This post aims to act like a hub for all the relevant information about my doctoral work. It will be constantly updated with new source and developments.
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. In this dissertation, we begin to address this challenge by performing a study of the dynamics preceding the creation of new topics. This study indicates that the emergence of a new topic is anticipated by a significant increase in the pace of collaboration between relevant research areas, which can be seen as the ‘ancestors’ of the new topic. Based on this understanding, we developed Augur, a novel approach to effectively detecting the emergence of new research topics. Augur analyses the diachronic relationships between research areas and is able to detect clusters of topics that exhibit dynamics correlated with the emergence of new research topics. Here we also present the Advanced Clique Percolation Method (ACPM), a new community detection algorithm developed specifically for supporting this task. Augur was evaluated on a gold standard of 1,408 debutant topics in the 2000-2011 timeframe and outperformed four alternative approaches in terms of both precision and recall.
(I submitted my PhD dissertation on 28 Nov 2018: post.)
Relevant Papers (in chronological order)
- Angelo Antonio Salatino, Francesco Osborne, Enrico Motta AUGUR: Forecasting the Emergence of New Research Topics. In JCDL ’18: The 18th ACM/IEEE Joint Conference on Digital Libraries, June 3–7, 2018, Fort Worth, TX, USA, 2018
- Angelo Antonio Salatino, Francesco Osborne, Enrico Motta How are topics born? Understanding the research dynamics preceding the emergence of new areas. In PeerJ Computer Science, pp. e119. 2017
- Angelo Antonio Salatino, Enrico Motta Detection of Embryonic Research Topics by Analysing Semantic Topic Networks. In 2016 Workshop on “Semantics, Analytics and Visualization: Enhancing Scholarly Data” at 25th International World Wide Web Conference (WWW 2016), Montreal, Quebec (CA), Springer, 2016
- Angelo Antonio Salatino Early Detection and Forecasting of Research Trends. In Proceedings of the Doctoral Consortium at the 14th International Semantic Web Conference (ISWC 2015), pp. 49-56. 2015
On the 8th February 2017, I gave a seminar to my department in which I described my doctoral work, including hypotheses, research questions, main assumptions, approaches and some preliminary results. To replay the seminar follow this link: PLAY
- Angelo Antonio Salatino Advances Towards Early Detection of Research Topics. CRC Conference 2016 at the Open University