Silvia Casola

Ritratto Silvia Casola

Computer Science and Innovation for Societal Challenges, XXXV series
Grant sponsor

Fondazione Bruno Kessler

Alberto Lavelli

Sabrina Cipolletta

Project description
Natural Language Processing (NLP) studies the ambiguous and evolving human language from a computational point of view: its applications include information extraction from text, automatic question answering, sentiment analysis, conversational agents and many others. In the Big Data era, a huge amount of digital textual data is produced daily. Using Natural Language Processing, we are now able to exploit such data to obtain information and perform predictions, achieving results that were unimaginable a few years ago. Machine learning and deep learning techniques play a key role in this process. Natural Language Processing is particularly useful in domains where several diverse sources of textual data exist, while structured data is difficult to obtain. One such domain is the technological domain, where information from patents and the scientific literature can be integrated with technical and non-technical newspapers and their readers’ comments, social networks, forum threads, blogs, etc. The goal is to understand how technology is evolving and perform foresight. Given the speed of the technology evolution, in fact, it is difficult to understand the technological landscape using traditional data sources only. Moreover, it is important to understand how technologies and devices are perceived by their users and potential users. My project aims at using Natural Language Processing for technology foresight, paying close attention to domains where technology has an impact on users’ everyday life (think, for example, at chronic patients using medical devices for self-care). We intend to map these technologies, finding their relations and predict future trends. Moreover, we want to study how the user’s perception affects technological evolution.