Literary Studies, Cognitive Linguistics, Computational Linguistics
I am interested in studying the way our minds process language (especially literary), and in the ways in which these insights can be applied for improving our communicative practices. I obatined my first degree in Literature, Linguistics, and Philosophy at the University of Buenos Aires (2005-2010). I pursued a Master at the universities of Strasbourg, Bologna, and Thessaloniki (2011-2013). And I have recently finished my PhD at the Freie Universität Berlin (2014-2019), with a stay at the Stanford University, under the supervision of Prof. Joachim Küpper and Prof. Friedemann Pulvermüller. My doctoral research was devoted to the study of reader responses from the perspectives of cognitive and computational linguistics - I'm currently editing it for publication.
The same message can produce different responses in different readers. How does the reading mind work? And how can we read it? These questions constitute the subject of my research. One of the motivations in which it’s grounded is that, in the last decades, two disciplines have revolutionized the ways in which we study the human mind. On the one hand, cognitive science has shown that our subjective responses (such as the meanings we attribute to a text or our emotional reactions to it) can be experimentally measured. On the other, data science has shown that, by mining big data about human behavior, many of our subjective responses become predictable at massive scales. The intention of my research is to introduce and deepen the discoveries that these two disciplines have made regarding the ways in which humans produce and consume stories, poems, novels, but also slogans, jokes, news, debates, speeches, and any other linguistic stimulus that recruits our literary minds.
My dissertation has three parts. The first one explores some of the main cognitive biases that model our responses to words, phrasing, stories, and characters. It describes, for instance, which parts of our brain are responsible for creating meaning, what hormones and neurotransmitters are elicited in our bodies by different literary genre, and what evolutionary adaptations turned us into animals that tell fictional stories to each other. The second part considers the progress in data science, which has allowed for the development of so much linguistic technology capable of predicting reader responses with increasing accuracy – from the microtargeting techniques used in political campaigns and marketing, to the invention of automatic translators and virtual assistants. The third part is a case study, which consists in the prediction of reader responses to a popular poem, on the basis of an analysis of a large dataset of YouTube comments – later verified through a survey.
We use to say that “the beauty is in the eye of the beholder.” But now we can observe the brains of the beholders, and we count with an enormous amount of data about their behavior and environment. My research attempts to communicate the great potential of these two novelties, the perspective that natural sciences and computation give us about our cultural practices, and the synthesis between science and humanities that this perspective represents. The resulting book addressed to everyone who is interested in understanding how our literary minds work and in leveraging these insights so as to make our communication more efficient.