RESEARCH IS A QUEST

reframing a project as a linguistic research program on Science Communication with the use of Data Science

Resumo

The effects of what science can do depend not just on the knowledge it produces, but on how this knowledge is communicated. For science communicators, one of the challenges is to compress multi-dimensional information into language that is accessible and meaningful to their target audiences. In order to explore ways to broaden the foundations of studies on Science Communication, we state that there is a methodological need to test hypothesis against data. By this approach, we mean to reframe a project in Cognitive Linguistics for teaching scientific writing through introspection as a program whose investigation is based on a massive systematic corpus of ecologically valid multimodal data, along with tools and practices to analyze this data. This Data Science approach is found in The Distributed Little Red Hen Lab, where we have developed the Basic Text Pipeline to investigate narrativity and figurativity in Science Communication from a corpus of 1,000 journal abstracts. The outcomes are to present theoretical contribution from Cognitive Linguistics to Science Communication, to model it from frame narratives and blending constructions and to develop tools for research purposes on this discipline as well as for teaching and learning scientific writing.