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 and listen to recent media coverage of our research:
- The Conversation Weekly, February 2022 – Listen to an interview about a recent paper on how ow people might discriminate against non-native speakers even if they are not prejudiced(starts at 31:41)
- Aussie English, January 2022 – Listen to an interview with the PI about her research
- The Conversation, December 3, 2021 – on how people might discriminate against non-native speakers even if they are not prejudiced
- 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:
- Lev-Ari, S. (2022) Community size influences word order. In Ravignani et al. (Eds.) The Evolution of Language. Proceedings of the Joint Conference on Language Evolution (JCoLE), pp. 458-460.
TLDR The paper shows experimentally that languages spoken by larger communities are more likely to rely on cross-linguistically common patterns, especially those that are driven by communicative needs. Specifically, larger groups were more likely to rely on SVO word order in the new communication system they developed.
- Lev-Ari, S. (2022) People with larger social networks show poorer voice recognition. Quarterly Journal of Experimental Psychology, 75, 3, 450-460.
TLDR People with larger social networks show poorer voice recognition, potentially because they attend less to speaker-specific information.
- 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.
05/09/2022: Joined Conference on Language Evolution