for word frequencies based on Information Theory, algorithmic coding of a text preserving the symbol sequence, concepts from quantum statistical physics and computer science and extremum principles. The Optimum Meaning Preserving Code (OMPC) of the discourse is realized when word frequencies follow the Modified Power Law (MPL). The model predicts a variant of the MPL for the relative frequencies of a small fixed set of symbols such as letters, phonemes and grammatical words. The OMPC can be viewed as containing orderly and random parts. This leads us to a quantitative definition of complexity of a string (C) that tends to 0 for the extremes of ‘all order’ and ‘all random’ but is a maximum (C = 1) for a mixture of both (Gell-Mann). It is found that natural languages have maximum complexity. The uniqueness of Zipf’s power law index (γ = 2) is shown to arise in four different ways, one of which depends on scale invariance characteristic of fractal structures. It is argued that random text models are unsuitable for natural languages. It is speculated that a drastic change in symbol frequency distribution starting from phrases is related to emergence of meaning and coherence of a discourse.Sat Apr 28 15:55:45 CEST 2007Phys. Rev. EJun66371--6375Possible origin of power-law behavior in $n$-tuple Zipf analysis531996tagora word zipf frequency distribution stanley mandelbrot d4.1 imported