- Lev-Ari, S. & McKay, R. (under review) The Sound of Swearing: Evidence for Universal Patterns in Profanity
- Lev-Ari, S. (under review) Larger communities create more granular and better
- 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, e13064TLDRPeople 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.TLDRLanguages 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.TLDRPeople with larger social networks show poorer voice recognition, potentially because they attend less to speaker-specific information.
- Lev-Ari (2021) Richer color vocabulary is correlated with color memory, but its relation to perception is unknown Proceedings of the National Academy of Science, 118, 10, e2024682118. TLDRA commentary on Hasantash and Afraz (2020) explaining that their experiment cannot determine whether language can influence perception because of ceiling performance. It also explains that the correlation between color memory and color vocabulary does not show an influence of langauge on memory as it is likely that the causality is in the opposite direction – better color memory leads to using more color labels.
- 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. TLDRReal 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.
- Raviv, L., Meyer, A.S. & Lev-Ari, S. (2020) The role of social network
structure in the emergence of linguistic structure Cognitive Science, 44, 8, e12876. TLDRWe 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.
- Lev-Ari, S. & Sebanz, N. (2020) Interacting with multiple partners improves communication skills Cognitive Science, 44, 4, e12836.TLDRWe 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.
- Iacozza, S. , Meyer, A.S. & Lev-Ari, S. (2020) How in-group bias influences the level of detail of speaker-specific information encoded in novel lexical representations Journal of Experimental Psychology: Learning, Memory, and Cognition 46, 5, 894–906.TLDRWe 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.
- Raviv, L., Meyer, A.S., & Lev-Ari, S. (2020) Network structure and the cultural evolution of linguistic structure: A group communication experiment. 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.
- Lev-Ari, S., Dodsworth, R., Mielke, J. & Peperkamp, S. (2019) The different roles
of expectations in phonetic and lexical processing. In Proceedings of the 20th Annual Conference of the international Speech Communication Association (INTERSPEECH)TLDRPrevious research investigates how the expectations listeners have of speakers influence language processing using either a lexical or a phonetic task, and the two are treated as interchangeable. We show that the two are not equivalent and have different underlying mechanisms that are sensitive to different individual differences. Performance on the phonetic task was sensitive to working memory whereas performance on the lexical task was sensitive to implicit bias.
- Iacozza, S. , Meyer, A.S. & Lev-Ari, S. (2019) How in-group bias source memory for words learned from in-group and out-group speakers Frontiers in Human Neuroscience 13:308 TLDRWe teach participants novel words from speakers from their own university (in-group) and another university (out-group). We show that people spontaneously encode speakers’ in/out-group status, and that the greater participants’ (implicit) in-group bias, the more hesitant they are about attributing learned words to speakers, especially in-group speakers.
- Raviv, L., Meyer, A.S., & Lev-Ari, S. (2019) Larger communities create more systematic languages. Proceedings of The Royal Society B 286, 201912 TLDRBy having small and large groups play a communication game in the lab using only words that they invent we find that larger communities create more structured languages, suggesting that cross-linguistic differences in grammatical and morphological complexity could be (partially) accounted for by community size. We also find that this effect is driven by the greater input variability.
- Raviv, L., Meyer, A.S., & Lev-Ari, S. (2019) Compositional structure can emerge without generational transmission. Cognition, 182, 151-164. TLDRAn experimental study showing that structure can emerge within a language during the first generation of users, and that one of the main pressures for its emergence is having multiple interaction partners.
- Lev-Ari, S. (2019) People with larger social networks are better at predicting what someone will say but not how they will say it. Language, Cognition, and Neuroscience, 34,1, 101-114. doi:10.1080/23273798.2018.1508733 TLDRPeople with larger social networks are better than those with smaller social networks at predicting the meaning that someone will express (e.g., car or bicycle) but not the form they would use (e.g., bicycle or bike).
- Monster, I. & Lev-Ari, S. (2018) The effect of social network size on hashtag adoption on Twitter. Cognitive Science, 42, 3149–3158. doi:10.1111/cogs.12675. TLDRTwitter users who follow fewer others are more likely to adopt each hashtag they see.
- Lev-Ari, S. (2018) Social network size can influence linguistic malleability and the propagation of linguistic change. Cognition 176, 31-39. doi:10.1016/j.cognition.2018.03.003. TLDRPeople with smaller social networks are more easily influenced by others and could be important for spreading linguistic trends.
- Lev-Ari, S., Ho, E., & Keysar, B. (2018) The unforeseen consequences of interacting with non-native speakers. Topics in Cognitive Science, 10, 835-849. doi:10.1111/tops.12325. TLDRBecause people process information in less detail when they interact with non-native speakers, they remember less well what they themselves said in those interactions.
- Lev-Ari, S. (2018) The influence of social network size on speech perception. Quarterly Journal of Experimental Psychology, 71, 10, 2249-2260. doi:10.1177/1747021817739865 TLDRPeople who regularly interact with more people are better at speech perception and this is driven by the greater variability in the speech input they receive.
- Raviv, L., Meyer, A., & Lev-Ari, S. (2018). The role of community size in the emergence of linguistic structure. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), The Evolution of Language: Proceedings of the 12th International Conference (EVOLANGXII). Toruń, Poland: NCU Press, pp. 402-404. doi:10.12775/3991-1.096
- Lev-Ari, S. (2017). Talking to fewer people leads to having more malleable linguistic representations. PLoS One, 12(8): e0183593. doi:10.1371/journal.pone.0183593. TLDRPeople who regularly interact with fewer others have more malleable phonological representations, such that they are more easily influenced by the speech of each speaker they encounter.
- Lev-Ari, S., & Peperkamp, S. (2017). Language for $200: Success in the environment influences grammatical alignment. Journal of Language Evolution,2(2), 177-187. doi:10.1093/jole/lzw012. TLDRThe less successful people are (in a non-linguistic domain), the more they attend to and learn from the environment, including the grammatical patterns in it. We show this using a corpus analysis of the gameshow Jeopardy and a Go Fish experiment in the lab. The results suggest that the spread of linguistic changes might accelerate in times of crisis.
- Lev-Ari, S., & Shao, Z. (2017). How social network heterogeneity facilitates lexical access and lexical prediction. Memory & Cognition, 45(3), 528-538. doi:10.3758/s13421-016-0675-y. TLDRIndividuals with social networks that are more varied age-wise show better lexical prediction and are faster to name difficult-to-name items. This might be because they have less entropy in the input they receive from their environment.
- Lev-Ari, S., van Heugten, M., & Peperkamp, S. (2017). Relative difficulty of understanding foreign accents as a marker of proficiency. Cognitive Science,41(4), 1106-1118. doi:10.1111/cogs.12394. TLDRThe study shows that as the linguistic competence of L2 learners increases, so does their relative difficulty of understanding foreign-accented speech. In other words, finding foreign-accented speech relatively difficult to understand is a marker of acquiring more accurate phonological representations.
- Lev-Ari, S. (2016). How the size of our social network influences our semantic skills. Cognitive Science, 40, 2050-2064. doi:10.1111/cogs.12317. TLDRPeople with larger social networks are better at understanding evaluative language, such as restaurant or product reviews. The paper provides joint evidence from an individual difference study and an experiment where social network size was experimentally manipulated.
- Lev-Ari, S. (2016). Selective grammatical convergence: Learning from desirable speakers. Discourse Processes, 53(8), 657-674. doi:10.1080/0163853X.2015.1094716. TLDRSocial factors such as speakers’ social standing and how much they are liked influence whether listeners adopt their grammatical patterns. The experiments test influence on generalized learning, that is, not convergence during interaction but behavior afterwards.
- Lev-Ari, S. (2016). Studying individual differences in the social environment to better understand language learning and processing. Linguistics Vanguard,2(s1), 13-22. doi:10.1515/lingvan-2016-0015. TLDRAn opinion/review paper that argues that individual differences in the social environment influence linguistic skills and performance even in adult native speakers. Specifically, it reviews evidence that shows that differences in input can affect performance by (1) influencing people’s knowledgebase, (2) by modulating their processing manner, and (3) by shaping expectations.
- Lev-Ari, S., & Peperkamp, S. (2016). How the demographic make-up of our community influences speech perception. The Journal of the Acoustical Society of America, 139(6), 3076-3087. doi:10.1121/1.4950811. TLDRBy recruiting participants from across the US and matching their location to census data, the paper shows that the demographic make-up of the community influences people’s expectations about what foreign languages sounds like, and how they consequently perceive the speech.
- Lev-Ari, S. (2015). Adjusting the manner of language processing to the social context: Attention allocation during interactions with non-native speakers. In R. K. Mishra, N. Srinivasan, & F. Huettig (Eds.), Attention and Vision in Language Processing (pp. 185-195). New York: Springer. doi:10.1007/978-81-322-2443-3_11.
- Lev-Ari, S. (2015). Comprehending non-native speakers: Theory and evidence for adjustment in manner of processing. Frontiers in Psychology, 5: 1546. doi:10.3389/fpsyg.2014.01546.TLDRPeople expect non-native speakers to have lower linguistic competence. This leads them to process their speech differently. In particular, people increase their reliance on predictive processes and process the speech in less-detail
- Lev-Ari, S., & Keysar, B. (2014). Executive control influences linguistic representations. Memory & Cognition, 42(2), 247-263. doi:10.3758/s13421-013-0352-3.TLDRThe paper shows that the poorer individuals’ executive control, the more they would perceive the meanings of homonyms to be more similar to each other and those of polysemous words to be less similar to each other. This is because over the life-time, executive function influences how successfully competitors are inhibited and how well reinforcing terms are activated. Similarly, we show that bilinguals with better executive control think more differently in their two languages because they are better able to suppress the one not in use.
- Lev-Ari, S., & Peperkamp, S. (2014). An experimental study of the role of social factors in sound change. Laboratory Phonology, 5(3), 379-401. doi:10.1515/lp-2014-0013.TDLRWe show experimentally that when borrowing a word from a different language, speakers would maintain the foreign sounds in their pronunciaiton if the donor language is prestigious in the domain but will adapt it to the sounds of their own language if the donor language is not prestigious in the domain. We also show that speakers adapt to others’ use and that way create a community norm
- Lev-Ari, S., & Peperkamp, S. (2014). Do people converge to the linguistic patterns of non-reliable speakers? Perceptual learning from non-native speakers. In S. Fuchs, M. Grice, A. Hermes, L. Lancia, & D. Mücke (Eds.), Proceedings of the 10th International Seminar on Speech Production (ISSP)(pp. 261-264).
- Lev-Ari, S., & Peperkamp, S. (2014). The influence of inhibitory skill on phonological representations in production and perception. Journal of Phonetics, 47, 36-46. doi:10.1016/j.wocn.2014.09.001.
- Lev-Ari, S., San Giacomo, M., & Peperkamp, S. (2014). The effect of domain prestige and interlocutors’ bilingualism on sound adaptation. Journal of Sociolinguistics, 18(5), 658-684. doi:10.1111/josl.12102.
- Lev-Ari, S., & Peperkamp, S. (2013). Low inhibitory skill leads to non-native perception and production in bilinguals’ native language. Journal of Phonetics,41(5), 320-331. doi:10.1016/j.wocn.2013.06.002.
- Lev-Ari, S., & Keysar, B. (2012). Less detailed representation of non-native language: Why non-native speakers’ stories seem more vague. Discourse Processes, 49(7), 523-538. doi:10.1080/0163853X.2012.698493.
- Chang, V., Arora, V., Lev-Ari, S., D’Arcy, M., & Keysar, B. (2010). Interns overestimate the effectiveness of their hand-off communication. Pediatrics,125(3), 491-496. doi:10.1542/peds.2009-0351.
- Lev-Ari, S., & Keysar, B. (2010). Why don’t we believe non-native speakers? The influence of accent on credibility. Journal of Experimental Social Psychology, 46(6), 1093-1096. doi:10.1016/j.jesp.2010.05.025.
- Taylor, L. J., Lev-Ari, S., & Zwaan, R. A. (2008). Inferences about action engage action systems. Brain and Language, 107(1), 62-67. doi:10.1016/j.bandl.2007.08.004.