Is grammatical complexity shaped by sociodemographic and sociolinguistic factors? The previously accepted "linguistic niche hypothesis" claims that with an increased number of nonnative speakers in a social group (high exotericity), grammatic complexity decreases; on the other hand, grammatical complexity increases amongst isolated linguistic communities (low exotericity). Through the use of spatiophylogenetic modelling of 1314 languages, the authors of this study do not find adequate evidence to support the linguistic niche hypothesis. Instead, they suggest that linguistic complexity is better predicted by phylogeny and geographic contiguity.

This article explores the relationship between language structure and social environment, positing that linguistic factors such as morphological complexity are associated with demographic/socio-historical factors such as number of speakers, geographic spread, and degree of language contact. Data support such an association. The authors further propose a Linguistic Niche Hypothesis suggesting that “the level of morphological specialization is a product of languages adapting to the learning constraints and the unique communicative needs of the speaker population” (7).

The authors statistically test existing theories and proposals regarding the existence and nature of the creole language profile. Results indicate that consistencies and variation between creole languages, as with non-creole languages, is a result of genealogical and contact processes. However, creole languages are unique from non-creole languages in that they have more than one language in their ancestry. Findings "call into question the existence of a pidgin stage in creole development and of creole-specific innovations." Support is found for the idea that language learning and transmission are strikingly resilient processes.

In order to investigate cross-cultural variation in systems of conversational turn-taking (who speaks and when), the researchers analyze the association of various contextual, verbal, and non-verbal factors with mean response time. Despite some variation in response time between languages, each of the explanatory variables is found to have significant impact on response time independent of language. A further test on subjective perception of ideal response time suggests that although similar factors act on response patterns cross-culturally (in support of a 'universal systems' theory), speakers are hypersensitive to even minor cultural variations in response time.

How is the evolution of language shaped by speaker population size? Through comparative data analyses of 153 language pairs from the Austronesian, Indo-European, and Niger-Congo language families, the authors find that the influence of population size on language evolution is not the same in the three language families. Only in Indo-European languages did a smaller population size of language-speakers significantly predict more word loss.

Researchers looked at the meaning of various emotion concepts, 'emotion semantics' in an attempt to determine the patterns and processes behind meaning cross-culturally. They used maps of colexification patterns (where semantically related concepts are named with the same word), adjusted Rand indices (ARIs) which indicated the similarities of two community's network structures, and various psychophysiological dimensions to test relationships and patterns of variability /structure in emotion semantics. These methods shed light on the underlying mechanisms behind emotions, both their words and their meanings in languages across the world. Their findings show substantial difference in language families and relationships between geographic proximity of language families and subsequent variation in emotion colexification tied to an evolutionary relationship, while also finding cultural universals in emotion colexification networks with languages primarily differentiating emotions on the basis of valence and activation.

The authors compare language phylogenies and spatial distributions with folktale frequencies of Indo-European peoples in order to reconstruct their cultural transmission. A stronger association is found between folktale frequency and language phylogeny than has been proposed in earlier literature studies, indicating that vertical transmission is more influential on folktale distribution than horizontal transmission through spatial proximity. Finally, the frequencies of certain folktales appear to trace the ancestral divergences of Indo-European languages to a much deeper level than previously though, suggesting that folktales are representative of broader features of culture, rather than recent literary inventions.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.

The "equi-complexity hypothesis" suggests that there is an equal complexity across languages, meaning that there are constant trade-offs between different domains. Using phylogenetic modelling in a sample of 244 languages, this study follows a diachronic perspective to explore if there is an inversed coevolution within the grammatical coding of nominal and verbal domains. The results show that while there appears to be a coevolutionary relationship between some features of these two domains, there is no evidence to support the idea that all languages maintain an overall equilibrium of grammatical complexity. Rather, the correlation nominal and verbal domains vary between lineages. Austronesian languages do not show a coevolution between the domains. Sino-Tibetan languages seem to have a positive correlation while Indo-European languages appear to have a negative correlation, meaning that this inverse coevolution can be lineage specific.

Languages and weaving methods are passed down generation to generation, allowing both of them to have relatively clear phylogenies. These researchers use a Bayesian approach with Markov chain Monte Carlo methods to uncover similar but independent phylogenies for Kra-Dai languages and weaving technologies. Evolutionary differences between the two are most likely due to different rates of change: smooth change (language) and periods of burst and stasis (weaving). This study found that language phylogenies were not efficient at predicting phylogenies of technologies.