Correlational Studies in Typological and Historical Linguistics

Ladd, D. Robert; Roberts, Seán G.; Dediu, Dan

doi:10.1146/annurev-linguist-030514-124819

Cited by 67 publications

(72 citation statements)

References 111 publications

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“…In particular, similarities and differences across languages cannot be compared as if they were statistically independent data points, because closely related languages are expected to be similar in many aspects. This hierarchical pattern of similarities can confound attempts to find causal correlations between aspects of human language and culture by creating spurious correlations, a methodological challenge sometimes referred to as Galton's problem (23,24). The comparison of rates of evolutionary change in different lineages presents additional challenges because we need to be able to infer the number of evolutionary changes that have occurred along each lineage (25,26).…”

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confidence: 99%

Rate of language evolution is affected by population size

Bromham

Hua

Fitzpatrick

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

101

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The effect of population size on patterns and rates of language evolution is controversial. Do languages with larger speaker populations change faster due to a greater capacity for innovation, or do smaller populations change faster due to more efficient diffusion of innovations? Do smaller populations suffer greater loss of language elements through founder effects or drift, or do languages with more speakers lose features due to a process of simplification? Revealing the influence of population size on the tempo and mode of language evolution not only will clarify underlying mechanisms of language change but also has practical implications for the way that language data are used to reconstruct the history of human cultures. Here, we provide, to our knowledge, the first empirical, statistically robust test of the influence of population size on rates of language evolution, controlling for the evolutionary history of the populations and formally comparing the fit of different models of language evolution. We compare rates of gain and loss of cognate words for basic vocabulary in Polynesian languages, an ideal test case with a well-defined history. We demonstrate that larger populations have higher rates of gain of new words whereas smaller populations have higher rates of word loss. These results show that demographic factors can influence rates of language evolution and that rates of gain and loss are affected differently. These findings are strikingly consistent with general predictions of evolutionary models. language evolution | sister-pair comparison | Austronesian | lexical change | Poisson regression P opulation size can play a crucial role in the evolution of languages and cultures (1). However, opinions differ on both the possible mechanisms and the expected patterns (2-7). It has been suggested that larger populations will generate more innovations and are less prone to random loss of cultural elements (8-10), but may have less efficient diffusion of innovations than smaller populations (4). Alternatively, languages spoken by small isolated populations of speakers may have lower rates of loss if they maintain tighter cultural norms that improve transmission and resist change (11). Rates of change might be accelerated by founder effects when a new population is started from a small number of colonists, which could result in loss of elements from the ancestral language (11-13). Population size might also influence language complexity if small populations can develop greater linguistic complexity (11), whereas large, widespread languages that are often learned by adults may become simplified (14). Conversely, it has been suggested that the average rate of word turnover is essentially the same in all languages (15-17), or that it is determined primarily by other factors such as language contact (6, 18).Uncovering systematic patterns of rates of language change may reveal underlying mechanisms of language evolution (13,19). In particular, investigating rates of language change can demonstrate whether langua...

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confidence: 99%

Rate of language evolution is affected by population size

Bromham

Hua

Fitzpatrick

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

101

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“…As cognitive science continues to evolve, artificial intelligent approaches such as statistical learning and network science are becoming increasingly attractive and relevant to researchers in cognitive science and artificial intelligence. Recent work [1][2][3][4][5][6] demonstrates that statistical learning is one of the most deeply explored phenomena in the field of cognitive science. Noticeably, the increasing utilization of network science with statistical learning [7][8][9] makes network-based approaches a robust tool in cognitive science and computational linguistics [10,11].…”

Section: Introductionmentioning

confidence: 99%

iWordNet: A New Approach to Cognitive Science and Artificial Intelligence

Chang

2017

Advances in Artificial Intelligence

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One of the main challenges in artificial intelligence or computational linguistics is understanding the meaning of a word or concept. We argue that the connotation of the term "understanding," or the meaning of the word "meaning," is merely a word mapping game due to unavoidable circular definitions. These circular definitions arise when an individual defines a concept, the concepts in its definition, and so on, eventually forming a personalized network of concepts, which we call an iWordNet. Such an iWordNet serves as an external representation of an individual's knowledge and state of mind at the time of the network construction. As a result, "understanding" and knowledge can be regarded as a calculable statistical property of iWordNet topology. We will discuss the construction and analysis of the iWordNet, as well as the proposed "Path of Understanding" in an iWordNet that characterizes an individual's understanding of a complex concept such as a written passage. In our pilot study of 20 subjects we used a regression model to demonstrate that the topological properties of an individual's iWordNet are related to his IQ score, a relationship that suggests iWordNets as a potential new methodology to studying cognitive science and artificial intelligence.

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“…Consequently, languages are not independent data points. This problem has long been recognised in cultural and linguistic studies as 'Galton's problem' (Tylor 1889;Mace & Pagel 1994;Bentz & Winter 2013;Roberts & Winters 2013;Ladd et al 2015), but linguists have few methods to effectively overcome this issue. One method to circumvent statistical non-independence in comparative biology is to use sisterpair comparisons, which examines the differences between pairs of closest relatives (sisters) and compares this to other more distantly related lineages (outgroup).…”

Section: Introductionmentioning

confidence: 99%

The relationship between population size and rates of language evolution

Welsh¹

2016

AURJ

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Languages change over time, and the evolution of languages is similar in many ways to biological evolution. But are all patterns predicted by evolutionary theory also seen in language evolution? One well-known biological pattern is that smaller populations tend to lose genetic diversity, and large populations tend to become more genetically diverse, but the effect of population size on language evolution is highly debated. Do small populations have faster rates of change through greater diffusion of new words, or slower rates of change due to strict language transmission? Do large populations gain words faster through more innovators, or lose faster due to simplification across varied speaker communities? This extract, taken from Welsh's (2015) Honours thesis, provides the background on the relationship between population size and rate of language change, discusses some of the contrasting hypotheses and methodological techniques and explains the research currently being conducted that attempts to clarify the relationship.

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Correlational Studies in Typological and Historical Linguistics

Cited by 67 publications

References 111 publications

Rate of language evolution is affected by population size

Rate of language evolution is affected by population size

iWordNet: A New Approach to Cognitive Science and Artificial Intelligence

The relationship between population size and rates of language evolution

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