75 citations · 215 across the 24 of their papers we have counts for
25 papers
Scoring Grant Applications with Large Language Models
Mike Thelwall, David Pride, Francesco Osborne +4
Purpose: Assessing grant applications is time-consuming and difficult, adding to the overall burden of academic peer review. Whilst funders are exploring whether AI can help, there…
COCI: Conference Organisers and Content Identifier
Angelo Salatino, Francesco Osborne, Alexis Vizcaino +2
Despite the critical role of grey literature in scholarly communication, artefacts such as Calls for Papers (CfPs) remain largely isolated from modern Scholarly Knowledge Graphs. T…
A Pathway for Assessing Grey Literature: Leveraging AI to Extract Conference Metadata and Organiser Information from Calls for Papers
Angelo Salatino, Francesco Osborne, Alexis Vizcaino +2
Despite its importance, grey literature, including Calls for Papers (CfPs), remains largely overlooked in Metascience and Scientometric analysis due to its unstructured, highly het…
Benchmarking Resource-Efficient LLMs for Research Topic Ontology Generation in the Biomedical Field
Tanay Aggarwal, Angelo Salatino, Francesco Osborne +1
Knowledge Organization Systems like Ontologies and taxonomies are fundamental for structuring scientific knowledge, yet their manual curation presents a persistent bottleneck in kn…
Representing Research Attention as Contextually Structured Flows
Jessica Rodrigues, Angelo Salatino, Gard Jenset +1
Research metrics use attention as evidence of societal impact. Yet attention serves as evidence only once interpreted, and its meaning depends on its contextual structure, not on v…
Research Entity Extraction and Topic Detection from UKRI Grant Proposals
Xingran Ruan, Angelo Salatino, Rosa Filgueira +4
This paper presents preliminary findings from a UKRI-funded Metascience project comparing three LLM-based approaches, GPT-4o, Mistral, and a bespoke algorithm, DSIT-Taxonomies, for…
Are Researchers Being Replaced by Artificial Intelligence?
Angelo A. Salatino, Ansgar Scherp, Christin Katharina Kreutz +1
A Nature survey from 2023 involving 1,600 researchers shows that scientists are ``concerned, as well as excited, by the increasing use of artificial-intelligence tools in research.…
How Do LLMs Encode Scientific Quality? An Empirical Study Using Monosemantic Features from Sparse Autoencoders
Michael McCoubrey, Angelo Salatino, Francesco Osborne +1
In recent years, there has been a growing use of generative AI, and large language models (LLMs) in particular, to support both the assessment and generation of scientific work. Al…
Integrating Large Language Models and Knowledge Graphs to Capture Political Viewpoints in News Media
Massimiliano Fadda, Enrico Motta, Francesco Osborne +2
News sources play a central role in democratic societies by shaping political and social discourse through specific topics, viewpoints and voices. Understanding these dynamics is e…
Polarity Detection of Sustainable Development Goals in News Text
Andrea Cadeddu, Alessandro Chessa, Vincenzo De Leo +5
The United Nations' Sustainable Development Goals (SDGs) provide a globally recognised framework for addressing major societal, environmental, and economic challenges. While recent…
A Hybrid AI Methodology for Generating Ontologies of Research Topics from Scientific Paper Corpora
Alessia Pisu, Livio Pompianu, Francesco Osborne +3
Taxonomies and ontologies of research topics (e.g., MeSH, UMLS, CSO, NLM) play a central role in providing the primary framework through which intelligent systems can explore and i…
Leveraging Large Language Models for Generating Research Topic Ontologies: A Multi-Disciplinary Study
Tanay Aggarwal, Angelo Salatino, Francesco Osborne +1
Ontologies and taxonomies of research fields are critical for managing and organising scientific knowledge, as they facilitate efficient classification, dissemination and retrieval…
Modelling and Classifying the Components of a Literature Review
Francisco Bolaños, Angelo Salatino, Francesco Osborne +1
Previous work has demonstrated that AI methods for analysing scientific literature benefit significantly from annotating sentences in papers according to their rhetorical roles, su…
A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals
Andrea Cadeddu, Alessandro Chessa, Vincenzo De Leo +6
In 2012, the United Nations introduced 17 Sustainable Development Goals (SDGs) aimed at creating a more sustainable and improved future by 2030. However, tracking progress toward t…
Large Language Models for Scholarly Ontology Generation: An Extensive Analysis in the Engineering Field
Tanay Aggarwal, Angelo Salatino, Francesco Osborne +1
Ontologies of research topics are crucial for structuring scientific knowledge, enabling scientists to navigate vast amounts of research, and forming the backbone of intelligent sy…
A Survey on Knowledge Organization Systems of Research Fields: Resources and Challenges
Angelo Salatino, Tanay Aggarwal, Andrea Mannocci +2
Knowledge Organization Systems (KOSs), such as term lists, thesauri, taxonomies, and ontologies, play a fundamental role in categorising, managing, and retrieving information. In t…
Artificial Intelligence for Literature Reviews: Opportunities and Challenges
Francisco Bolanos, Angelo Salatino, Francesco Osborne +1
This manuscript presents a comprehensive review of the use of Artificial Intelligence (AI) in Systematic Literature Reviews (SLRs). A SLR is a rigorous and organised methodology th…
Diversity of Expertise is Key to Scientific Impact: a Large-Scale Analysis in the Field of Computer Science
Angelo Salatino, Simone Angioni, Francesco Osborne +2
Understanding the relationship between the composition of a research team and the potential impact of their research papers is crucial as it can steer the development of new scienc…
Characterising Research Areas in the field of AI
Alessandra Belfiore, Angelo Salatino, Francesco Osborne
Interest in Artificial Intelligence (AI) continues to grow rapidly, hence it is crucial to support researchers and organisations in understanding where AI research is heading. In t…
Trans4E: Link Prediction on Scholarly Knowledge Graphs
Mojtaba Nayyeri, Gokce Muge Cil, Sahar Vahdati +8
The incompleteness of Knowledge Graphs (KGs) is a crucial issue affecting the quality of AI-based services. In the scholarly domain, KGs describing research publications typically…
Detection, Analysis, and Prediction of Research Topics with Scientific Knowledge Graphs
Angelo Salatino, Andrea Mannocci, Francesco Osborne
Analysing research trends and predicting their impact on academia and industry is crucial to gain a deeper understanding of the advances in a research field and to inform critical…
The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articles
Angelo A. Salatino, Francesco Osborne, Thiviyan Thanapalasingam +1
Classifying research papers according to their research topics is an important task to improve their retrievability, assist the creation of smart analytics, and support a variety o…
Improving Editorial Workflow and Metadata Quality at Springer Nature
Angelo A. Salatino, Francesco Osborne, Aliaksandr Birukou +1
Identifying the research topics that best describe the scope of a scientific publication is a crucial task for editors, in particular because the quality of these annotations deter…
Ontology Extraction and Usage in the Scholarly Knowledge Domain
Angelo A. Salatino, Francesco Osborne, Enrico Motta
Ontologies of research areas have been proven to be useful in many application for analysing and making sense of scholarly data. In this chapter, we present the Computer Science On…