Our research approaches language from a social networks perspective. We show how network structure can influence how good individuals are at understanding others and expressing themselves, why languages spoken by different communities differ from each other, and how individuals’ language use influences the language of the community. We examine these questions using a combination of individual differences, experimental, and computational methods and across different linguistic levels.
The lab is recruiting a PhD student. If you are interested, email shiri.lev-ari AT rhul.ac.uk ASAP.
Read recent news articles about our research:
- The Economist, August 8, 2019 – on how larger communities create less complex languages
- The Times, July 19, 2019 – on how larger communities create less complex languages
- Society for Human Resources Management, August 6, 2019 – on how things sound less credible when said with a foreign accent
Check out our latest papers:
- Boduch-Grabka, K. & Lev-Ari, S. (2021) Exposing individuals to foreign accent increases their trust in what non-native speakers say. Cognitive Science, 45, 11, e13064
TLDR People believe information less when it is delivered in a foreign accent even if they are not prejudiced. They doubt it because it is harder to process foreign-accented speech and people implicitly infer form the difficulty that the information is wrong. This bias against believing non-native speakers, however, can be reduced by exposing listeners to foreign-accented speech, because exposure trains listeners to become better at processing foreign-accented speech.
- Lev-Ari, S., Kancheva, I., Marston, L., Morris, H. & Zaynudinova, M. (2021) ‘Big’ sounds bigger in more widely-spoken languages. Cognitive Science, 45, 11, e13059.
TLDR Languages that are spoken by larger communities (i.e., millions of speakers) are more sound symbolic than languages spoken by smaller communities (e.g., thousands of speakers). We demonstrate it by showing that people are better at guessing the meaning of words in unfamiliar languages if those languages are spoken by large rather than smaller communities. The reason for that is that communication is harder in larger communities, so the languages of large communities adapt and overcome the greater challenges by relying on sound symbolism, that is, having words that sound like what they mean.
- Lev-Ari, S. (in press) People with larger social networks show poorer voice recognition. Quarterly Journal of Experimental Psychology.
TLDR People with larger social networks show poorer voice recognition, potentially because they attend less to speaker-specific information.
- Lev-Ari, S., Haidari, B., Sayer, T., Au, V. & Nazihah, F. (2021) Noticing how our social networks are interconnected can influence language change Language, Cognition & Neuroscience, 36, 1, 119-134.
TLDR Real world social networks are interconnected, so information we receive from several people might originate from the same person. We show that people tend to neglect to consider this interconnectivity when learning information, and even more so when the information is linguistic (how to call something) compared to opinions. We also show that this neglect facilitates the spread of language and trends.
27/07/2021: CogSci 2021