“Characterising Research Areas in the field of AI” is a research paper submitted to the special track “Statistical Methods for Science Mapping” on “51st Scientific Meeting of the Italian Statistical Society”. Alessandra Belfiore1, Angelo Salatino2, Francesco Osborne2 1 Università della Campania Luigi Vanvitelli, Caserta (Italy) 2 Knowledge Media Institute, The Open University, Milton Keynes (UK) Abstract […]
“Detection, Analysis, and Prediction of Research Topics with Scientific Knowledge Graphs” is a book chapter of “Predicting the Dynamics of Research Impact” edited by Springer. Angelo A. Salatino1, Andrea Mannocci2, and Francesco Osborne1 1Knowledge Media Institute – The Open University, Milton Keynes, United Kingdom 2Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo”, Italian National Research […]
Being able to rapidly recognise new research trends is strategic for many stakeholders, including universities, institutional funding bodies, academic publishers and companies. The literature presents several approaches to identifying the emergence of new research topics, which rely on the assumption that the topic is already exhibiting a certain degree of popularity and consistently referred to by a community of researchers. However, detecting the emergence of a new research area at an embryonic stage, i.e., before the topic has been consistently labelled by a community of researchers and associated with a number of publications, is still an open challenge.
“Early Detection and Forecasting of Research Trends” is a paper presented at the Doctoral Consortium of the 14th International Semantic Web Conference (ISWC2015) in Bethlehem (PA, USA). Abstract Identifying and forecasting research trends is of critical importance for a variety of stakeholders, including researchers, academic publishers, institutional funding bodies, companies operating in the innovation space and others. […]