Due to the limitations of such a project, we intend to focus our attention on two specific aspects related to terminological change: the linguistic mechanism of lexicalization and the sociolinguistic structure of the present-day speaker communities of specialized sectors, which are complex. In the previous project, TERMMED. Evolution of scientific knowledge in medicine: lexical and semantic change (FFI2017-88100-P) 2018-2020, whose principal investigators were Rosa Estopà and Mercè Lorente, the hypotheses on terminological change were applied to the analysis of a Spanish corpus on assisted reproduction within medicine, which was fragmented into 7-year periods. The scenarios of change analyzed were: the neology of syntagmatic structure and its evolution; acronyms; the disappearance of terms; morphological mechanisms and relevant syntagmatic patterns; and the stabilization of terms through their incorporation in dictionaries. In this new project we want to focus on other areas of specialization, Computer Science and Economics, in order to be able to generalize some of the trends detected in the previous project. On the other hand, having already tested the research methodology, we propose more ambitious objectives from the applied perspective (two languages and two fields) and the theoretical one (to deepen the concept of lexicalization in linguistic change and in that of speaker communities adapted to specialized communicative contexts). 

The general objectives of the EVOTERM project are the following: 

1. To establish theoretical and methodological bases for the study of the evolution of the specialized lexicon or terminology, within the framework of linguistic change. 
2. To analyze the variation and processes of morphological, syntactic, semantic and pragmatic change related to the concept of lexicalization, from real data extracted from textual corpora from the fields of Economics and Computer Science in Spanish and Catalan. 
3. To characterize the communities of speakers in these specialized sectors (Economics and Computer Science), which have evolved from homogeneous communities of experts to complex communities with agents with different training profiles, different application profiles, different communicative purposes and different reference models.

Research Team

• Mercè Lorente Casafont (IP)
• Teresa Cabré Castellví
• Janet De Cesaris

Work Team

• Anna Joan Casademont
• M. Àngels Martínez Salom
• Albert Morales Moreno
• Juan Manuel Torres Moreno
• Jorge Vivaldi Palatresi
• Yingfeng Xu

Collaborating PhD Scholars

• Mariona Arnau Garcia
• Chenlu Lu
• Huimin Sun
• Sangzhu Zhaxi

General documentation

• Scientific-technical report of the project