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IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Genetic Code-Script Source3. Iteracy: A Rosetta Ecosmos Textuality
Massip-Bonet, Angels and Albert Bastardas-Boada, eds.
Complexity Perspectives on Language, Communication and Society.
Berlin: Springer,
2013.
Due in January, the editors are a philologist and a sociolinguist at the University of Barcelona. The work, first found on Complexity Digest whose editor Carlos Gershenon contributes an essay, is cited in Rosetta Cosmos because it perceives human cultural discourse as a further manifestation of nature’s universal deployment of self-organizing, complex network systems. Exemplary chapters are “Sociolinguistics: Towards a Complex Ecological View” by Albert Bastardas-Boada, “Self-Organization in Communicating Groups: The Emergence of Coordination, Shared References and Collective Intelligence” by Francis Heylighen (search), “The Emergence of Complexity in Language: An Evolutionary Perspective” by University of Chicago linguist Salikoko Mufwene, and especially Angels Massip-Bonet’s “Language as a Complex Adaptive System: Towards an Integrative Linguistics” (search). As the sociologist Norbert Elias pointed out, there is a need of new procedural models to get to grasp the complex functioning of human-beings-in-society. An ecological complexity approach could be useful to advance our knowledge. How can we think of a sociolinguistic “ecosystem”? What elements do we need to put in such an ecosystem and what analogies could be applied? The (bio)ecological inspiration is a metaphorical exercise to proceed toward a more holistic approach in dynamic sociolinguistics. However, a language is not a species and, therefore, we need to make our complex ecology socio-cognitive and multidimensional. We need to create theories and represent to ourselves how language behaviour is woven together with its contexts in order to maintain language diversity and, at the same time, foster general human intercommunication on a planetary scale. (Albert Bastardas-Boada) Mehri, Ali and Sahar Mohammadpour Lashkari. Power-Law Regularities in Human Language. European Physical Journal B. 89/241, 2016. Noshirvani University of Technology, Iran, physicists perform an independent analysis of these nonlinear qualities of our sapient writings and conversation to once more affirm the presence of universal patterns. The authors studied range from Shakespeare, Cervantes, and Melville to Darwin, Einstein, (Steven) Weinberg, and Hawking. (I wonder if SW, who claims all is pointless, is aware of an innate mathematics that guides his quill.) See also The Fractal Patterns of Words in a Text (PLoS One, Online June 2015) by the University of Zanjan, Iran, physicists Najafi, Elham Najafi and Amir Darooneh, second Abstract. Compare this work with a concurrent paper from Poland, (search Drozdz) to glimpse a discovery of a textual human uniVerse. Complex structure of human language enables us to exchange very complicated information. This communication system obeys some common nonlinear statistical regularities. We investigate four important long-range features of human language. We perform our calculations for adopted works of seven famous litterateurs. Zipfs law and Heaps law, which imply well-known power-law behaviors, are established in human language, showing a qualitative inverse relation with each other. Furthermore, the informational content associated with the words ordering, is measured by using an entropic metric. We also calculate fractal dimension of words in the text by using box counting method. The fractal dimension of each word, that is a positive value less than or equal to one, exhibits its spatial distribution in the text. Generally, we can claim that the Human language follows the mentioned power-law regularities. Power-law relations imply the existence of long-range correlations between the word types, to convey an especial idea. (Mehri Abstract) Melko, Roger and Juan Carrasquilla.. Language models for quantum simulation. Nature Computational Science. 4/1, 2024. University of Waterloo, Ontario theorists (search each) consider the latest cross-integrations of these widely separated natural and social realms which then increasingly appear to have an innate, common affinity. As Earth continues to learn into this year, the real presence of an actual recursive narrative from uniVerse to US gains a deep veracity. A key challenge in the effort to simulate todays quantum computing devices is the ability to learn and encode the complex correlations that occur between qubits. Emerging technologies based on language models adopted from machine learning have shown unique abilities to learn quantum states. We highlight the contributions that language models are making in the effort to build quantum computers and discuss their future role in the race to quantum advantage. Min, Semi and Juyong Park. Mapping Out Narrative Structures and Dynamics Using Networks and Textual Information. arXiv:1604.03029. Korea Advanced Institute of Science and Technology (KAIST) linguists show how the new science of scale-free networks are exemplified even by cultural literary works from Victor Hugos Les Miserables to J. K. Rowlings Harry Potter. The various characters and their dramatic interactions are found to exhibit typical node and link topologies and dynamics. Their project is seen as a companion to the statistical physics version by MacCarron and Kenna (search). At the same time we also log in The Network Behind the Cosmic Web (Coutinho) which similarly finds the scale-free networks to fit galactic geometries. Into this 21st century might a textual, cognitive, animate genesis procreation at last be witnessed and availed? Human communication is often executed in the form of a narrative, an account of connected events composed of characters, actions, and settings. A coherent narrative structure is therefore a requisite for a well-formulated narrative -- be it fictional or nonfictional -- for informative and effective communication, opening up the possibility of a deeper understanding of a narrative by studying its structural properties. In this paper we present a network-based framework for modeling and analyzing the structure of a narrative, which is further expanded by incorporating methods from computational linguistics to utilize the narrative text. Modeling a narrative as a dynamically unfolding system, we characterize its progression via the growth patterns of the character network, and use sentiment analysis and topic modeling to represent the actual content of the narrative in the form of interaction maps between characters with associated sentiment values and keywords. This is a network framework advanced beyond the simple occurrence-based one most often used until now, allowing one to utilize the unique characteristics of a given narrative to a high degree. Given the ubiquity and importance of narratives, such advanced network-based representation and analysis framework may lead to a more systematic modeling and understanding of narratives for social interactions, expression of human sentiments, and communication. (Abstract) Montemurro, Marcelo and Damian Zanette. Complexity and Universality in the Long-range Order of Words. arXiv:1503.01129. These University of Manchester, UK and Centro Atomico Bariloche, Argentina, systems scientists have been collaborating for some time on an illustrious synthesis of linguistics and physics, which as this section reports, are being found to have a deepest affinity. In 2015, a true universality can be robustly affirmed. See also Quantifying the Information in the Long-range Order of Words in Cortex (Vol. 55, 2014) by MM, Statistical Patterns in Written Language at arXiv:1412.3336 by DZ, and concurrent papers herein by Altmann, Blythe, and Thurner. As is the case of many signals produced by complex systems, language presents a statistical structure that is balanced between order and disorder. Here we review and extend recent results from quantitative characterisations of the degree of order in linguistic sequences that give insights into two relevant aspects of language: the presence of statistical universals in word ordering, and the link between semantic information and the statistical linguistic structure. We first analyse a measure of relative entropy that assesses how much the ordering of words contributes to the overall statistical structure of language. This measure presents an almost constant value close to 3.5 bits/word across several linguistic families. Then, we show that a direct application of information theory leads to an entropy measure that can quantify and extract semantic structures from linguistic samples, even without prior knowledge of the underlying language. (Abstract) Montemurro, Marcelo and Pedro Pury. Long Range Fractal Correlations in Literary Corpora. Fractals. 10/4, 2002. National University of Cordoba and Ciudad University, Cordoba, Argentina mathematicians provide early insights into how the even the composite collection of human writings could be treated with the same self-similar mathematics and geometries as every else in nature. In this paper, we analyze the fractal structure of long human language records by mapping large samples of texts onto time series. The particular mapping set up in this work is inspired on linguistic basis in the sense that is retains the word as the fundamental unit of communication. The results confirm that beyond the short-range correlations resulting from syntactic rules acting at sentence level, long-range structures emerge in large written language samples that give rise to long-range correlations in the use of words. (Abstract) Montgomery, Scott. Science in Translation. Chicago: University of Chicago Press, 2000. A literate inquiry of how knowledge moves between cultures and over historical time. From Greece, Rome, Arabia, and China to medieval Europe and onto modern Japan, each script and language reflects the same starry heavens, physical forces and evolving organisms. Morales, Jose, et al. Rank Dynamics of Word Usage at Multiple Scales. arXiv:1802.07258. We note this posting by National Autonomous University of Mexico, and Aalto University, Finland computer scientists including Carlos Gershenson as a current example of how linguistic textual writings can be treated by and seen to exemplify the same complex network systems just like quantum and genomic to neural and societal. A great truth and realization is thus arising in our midst whence natural phenomena becomes, in turn, deeply textual in kind, a library of cosmos and culture. See also Quantifying the Information in the Long Range Order of Words: Semantic Structures and Universal Linguistic Constraints by Marcelo Montemurro in Cortex (Vol. 55, 2014) The recent dramatic increase in online data availability has allowed researchers to explore human culture with unprecedented detail, such as the growth and diversification of language. In particular, it provides statistical tools to explore whether word use is similar across languages, and if so, whether these generic features appear at different scales of language structure. Here we use the Google Books N-grams dataset to analyze the temporal evolution of word usage in several languages. Using different methods, results show that there are generic properties for different languages at different scales, such as a core of words necessary to minimally understand a language. (Abstract) Mufwene, Salikoko, et al. Complexity in Language: Developmental and Evolutionary Perspectives. Cambridge: Cambridge University Press, 2017. A collection of chapters which consider an innate synthesis of these natural communicative aspects and affinities. It was conceived by Mufwene, the senior University of Chicago linguist (search), along with University of Lyon, France coeditors Christophe Coupe and Francois Pellegrino and draws on conferences and studies since 2011. A wide array includes Complex Adaptive Systems Approach to the Evolution of Language and the Brain by Thomas Schoenemann, A Complexity View of Ontogeny as a Window on Phylogeny by Barbara L. Davis, and Evolutionary Complexity of Social Cognition, Semasiographic Systems and Language by William Croft. The question of complexity, as in what makes one language more 'complex' than another, is a long-established topic of debate amongst linguists. Recently, this issue has been complemented with the view that languages are complex adaptive systems, in which emergence and self-organization play major roles. However, few students of the phenomenon have gone beyond the basic assessment of the number of units and rules in a language (what has been characterized as 'bit complexity') or shown some familiarity with the science of complexity. This book reveals how much can be learned by overcoming these limitations, especially by adopting developmental and evolutionary perspectives. The contributors include specialists of language acquisition, evolution and ecology, grammaticization, phonology, and modeling, all of whom approach languages as dynamical, emergent, and adaptive complex systems. Mukherjee, Animesh, et al. Self-Organization of the Sound Inventories: Analysis and Synthesis of the Occurrence and Co-occurrence Networks of Consonants. Journal of Quantitative Linguistics. 16/2, 2009. Indian Institute of Technology, and Microsoft Research India, computer scientists quantify the presence of natures constant creative principles even in all aspects of our human speech and script. The quotes could equally apply to genomic dynamics and discourse. The sound inventories of the world's languages self-organize themselves, giving rise to similar cross-linguistic patterns. In this work, we attempt to capture this phenomenon of self-organization, which shapes the structure of the consonant inventories, through a complex network approach. For this purpose we define the occurrence and co-occurrence networks of consonants and systematically study some of their important topological properties. A crucial observation is that the occurrence as well as the co-occurrence of consonants across languages follows a power law distribution. This property is arguably a consequence of the principle of preferential attachment. In order to support this argument we propose a synthesis model, which reproduces the degree distribution for the networks to a close approximation. Finally, we discuss how preferential attachment manifests itself through the evolutionary nature of language. (Abstract, 157) Murugan, Arvind, et al. Discriminatory Proofreading Regimes in Nonequilibrium Systems. Physical Review X. 4/021016, 2014. Murugan, with Stanislas Leibler, Systems Biology, and David Huse, Physics, Princeton University first note that biological activities could be viewed as an organic editorial process, which might then have broader apply across natural realms. The work draws on an earlier paper Speed, Dissipation, and Error in Kinetic Proofreading by the authors in PNAS (109/12034, 2012). Our interest is a perception of life and our human phase as engaged in some cosmic writing and reading project, ever trying for better clarity and content. We use ideas from kinetic proofreading, an error-correcting mechanism in biology, to identify new kinetic regimes in nonequilibrium systems. These regimes are defined by the sensitivity of the occupancy of a state of the system to a change in its energy. In biological contexts, higher sensitivity corresponds to stronger discrimination between molecular substrates with different energetics competing in the same reaction. We study this discriminatory ability in systems with discrete states that are connected by a general network of transitions. (Abstract) Najafi, Elham and Amir Darooneh. A New Universality Class in Corpus of Texts: A Statistical Physics Study. Physics Letters A. 382/1140, 2018. University of Zanjan, Iran physicists continue their endeavor to achieve a complex network systems analysis of written documents, which are similarly amenable to this approach, just as all other domains. See also The Fractal Patterns of Words in a Text by the authors in PloS One (Online June 19, 2015). In cultural regard, as a natural, and social realms become deeply scriptural, could these multiple findings be the advent of a worldwise 21st century dispensation so as to newly unite the many historic divisions? Text can be regarded as a complex system. There are some methods in statistical physics which can be used to study this system. In this work, by means of statistical physics methods, we reveal new universal behaviors of texts associating with the fractality values of words in a text. The fractality measure indicates the importance of words in a text by considering distribution pattern of words throughout the text. We observed a power law relation between fractality of text and vocabulary size for texts and corpora. We also observed this behavior in studying biological data. (Abstract)
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