English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The representation of abstract concepts remains a challenge, justifying the need for further experimental investigation. To that end, we introduce a normative database for 630 semantically similar French word pairs and associated levels of abstractness for 1260 isolated words based on data from 900 subjects. The semantic similarity and abstractness norms were obtained in two studies using 7-point scales. The database is organised according to word-pair semantic similarity, abstractness, and associated lexical variables such as word length (in number of letters), word frequency, and other lexical variables to allow for matching of experimental material. The associated variables were obtained by cross-referencing our database with other known psycholinguistic databases including Lexique (New et al., 2004), the French Lexicon Project (Ferrand et al., 2010), Wordlex (Gimenes &amp; New, 2016), and MEGALEX (Ferrand et al., 2018). We introduced sufficient diversity to allow researchers to select pairs with varying levels of semantic similarity and abstractness. In addition, it is possible to use these data as continuous or discrete variables. The full data are available in the supplementary materials as well as on OSF ( https://osf.io/qsd4v/ ).

Semantic similarity and associated abstractness norms for 630 French word pairs