Semantic Factors Predict the Rate of Lexical Replacement of Content Words

Rating norms should be calculated from cumulative link mixed effects models

Studies which provide norms of Likert ratings typically report per-item summary statistics. Traditionally, these summary statistics comprise the mean and the standard deviation (SD) of the ratings, and the number of observations. Such summary statistics can preserve the rank order of items, but provide distorted estimates of the relative distances between items because of the ordinal nature of Likert ratings. Inter-item relations in such ordinal scales can be more appropriately modelled by cumulative link mixed effects models (CLMMs). In a series of simulations, and with a reanalysis of an existing rating norms dataset, we show that CLMMs can be used to more accurately norm items, and can provide summary statistics analogous to the traditionally reported means and SDs, but which are disentangled from participants' response biases. CLMMs can be applied to solve important statistical issues that exist for more traditional analyses of rating norms.

Supernatural explanations across 114 societies are more common for natural than social phenomena

Humans across the globe use supernatural beliefs to explain the world around them. This article explores whether cultural groups invoke the supernatural more to explain natural phenomena (for example, storms, disease outbreaks) or social phenomena (for example, murder, warfare). Quantitative analysis of ethnographic text across 114 geographically and culturally diverse societies found that supernatural explanations are more prevalent for natural than for social phenomena, consistent with theories that ground the origin of religious belief in a human tendency to perceive intent and agency in the natural world. Despite the dominance of supernatural explanations of natural phenomena, supernatural explanations of social phenomena were especially prevalent in urbanized societies with more socially complex and anonymous groups. Our results show how people use supernatural beliefs as explanatory tools in non-industrial societies, and how these applications vary across small-scale communities versus large and urbanized groups.

Valence-dependent mutation in lexical evolution

A central goal of linguistics is to understand how words evolve. Past research has found that macro-level factors such as frequency of word usage and population size explain the pace of lexical evolution. Here we focus on cognitive and affective factors, testing whether valence (positivity-negativity) explains lexical evolution rates. Using estimates of cognate replacement rates for 200 concepts on an Indo-European language tree spanning six to ten millennia, we find that negative valence correlates with faster cognate replacement. This association holds when controlling for frequency of use, and follow-up analyses show that it is most robust for adjectives ('dirty' versus 'clean'; 'bad' versus 'good'); it does not consistently reach statistical significance for verbs, and never reaches significance for nouns. We also present experiments showing that individuals are more likely to replace words for negative versus positive concepts. Our findings suggest that emotional valence affects micro-level guided variation, which drives macro-level valence-dependent mutation in adjectives.

Cross-linguistic conditions on word length

Based on a dataset representing close to ¾ of the world's languages we investigate differences among languages and between items on the Swadesh list with regard to mean word length from a linguistic typological point of view. Mapping the world-wide distribution of word length shows convergence at a continent-wide level, a Pacific Rim signature, and a tendency for large word length averages to be a recessive trait. The amount of data, which is unparalleled in previous, related studies, allows us to provide more solid estimates and accounts for the interrelationships between word length, phoneme segment inventory size, and population size than was previously possible. Word length differences between items exhibit robust, universal tendencies, which are discussed in relation to other quantities, including stability, synonymy, and attestation.

The sound of swearing: Are there universal patterns in profanity?

Why do swear words sound the way they do? Swear words are often thought to have sounds that render them especially fit for purpose, facilitating the expression of emotion and attitude. To date, however, there has been no systematic cross-linguistic investigation of phonetic patterns in profanity. In an initial, pilot study we explored statistical regularities in the sounds of swear words across a range of typologically distant languages. The best candidate for a cross-linguistic phonemic pattern in profanity was the absence of approximants (sonorous sounds like l, r, w and y). In Study 1, native speakers of various languages (Arabic, Chinese, Finnish, French, German, Spanish; N = 215) judged foreign words less likely to be swear words if they contained an approximant. In Study 2 we found that sanitized versions of English swear words – like darn instead of damn – contain significantly more approximants than the original swear words. Our findings reveal that not all sounds are equally suitable for profanity, and demonstrate that sound symbolism – wherein certain sounds are intrinsically associated with certain meanings – is more pervasive than has previously been appreciated, extending beyond denoting single concepts to serving pragmatic functions.

Linking norms, ratings, and relations of words and concepts across multiple language varieties

Psychologists and linguists collect various data on word and concept properties. In psychology, scholars have accumulated norms and ratings for a large number of words in languages with many speakers. In linguistics, scholars have accumulated cross-linguistic information about the relations between words and concepts. Until now, however, there have been no efforts to combine information from the two fields, which would allow comparison of psychological and linguistic properties across different languages. The Database of Cross-Linguistic Norms, Ratings, and Relations for Words and Concepts (NoRaRe) is the first attempt to close this gap. Building on a reference catalog that offers standardization of concepts used in historical and typological language comparison, it integrates data from psychology and linguistics, collected from 98 data sets, covering 65 unique properties for 40 languages. The database is curated with the help of manual, automated, semi-automated workflows and uses a software API to control and access the data. The database is accessible via a web application, the software API, or using scripting languages. In this study, we present how the database is structured, how it can be extended, and how we control the quality of the data curation process. To illustrate its application, we present three case studies that test the validity of our approach, the accuracy of our workflows, and the integrative potential of the database. Due to regular version updates, the NoRaRe database has the potential to advance research in psychology and linguistics by offering researchers an integrated perspective on both fields.

Evolution of emotion semantics

Humans possess the unique ability to communicate emotions through language. Although concepts like anger or awe are abstract, there is a shared consensus about what these English emotion words mean. This consensus may give the impression that their meaning is static, but we propose this is not the case. We cannot travel back to earlier periods to study emotion concepts directly, but we can examine text corpora, which have partially preserved the meaning of emotion words. Using natural language processing of historical text, we found evidence for semantic change in emotion words over the past century and that varying rates of change were predicted in part by an emotion concept's prototypicality-how representative it is of the broader category of "emotion". Prototypicality negatively correlated with historical rates of emotion semantic change obtained from text-based word embeddings, beyond more established variables including usage frequency in English and a second comparison language, French. This effect for prototypicality did not consistently extend to the semantic category of birds, suggesting its relevance for predicting semantic change may be category-dependent. Our results suggest emotion semantics are evolving over time, with prototypical emotion words remaining semantically stable, while other emotion words evolve more freely.

Iconicity and Diachronic Language Change

Iconicity, the resemblance between the form of a word and its meaning, has effects on behavior in both communicative symbol development and language learning experiments. These results have invited speculation about iconicity being a key feature of the origins of language, yet the presence of iconicity in natural languages seems limited. In a diachronic study of language change, we investigated the extent to which iconicity is a stable property of vocabulary, alongside previously investigated psycholinguistic predictors of change. Analyzing 784 English words with data on their historical forms, we found that stable words are higher in iconicity, longer in length, and earlier acquired during development, but that the role of frequency and grammatical category may be less important than previously suggested. Iconicity is revealed as a feature of ultra-conserved words and potentially also as a property of vocabulary early in the history of language origins.

Words with Consistent Diachronic Usage Patterns are Learned Earlier: A Computational Analysis Using Temporally Aligned Word Embeddings

In this study, we use temporally aligned word embeddings and a large diachronic corpus of English to quantify language change in a data-driven, scalable way, which is grounded in language use. We show a unique and reliable relation between measures of language change and age of acquisition (AoA) while controlling for frequency, contextual diversity, concreteness, length, dominant part of speech, orthographic neighborhood density, and diachronic frequency variation. We analyze measures of language change tackling both the change in lexical representations and the change in the relation between lexical representations and the words with the most similar usage patterns, showing that they capture different aspects of language change. Our results show a unique relation between language change and AoA, which is stronger when considering neighborhood-level measures of language change: Words with more coherent diachronic usage patterns tend to be acquired earlier. The results support theories positing a link between ontogenetic and ethnogenetic processes in language.

The Macroscope: A tool for examining the historical structure of language

The recent rise in digitized historical text has made it possible to quantitatively study our psychological past. This involves understanding changes in what words meant, how words were used, and how these changes may have responded to changes in the environment, such as in healthcare, wealth disparity, and war. Here we make available a tool, the Macroscope, for studying historical changes in language over the last two centuries. The Macroscope uses over 155 billion words of historical text, which will grow as we include new historical corpora, and derives word properties from frequency-of-usage and co-occurrence patterns over time. Using co-occurrence patterns, the Macroscope can track changes in semantics, allowing researchers to identify semantically stable and unstable words in historical text and providing quantitative information about changes in a word’s valence, arousal, and concreteness, as well as information about new properties, such as semantic drift. The Macroscope provides information about both the local and global properties of words, as well as information about how these properties change over time, allowing researchers to visualize and download data in order to make inferences about historical psychology. Although quantitative historical psychology represents a largely new field of study, we see this work as complementing a wealth of other historical investigations, offering new insights and new approaches to understanding existing theory. The Macroscope is available online at http://www.macroscope.tech.

The causality of borrowing: Lexical loans in Eurasian languages

All languages borrow words from other languages. Some languages are more prone to borrowing, while others borrow less, and different domains of the vocabulary are unequally susceptible to borrowing. Languages typically borrow words when a new concept is introduced, but languages may also borrow a new word for an already existing concept. Linguists describe two causalities for borrowing: need, i.e., the internal pressure of borrowing a new term for a concept in the language, and prestige, i.e., the external pressure of borrowing a term from a more prestigious language. We investigate lexical loans in a dataset of 104 concepts in 115 Eurasian languages from 7 families occupying a coherent contact area of the Eurasian landmass, of which Indo-European languages from various periods constitute a majority. We use a cognacy-coded dataset, which identifies loan events including a source and a target language. To avoid loans for newly introduced concepts in languages, we use a list of lexical concepts that have been in use at least since the Chalcolithic (4000–3000 BCE). We observe that the rates of borrowing are highly variable among concepts, lexical domains, languages, language families, and time periods. We compare our results to those of a global sample and observe that our rates are generally lower, but that the rates between the samples are significantly correlated. To test the causality of borrowing, we use two different ranks. Firstly, to test need, we use a cultural ranking of concepts by their mobility (of nature items) or their labour intensity and “distance-from-hearth” (of culture items). Secondly, to test prestige, we use a power ranking of languages by their socio-cultural status. We conclude that the borrowability of concepts increases with increasing mobility (nature), and with increased labour intensity and “distance-from-hearth” (culture). We also conclude that language prestige is not correlated with borrowability in general (all languages borrow, independently of prestige), but prestige predicts the directionality of borrowing, from a more prestigious language to a less prestigious one. The process is not constant over time, with a larger inequality during the ancient and modern periods, but this result may depend on the status of the data (non-prestigious languages often remain unattested). In conclusion, we observe that need and prestige compete as causes of lexical borrowing.

Cognitive influences in language evolution: Psycholinguistic predictors of loan word borrowing

Languages change due to social, cultural, and cognitive influences. In this paper, we provide an assessment of these cognitive influences on diachronic change in the vocabulary. Previously, tests of stability and change of vocabulary items have been conducted on small sets of words where diachronic change is imputed from cladistics studies. Here, we show for a substantially larger set of words that stability and change in terms of documented borrowings of words into English and into Dutch can be predicted by psycholinguistic properties of words that reflect their representational fidelity. We found that grammatical category, word length, age of acquisition, and frequency predict borrowing rates, but frequency has a non-linear relationship. Frequency correlates negatively with probability of borrowing for high-frequency words, but positively for low-frequency words. This borrowing evidence documents recent, observable diachronic change in the vocabulary enabling us to distinguish between change associated with transmission during language acquisition and change due to innovations by proficient speakers.

Darwinian perspectives on the evolution of human languages

Human languages evolve by a process of descent with modification in which parent languages give rise to daughter languages over time and in a manner that mimics the evolution of biological species. Descent with modification is just one of many parallels between biological and linguistic evolution that, taken together, offer up a Darwinian perspective on how languages evolve. Combined with statistical methods borrowed from evolutionary biology, this Darwinian perspective has brought new opportunities to the study of the evolution of human languages. These include the statistical inference of phylogenetic trees of languages, the study of how linguistic traits evolve over thousands of years of language change, the reconstruction of ancestral or proto-languages, and using language change to date historical events.