Biography

Dr. Daniele Rotolo is a Senior Lecturer in Science, Technology and Innovation Policy at SPRU (Science Policy Research Unit) at the University of Sussex. From 2014 to 2016, Daniele was an EU Marie Curie Researcher at SPRU and the School of Public Policy of Georgia Institute of Technology (Atlanta, US). Daniele holds a PhD (European Doctorate) in Innovation Management from Scuola Interpolitecnica (Italy), a joint PhD program among the Technical University of Bari, Technical University of Milan, and Technical University of Turin. During his PhD, Daniele was also a visiting researcher at University College London (London, UK) and Stern Business School at New York University (New York, US). He holds a PhD (European Doctorate) in Innovation Management from Scuola Interpolitecnica (Italy), a joint PhD program among the Technical University of Bari, Technical University of Milan, and Technical University of Turin. During his PhD, Daniele was also a visiting researcher at University College London (London, UK) and Stern Business School at New York University (New York, US). Daniele has received research funding from the European Commission, Cancer Research UK, and Higher Education Funding Council for England (HEFCE). His most recent work has focussed on the conceptualisation and operationalisation of emerging technologies, inter-organisational network dynamics featuring technological change, scientometric mapping techniques, the role of networks in knowledge creation, barriers to interdisciplinary research, and the determinants of academic productivity. This work has been published in top-tier journals in the field of science policy and innovation studies such as Research Policy, Journal of Organizational Behaviour, and Journal of the Association for Information Science and Technology (JASIST). Daniele is also Associate Editor of Research Policy and ad hoc reviewer for a number of leading journals.

Personal Website: http://www.danielerotolo.com/

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Episode 4: Diving in Deep to the Data: Text Mining and Deep Transitions

Episode 4: Diving in Deep to the Data: Text Mining and Deep Transitions
Deep Transitions Podcast Series

 
 
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What can over 3.5 million pages of the New York Times, and 2000 issues of Scientific American, tell us about the social changes witnessed from 1850 to the present day? In this week’s episode, Diving in Deep to the Data: Text Mining and Deep Transitions, Frederique Bone and Daniele Rotolo tell us how they converted…