Towards the quantification of the semantic information encoded in written language

Written language is a complex communication signal capable of conveying information encoded in the form of ordered sequences of words. Beyond the local order ruled by grammar, semantic and thematic structures affect long-range patterns in word usage. Here, we show that a direct application of information theory quantifies the relationship between the statistical distribution of words and the semantic content of the text. We show that there is a characteristic scale, roughly around a few thousand words, which establishes the typical size of the most informative segments in written language. Moreover, we find that the words whose contributions to the overall information is larger, are the ones more closely associated with the main subjects and topics of the text. This scenario can be explained by a model of word usage that assumes that words are distributed along the text in domains of a characteristic size where their frequency is higher than elsewhere. Our conclusions are based on the analysis of a large database of written language, diverse in subjects and styles, and thus are likely to be applicable to general language sequences encoding complex information.Comment: 19 pages, 4 figure

Entropic analysis of the role of words in literary texts

Beyond the local constraints imposed by grammar, words concatenated in long sequences carrying a complex message show statistical regularities that may reflect their linguistic role in the message. In this paper, we perform a systematic statistical analysis of the use of words in literary English corpora. We show that there is a quantitative relation between the role of content words in literary English and the Shannon information entropy defined over an appropriate probability distribution. Without assuming any previous knowledge about the syntactic structure of language, we are able to cluster certain groups of words according to their specific role in the text.Comment: 9 pages, 5 figure

Not too late to learn from the Sydney Olympics experience: Opportunities offered by multimodality in current transport policy

Sydney is the Australian city that attracts the most global attention with its beautiful harbour, its iconic attractions of the harbour bridge and opera house. Tourists may leave Sydney with a complimentary view of Sydney’s public transport but the Sydneysider’s assessments of Sydney’s public transport system is often much harsher, especially if the journey requires travel beyond the immediate centre of the city. In Sydney, the reference point of what constitutes a functioning transport system is informed by the success of the transport system in meeting the needs of the participants and observers at the Olympics in 2000. Changes to the transport system to provide more multimodal travel were supported by Sydneysiders and visitors and this paper analyses why this success has not been translated into everyday public transport. The analysis of the paper allows the opportunities which still exist for Sydney to benefit from the success of the Olympics to be highlighted. These opportunities involve strengthening the opportunities for, and acceptance of, multimodal trips by the travelling public

Homologous self-organising scale-invariant properties characterise long range species spread and cancer invasion

The invariance of some system properties over a range of temporal and/or spatial scales is an attribute of many processes in nature1, often characterised by power law functions and fractal geometry2. In particular, there is growing consensus in that fat-tailed functions like the power law adequately describe long-distance dispersal (LDD) spread of organisms 3,4. Here we show that the spatial spread of individuals governed by a power law dispersal function is represented by a clear and unique signature, characterised by two properties: A fractal geometry of the boundaries of patches generated by dispersal with a fractal dimension D displaying universal features, and a disrupted patch size distribution characterised by two different power laws. Analysing patterns obtained by simulations and real patterns from species dispersal and cell spread in cancer invasion we show that both pattern properties are a direct result of LDD and localised dispersal and recruitment, reflecting population self-organisation

Beyond the Zipf-Mandelbrot law in quantitative linguistics

In this paper the Zipf-Mandelbrot law is revisited in the context of linguistics. Despite its widespread popularity the Zipf--Mandelbrot law can only describe the statistical behaviour of a rather restricted fraction of the total number of words contained in some given corpus. In particular, we focus our attention on the important deviations that become statistically relevant as larger corpora are considered and that ultimately could be understood as salient features of the underlying complex process of language generation. Finally, it is shown that all the different observed regimes can be accurately encompassed within a single mathematical framework recently introduced by C. Tsallis.Comment: 6 pages and 7 figures; minor changes in text, added referece

Conversion of phase information into a spike-count code by bursting neurons

Single neurons in the cerebral cortex are immersed in a fluctuating electric field, the local field potential (LFP), which mainly originates from synchronous synaptic input into the local neural neighborhood. As shown by recent studies in visual and auditory cortices, the angular phase of the LFP at the time of spike generation adds significant extra information about the external world, beyond the one contained in the firing rate alone. However, no biologically plausible mechanism has yet been suggested that allows downstream neurons to infer the phase of the LFP at the soma of their pre-synaptic afferents. Therefore, so far there is no evidence that the nervous system can process phase information. Here we study a model of a bursting pyramidal neuron, driven by a time-dependent stimulus. We show that the number of spikes per burst varies systematically with the phase of the fluctuating input at the time of burst onset. The mapping between input phase and number of spikes per burst is a robust response feature for a broad range of stimulus statistics. Our results suggest that cortical bursting neurons could play a crucial role in translating LFP phase information into an easily decodable spike count code

Adaptive Preference Formation & Autonomy: Moving towards Respect

First lines of the Introduction (as abstract not provided): This thesis seeks to primarily answer the following question: are adapted preferences autonomous? In pursuing the answer of this question, I am unsurprisingly faced with two importantly related queries: firstly, what actually is adaptive preference formation? And secondly, what kind of theory of autonomy is correct and why? In the spirit of question answering, the first chapter of this thesis seeks to provide a more robust account of adaptive preference formation (herein APF), a theory which states that the preferences held by an agent can be subconsciously causally produced by the restriction of options. Through an examination of Jon Elster’s original account of the concept, and a consideration of Amartya Sen and Martha Nussbaum’s contemporary interpretations of Elster’s account, I intend to flesh out the mechanics of APF, considering the necessary and sufficient conditions for APF. This section aims to solidify the descriptive literature of APF, with a focus on differentiating the process from other similar concepts such as character planning and internalised oppression (herein IO). Ultimately, I conclude with a variation of Elster’s account and produce my own examples of agents who hold adapted preferences (herein AP)

Dynamics and nonequilibrium states in the Hamiltonian mean-field model: A closer look

We critically revisit the evidence for the existence of quasistationary states in the globally coupled XY (or Hamiltonian mean-field) model. A slow-relaxation regime at long times is clearly revealed by numerical realizations of the model, but no traces of quasistationarity are found during the earlier stages of the evolution. We point out the nonergodic properties of this system in the short-time range, which makes a standard statistical description unsuitable. New aspects of the evolution during the nonergodic regime, and of the energy distribution function in the final approach to equilibrium, are disclosed