TACO: a Turkish database for Abstract COncepts

We created a Turkish database for Abstract COncepts (TACO). We collected ratings from 504 Turkish words, of which 79 were concrete, namely belonging to the categories of fruits, animals, and tools, and 425 abstract, including emotions, social, mental states, theoretical, quantity, space, and political concepts. The words were rated by 118 participants for 11 dimensions, including familiarity, imageability, Age of Acquisition, valence, arousal, quantity, space, theoretical, social, mental state and political. We conducted a PCA analysis, to see the latent factors for our dataset. Results showed good consistency with previous studies in other languages, as well as some relevant novelties. The mental state dimension was rated as the most dominant for the majority of concepts (32.94%) and all the dimensions showed moderate-to-low levels of exclusivity, indicating their multidimensional nature. Four latent factors emerged from PCA. Factor 1 (Magnitude with low introspection) captured the juxtaposition between magnitude and introspection polarities, with concepts highly grounded on this factor being judged as highly imageable and connected to a magnitude-related dimension, i.e. space and quantity, and, at the same time, being judged as hardly connected with mental state dimension. In Factor 2 (Theoretical factor), high values described concepts acquired later, of a theoretical nature, and characterized by low familiarity. Factor 3 (Social-Political factor) connected social and political dimensions. Lastly, valence and arousal dimensions were grouped together in Factor 4 (Affective factor), in which high scores accounted for concepts with low arousal and positive valence. To conclude, TACO offers the first extensive database for Turkish language.