The choice associated with words is a fundamental property of natural languages. It lies at the heart of quantitative linguistics, computational linguistics and language sciences more generally. Information theory gives us tools at hand to measure precisely the average amount of choice associated with words: the word entropy. Here, we use three parallel corpora, encompassing ca. 450 million words in 1916 texts and 1259 languages, to tackle some of the major conceptual and practical problems of word entropy estimation: dependence on text size, register, style and estimation method, as well as non-independence of words in co-text. We present two main findings: Firstly, word entropies display relatively narrow, unimodal distributions. There is no language in our sample with a unigram entropy of less than six bits/word. We argue that this is in line with information-theoretic models of communication. Languages are held in a narrow range by two fundamental pressures: word learnability and word expressivity, with a potential bias towards expressivity. Secondly, there is a strong linear relationship between unigram entropies and entropy rates. The entropy difference between words with and without co-textual information is narrowly distributed around ca. three bits/word. In other words, knowing the preceding text reduces the uncertainty of words by roughly the same amount across languages of the world.

This paper discusses a multidimensional probabilistic semantic map of lexical motion verb stems based on data collected from parallel texts (viz. translations of the Gospel according to Mark) for 100 languages from all continents. The crosslinguistic diversity of lexical semantics in motion verbs is illustrated in detail for the domain of ‘go’, ‘come’, and ‘arrive’ type contexts. It is argued that the theoretical bases underlying probabilistic semantic maps from exemplar data are the isomorphism hypothesis (given any two meanings and their corresponding forms in any particular language, more similar meanings are more likely to be expressed by the same form in any language), similarity semantics (similarity is more basic than identity), and exemplar semantics (exemplar meaning is more fundamental than abstract concepts).

This chapter argues that an evolutionary cultural approach to language not only has already proven fruitful, but it probably holds the key to understand many puzzling aspects of language, its change and origins. The chapter begins by highlighting several still common misconceptions about language that might seem to call into question a cultural evolutionary approach. It explores the antiquity of language and sketches a general evolutionary approach discussing the aspects of function, fitness, replication, and selection, as well the relevant units of linguistic evolution. In this context, the chapter looks at some fundamental aspects of linguistic diversity such as the nature of the design space, the mechanisms generating it, and the shape and fabric of language. Given that biology is another evolutionary system, its complex coevolution with language needs to be understood in order to have a proper theory of language. Throughout the chapter, various challenges are identified and discussed, sketching promising directions for future research. The chapter ends by listing the necessary data, methods, and theoretical developments required for a grounded evolutionary approach to language.

Understanding the patterns and causes of differential structural stability is an area of major interest for the study of language change and evolution. It is still debated whether structural features have intrinsic stabilities across language families and geographic areas, or if the processes governing their rate of change are completely dependent upon the specific context of a given language or language family. We conducted an extensive literature review and selected seven different approaches to conceptualising and estimating the stability of structural linguistic features, aiming at comparing them using the same dataset, the World Atlas of Language Structures. We found that, despite profound conceptual and empirical differences between these methods, they tend to agree in classifying some structural linguistic features as being more stable than others. This suggests that there are intrinsic properties of such structural features influencing their stability across methods, language families and geographic areas. This finding is a major step towards understanding the nature of structural linguistic features and their interaction with idiosyncratic, lineage- and area-specific factors during language change and evolution.

There are many parallels between historical linguistics and molecular phylogenetics. In this paper we describe an algorithmic pipeline that mimics, as closely as possible, the traditional workflow of language reconstruction known as the comparative method. The pipeline consists of suitably modified algorithms based on recent research in bioinformatics, which are adapted to the specifics of linguistic data. This approach can alleviate much of the laborious research needed to establish proof of historical relationships between languages. Equally important to our proposal is that each step in the workflow of the comparative method is implemented independently, so language specialists have the possibility to scrutinize intermediate results. We have used our pipeline to investigate two groups of languages, the Tsezic languages of the Caucasus and the Mataco-Guaicuruan languages of South America, based on the lexical data from the Intercontinental Dictionary Series (IDS). The results of these tests show that the current approach is a viable and useful extension to historical linguistic research.