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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.

PhD studenthip

The lab is recruiting a PhD student. If you are interested, email shiri.lev-ari AT rhul.ac.uk ASAP.

LATEST NEWS

Read recent news articles about our research:

Check out our latest papers:

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.

TLDR We compared the emergence of linguistic structure in fully connected, small‐world, and scale‐free communities. We did not find an effecet of community structure on any of our measures (systematicity, stability, convergence, and communicative success), but small world communities consistently showed greater variation in their behavior and scale-free networks showed the least variation in their performace. These results suggest that network structure might influence vulnerability to drift.

TLDR:We show that talking to more people improves communication skills even when those we talk to are passive listeners who don’t talk back. We further show that this might be because talking to multiple people increases the tendency to take perspective.

TLDR: We process  and represent the speech of ingorup and outgroup members differently. The greater individuals’ implicit ingroup bias, the more they store speech from ingroup speakers in more detail than speech from outgroup speakers. We show this by looking at participants’ source memory for novel words they learn from (speakers presented as) ingroup and outgroup members.

  • Lev-Ari, S. (2020) Communities of different size create different categorization systems. In Ravignani, A. and Barbieri, C. and Martins, M. and Flaherty, M. and Jadoul, Y. and Lattenkamp, E. and Little, H. and Mudd, K. and Verhoef, T. (Eds.) The Evolution of Language: Proceedings of the 13th International Conference (EvoLang13), Brussels, Belgium.
  • Lev-Ari, S. (2020). The influence of social network properties on language processing and use. In M. S. Vitevitch (Ed.), Network Science in Cognitive Psychology. New York, NY: Routledge.

Upcoming presentations:

Zoom times!
30/10/2020: Northwestern University, Linguistics colloquium
18/11/2020: UCL, Psychology colloquium