Our research approaches language from a social networks perspective. We show how individuals’ social network structure influences how good individuals are at understanding others and at expressing themselves. We also examine whether one of the reasons that languages differ from each other is because they are spoken by communities with differnet social structures. We examine these questions using a combination of individual differences, experimental, and computational methods, and across different linguistic levels.


Check out our latest papers:

TLDR Languages differ in how they categorize the world. The paper shows that larger communities create more expressive categories that allow them to communicate more successfully. It shows this via agent-based simulations over different types of meaning spaces.

TLDR The paper shows experimentally that languages spoken by more speakers are more likely to rely on SVO order, probably because it facilitates communication and communicative challenges are harder in larger communities.

TLDR One of the defining properties of langauge is the arbitrary relation between the forms of words and their meaning. This is often illustrated with the example that ‘whale’ is a short word for a very large entity whereas ‘microorganism’ is a very long word for a very small entity. That is, the form of the word does not seem to reflect its meaning. This paper shows that this example in fact aligns with a cross-linguistic sound symbolic (i.e., non-arbitrary) pattern, and that languages tend to use longer words to denote small size than large size.

TLDR The paper shows that there are cross-linguistic regularities in the sounds of swear words, and approximants (sounds like l,w,r,y) are particularly unsuitable for swearing. (1) An examination of swear words across unrelated languages suggests that approximants are particularly absent in swear words (2) When speakers of different languages need to guess which of two pseudo-words is a swear word, they systematically choose the word without approximants, and (3) English speakers sanitize swear words by introducing approximants into them (e.g., darn instead of damn).

Read and listen to recent media coverage of our research:

Upcoming presentations:

16-18/5/2024: 37th Annual Conference on Human Sentence Processing (Ann Arbor, Michigan, USA)