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Special Issue "Complexity of Human Language and Cognition"

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A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: closed (31 December 2009)

Special Issue Editor

Guest Editor
Dr. Ramon Ferrer i Cancho

Complexity & Quantitative Linguistics Lab, LARCA Research Group, Departament de Ciencies de la Computacio, Universitat Politecnica de Catalunya, Campus Nord, Edifici Omega Jordi Girona Salgado 1-3, 08034 Barcelona (Catalonia), Spain
Website | E-Mail
Phone: +34 934137870
Fax: +34 934137787
Interests: applications of information theory and network theory to biology and linguistics; quantitative linguistics; corpus linguistics; origins and evolution of language

Special Issue Information

Dear Colleagues,

This Special Issue is devoted to shed light on the complexity of human language and cognition from a transdisciplinary perspective. Much recent progress on the complexity of human language and cognition from network and information theory is scattered in the literature of physics, cognitive science, neurology, biology, quantitative linguistics...It is time to bring together efforts from different areas in a more coherent environment to show that new insights into different areas of human language and cognition can originate from common theoretical approaches.

There is no a priori constraint on the aspect of human language or cognition addressed. There is no constraint either on the background of the contribution: physics, cognitive science, neurology, biology, quantitative linguistics... The only condition is that the insight comes from a theoretical discipline such as information theory or network theory. Theoretical insights from other theoretical disciplines might be considered.

Ramon Ferrer i Cancho, Ph.D.
Guest Editor

Keywords

  • complexity
  • language
  • cognition
  • information theory
  • graph theory
  • network theory
  • quantitative linguistics
  • statistical mechanics

Published Papers (7 papers)

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Research

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Open AccessArticle Fitting Ranked Linguistic Data with Two-Parameter Functions
Entropy 2010, 12(7), 1743-1764; doi:10.3390/e12071743
Received: 4 April 2010 / Revised: 18 May 2010 / Accepted: 1 July 2010 / Published: 7 July 2010
Cited by 21 | PDF Full-text (964 KB) | HTML Full-text | XML Full-text
Abstract
It is well known that many ranked linguistic data can fit well with one-parameter models such as Zipf’s law for ranked word frequencies. However, in cases where discrepancies from the one-parameter model occur (these will come at the two extremes of the rank),
[...] Read more.
It is well known that many ranked linguistic data can fit well with one-parameter models such as Zipf’s law for ranked word frequencies. However, in cases where discrepancies from the one-parameter model occur (these will come at the two extremes of the rank), it is natural to use one more parameter in the fitting model. In this paper, we compare several two-parameter models, including Beta function, Yule function, Weibull function—all can be framed as a multiple regression in the logarithmic scale—in their fitting performance of several ranked linguistic data, such as letter frequencies, word-spacings, and word frequencies. We observed that Beta function fits the ranked letter frequency the best, Yule function fits the ranked word-spacing distribution the best, and Altmann, Beta, Yule functions all slightly outperform the Zipf’s power-law function in word ranked- frequency distribution. Full article
(This article belongs to the Special Issue Complexity of Human Language and Cognition)
Open AccessArticle A Network Model of Interpersonal Alignment in Dialog
Entropy 2010, 12(6), 1440-1483; doi:10.3390/e12061440
Received: 9 May 2010 / Accepted: 3 June 2010 / Published: 9 June 2010
Cited by 28 | PDF Full-text (2596 KB)
Abstract
In dyadic communication, both interlocutors adapt to each other linguistically, that is, they align interpersonally. In this article, we develop a framework for modeling interpersonal alignment in terms of the structural similarity of the interlocutors’ dialog lexica. This is done by means
[...] Read more.
In dyadic communication, both interlocutors adapt to each other linguistically, that is, they align interpersonally. In this article, we develop a framework for modeling interpersonal alignment in terms of the structural similarity of the interlocutors’ dialog lexica. This is done by means of so-called two-layer time-aligned network series, that is, a time-adjusted graph model. The graph model is partitioned into two layers, so that the interlocutors’ lexica are captured as subgraphs of an encompassing dialog graph. Each constituent network of the series is updated utterance-wise. Thus, both the inherent bipartition of dyadic conversations and their gradual development are modeled. The notion of alignment is then operationalized within a quantitative model of structure formation based on the mutual information of the subgraphs that represent the interlocutor’s dialog lexica. By adapting and further developing several models of complex network theory, we show that dialog lexica evolve as a novel class of graphs that have not been considered before in the area of complex (linguistic) networks. Additionally, we show that our framework allows for classifying dialogs according to their alignment status. To the best of our knowledge, this is the first approach to measuring alignment in communication that explores the similarities of graph-like cognitive representations. Full article
(This article belongs to the Special Issue Complexity of Human Language and Cognition)
Open AccessArticle Sound Symbolism in Basic Vocabulary
Entropy 2010, 12(4), 844-858; doi:10.3390/e12040844
Received: 23 December 2009 / Revised: 2 April 2010 / Accepted: 7 April 2010 / Published: 9 April 2010
Cited by 10 | PDF Full-text (164 KB) | HTML Full-text | XML Full-text
Abstract
The relationship between meanings of words and their sound shapes is to a large extent arbitrary, but it is well known that languages exhibit sound symbolism effects violating arbitrariness. Evidence for sound symbolism is typically anecdotal, however. Here we present a systematic approach.
[...] Read more.
The relationship between meanings of words and their sound shapes is to a large extent arbitrary, but it is well known that languages exhibit sound symbolism effects violating arbitrariness. Evidence for sound symbolism is typically anecdotal, however. Here we present a systematic approach. Using a selection of basic vocabulary in nearly one half of the world’s languages we find commonalities among sound shapes for words referring to same concepts. These are interpreted as due to sound symbolism. Studying the effects of sound symbolism cross-linguistically is of key importance for the understanding of language evolution. Full article
(This article belongs to the Special Issue Complexity of Human Language and Cognition)
Open AccessArticle Article Omission in Dutch Children with SLI: A Processing Approach
Entropy 2010, 12(4), 798-817; doi:10.3390/e12040798
Received: 21 December 2009 / Revised: 5 March 2010 / Accepted: 7 April 2010 / Published: 8 April 2010
Cited by 4 | PDF Full-text (270 KB) | HTML Full-text | XML Full-text
Abstract
Children with Specific Language Impairment (SLI) show difficulties with grammatical morphology. Based on the data from 12 Dutch children with SLI, an information-theoretical model is proposed in which the noun-article set dependency is modeled as a channel. We propose that reduced capacity of
[...] Read more.
Children with Specific Language Impairment (SLI) show difficulties with grammatical morphology. Based on the data from 12 Dutch children with SLI, an information-theoretical model is proposed in which the noun-article set dependency is modeled as a channel. We propose that reduced capacity of this channel is responsible for article omission. The Kullback-Leibler divergence between input and output distribution of article production provides an index of the channel capacity, which is shown to correlate with the percentage of article omission and to lag behind in SLI development as compared to typically developing children. Full article
(This article belongs to the Special Issue Complexity of Human Language and Cognition)
Open AccessArticle Statistical Information and Uncertainty: A Critique of Applications in Experimental Psychology
Entropy 2010, 12(4), 720-771; doi:10.3390/e12040720
Received: 11 February 2010 / Revised: 10 March 2010 / Accepted: 1 April 2010 / Published: 7 April 2010
Cited by 8 | PDF Full-text (446 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents, first, a formal exploration of the relationships between information (statistically defined), statistical hypothesis testing, the use of hypothesis testing in reverse as an investigative tool, channel capacity in a communication system, uncertainty, the concept of entropy in thermodynamics, and Bayes’
[...] Read more.
This paper presents, first, a formal exploration of the relationships between information (statistically defined), statistical hypothesis testing, the use of hypothesis testing in reverse as an investigative tool, channel capacity in a communication system, uncertainty, the concept of entropy in thermodynamics, and Bayes’ theorem. This exercise brings out the close mathematical interrelationships between different applications of these ideas in diverse areas of psychology. Subsequent illustrative examples are grouped under (a) the human operator as an ideal communications channel, (b) the human operator as a purely physical system, and (c) Bayes’ theorem as an algorithm for combining information from different sources. Some tentative conclusions are drawn about the usefulness of information theory within these different categories. (a) The idea of the human operator as an ideal communications channel has long been abandoned, though it provides some lessons that still need to be absorbed today. (b) Treating the human operator as a purely physical system provides a platform for the quantitative exploration of many aspects of human performance by analogy with the analysis of other physical systems. (c) The use of Bayes’ theorem to calculate the effects of prior probabilities and stimulus frequencies on human performance is probably misconceived, but it is difficult to obtain results precise enough to resolve this question. Full article
(This article belongs to the Special Issue Complexity of Human Language and Cognition)
Open AccessArticle Comparative Analysis of Networks of Phonologically Similar Words in English and Spanish
Entropy 2010, 12(3), 327-337; doi:10.3390/e12030327
Received: 4 December 2009 / Revised: 16 February 2010 / Accepted: 21 February 2010 / Published: 2 March 2010
Cited by 20 | PDF Full-text (234 KB) | HTML Full-text | XML Full-text
Abstract
Previous network analyses of several languages revealed a unique set of structural characteristics. One of these characteristics—the presence of many smaller components (referred to as islands)—was further examined with a comparative analysis of the island constituents. The results showed that Spanish words
[...] Read more.
Previous network analyses of several languages revealed a unique set of structural characteristics. One of these characteristics—the presence of many smaller components (referred to as islands)—was further examined with a comparative analysis of the island constituents. The results showed that Spanish words in the islands tended to be phonologically and semantically similar to each other, but English words in the islands tended only to be phonologically similar to each other. The results of this analysis yielded hypotheses about language processing that can be tested with psycholinguistic experiments, and offer insight into cross-language differences in processing that have been previously observed. Full article
(This article belongs to the Special Issue Complexity of Human Language and Cognition)

Review

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Open AccessReview Semantic Networks: Structure and Dynamics
Entropy 2010, 12(5), 1264-1302; doi:10.3390/e12051264
Received: 21 February 2010 / Accepted: 1 May 2010 / Published: 14 May 2010
Cited by 61 | PDF Full-text (1439 KB)
Abstract
During the last ten years several studies have appeared regarding language complexity. Research on this issue began soon after the burst of a new movement of interest and research in the study of complex networks, i.e., networks whose structure is irregular,
[...] Read more.
During the last ten years several studies have appeared regarding language complexity. Research on this issue began soon after the burst of a new movement of interest and research in the study of complex networks, i.e., networks whose structure is irregular, complex and dynamically evolving in time. In the first years, network approach to language mostly focused on a very abstract and general overview of language complexity, and few of them studied how this complexity is actually embodied in humans or how it affects cognition. However research has slowly shifted from the language-oriented towards a more cognitive-oriented point of view. This review first offers a brief summary on the methodological and formal foundations of complex networks, then it attempts a general vision of research activity on language from a complex networks perspective, and specially highlights those efforts with cognitive-inspired aim. Full article
(This article belongs to the Special Issue Complexity of Human Language and Cognition)

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