DReaM
Affective and lexico-semantic analysis of metaphors in Croatian: Digital repository and electrophysiological validation
Affective and lexico-semantic analysis of metaphors in Croatian: Digital repository and electrophysiological validation
The main aim of the project is to compile a publicly accessible and searchable Repository of Affective and Lexico-semantic Norms for Croatian Metaphors (DigiMet). The secondary goal of the project is to conduct an electrophysiological study of figurative multi-word expression (MWE) processing in bilingual speakers using metaphors based on collected norms. The digital repository will contain norms for Croatian metaphors and their English equivalents: 1. valence, 2. arousal, 3. concreteness, 4. imageability, 5. metaphoricity, and 6. familiarity, that will be collected via SurveyMonkey on a sample of 500 participants. Lexical data on target words in metaphorical MWE (e.g. frequency, number of syllables, letters) will also be collected through corpus analysis. Computational linguistic technologies (available corpora and databases of English and Croatian metaphors and MWE) will be used to collect metaphors and lexical-semantic data. In order to conduct the experiment, stimuli for evoked potential (ERP) testing will be selected using the DigiMet repository of metaphors. The ERP study will serve to investigate how metaphors influence MWE processing from L2 in sentence context compared to literal sentences in bilingual speakers. The DigiMet repository and ERP data will contribute to the understanding of figurative MWE processing in a bilingual context. Furthermore, neurocognitive language studies are significantly less represented in Croatian than in English, highlighting the need for its implementation and the development of the necessary open-access tools. Considering the significant influence of emotional valence on memory, learning and perception, the project results have broad applications in education, interdisciplinary research on cognitive language processing and the development of large language models (AI).
Jasmina Jelčić Čolakovac, University of Rijeka, Faculty of Maritime Studies, Croatia (Head)
Irena Bogunović, University of Rijeka, Faculty of Maritime Studies, Croatia
Mirjana Borucinsky, University of Rijeka, Faculty of Maritime Studies, Croatia
Jana Kegalj, University of Rijeka, Faculty of Maritime Studies, Croatia
Sandra Tominac Coslovich, University of Rijeka, Faculty of Maritime Studies, Croatia
Ivan Panić, University of Rijeka, Faculty of Maritime Studies, Croatia
Marko Vukšić, University of Rijeka, Faculty of Maritime Studies, Croatia
Marcin Naranowicz, Adam Mickiewicz University in Poznań, Faculty of English, Poland
Katarzyna Jankowiak, Adam Mickiewicz University in Poznań, Faculty of English, Poland
Bojana Ćoso, ISPP, Cambodia
Call for funding of Institutional research projects of the University of Rijeka financed from source 581 – Recovery and Resilience Mechanism (University of Rijeka, Institutional Research Projects)