The "Small World of Words" Free Association Norms for Rioplatense Spanish

Abstract

Large scale word association datasets are both important tools used in psycholinguistics and used as models that capture meaning when considered as semantic networks. Here we present word association norms for Rioplatense Spanish, a variant spoken in Argentina and Uruguay. The norms were derived through a large-scale crowd-sourced continued word association task in which participants give three associations to a list of cue words. Covering over 13,000 words and +3.6M responses, it is currently the most extensive dataset available for Spanish. We compare the obtained dataset with previous studies in Dutch and English to investigate the role of grammatical gender and studies that used Iberian Spanish to test generalizability to other Spanish variants. Finally, we evaluated the validity of our data in word processing (lexical decision reaction times) and semantic (similarity judgment) tasks. Our results demonstrate that network measures such as in-degree provide a good prediction of lexical decision response times. Analyzing semantic similarity judgments, showed that results replicate and extend previous findings demonstrating that semantic similarity derived using spreading activation or spectral methods outperform word embeddings trained on text corpora.

A Computational Approach to Identifying Cultural Keywords Across Languages

“…(2019) report a correlation of around 0.5 between corpus frequencies and association frequencies, suggesting that these two frequency measures are overlapping but distinct. A similar conclusion emerges from analyses showing that neither measure is redundant when the two are used to predict measures of lexical processing such as response times for lexical decision and naming tasks across all four languages (Cabana et al., 2022; De Deyne et al., 2013, 2019; Li et al., 2023). These results suggest that both corpus frequency and association frequency are worth considering as sources of information about cultural keywords.…”

“…Word association is a classic technique used to study semantic representation (De Deyne et al., 2013, 2019; Joyce, 2005; Jung, Li, & Akama, 2010; Moss, Older, & Older, 1996; Nelson, McEvoy, Walling, & Wheeler, 1980; Wilson & Kiss, 1988), and our approach builds on previous studies that have compared word association data across languages (Szalay & Maday, 1973; Szalay & Deese, 1978; Ufimtseva, 2014). Our analyses draw on data from the “Small World of Words” (SWOW), the largest word association study in the literature (Cabana et al., 2022; De Deyne et al., 2013, 2019; Li et al., 2023). 6 For each cue in this study, participants were provided three responses: for example, three possible responses to two are couple , three , and double .…”

“…The first is a subset of the WorldLex corpus (Gimenes & New, 2016) that includes frequencies based on tweets, blog posts, and news reports in 23 languages. The second source is word association data, and we will analyze response frequencies derived from association norms for four languages (Cabana, Zugarramurdi, Lisboa, & De Deyne, 2022;De Deyne, Navarro, & Storms, 2013;De Deyne, Navarro, Perfors, Brysbaert, & Storms, 2019;Li, Ding, De Deyne, & Cai, 2023). De Deyne et al ( 2019) report a correlation of around 0.5 between corpus frequencies and association frequencies, suggesting that these two frequency measures are overlapping but distinct.…”

Contrasting the semantic typology biases of Deaf and hearing nonsigners in their conceptualization of time and space

“…Future avenues of research include expanding the sample; comparing the Deaf sample with subsamples of the Rioplatense Spanish lexicon (Vivas J. et al, 2017;Cabana et al, 2020) and other spoken-sign languages pairs such as DGS-German, CSL-Mandarin, LSE-Spanish, or ASL-English; testing bimodal bilinguals would help to find whether they follow the pattern of Deaf signers, hearing nonsigners, both, or neither. Mainly, the cross-linguistic approach might help to clarify whether the patterns that we found here are due to modality effects or artifacts of the tested specific languages (LSU and Uruguayan Spanish).…”

A Computational Approach to Identifying Cultural Keywords across Languages

“…Word association is a classic technique used to study semantic representation, (Nelson, McEvoy, Walling, & Wheeler, 1980;Wilson & Kiss, 1988;Moss, Older, & Older, 1996;Joyce, 2005;Jung, Li, & Akama, 2010;De Deyne, Navarro, & Storms, 2013;De Deyne, Navarro, Perfors, Brysbaert, & Storms, 2019), and our approach builds on previous studies that have compared word association data across languages (Szalay & Maday, 1973;Szalay & Deese, 1978;Ufimtseva, 2014). Our analyses draw on data from the "Small World of Words" (SWOW), the largest word association study in the literature (Cabana, Zugarramurdi, Lisboa, & De Deyne, 2022;De Deyne et al, 2013, 2019. 5 For each cue in this study, participants were provided three responses: for example, three possible responses to two are couple, three and double.…”