
Senior Lecturer
- About
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- Office Address
- School/Department
- School of Natural and Computing Sciences
Biography
My research lies in the field of social media analytics, which is closely related to data science and employs a variety of tools and techniques to examine large volumes of data to extract meaningful insights and inform decisions and strategies. I have followed an interdisciplinary approach to contribute to the understanding of public opinion, trends, and behaviours across several topics. This has led me to address questions at the cutting edge of news, politics, and marketing.
Previously, I have published on the following areas:
- Sentiment Analysis: The process of computationally identifying and categorising opinions expressed in text. I have worked on the application of sentiment analysis tools and the impact of pre-processing on the performance of such tools.
- Spatiotemporal databases: A spatiotemporal database is a repository that records and manages both space and time information. Typically, such databases capture the movement of objects. I am interested in detecting periodic patterns on such databases, because this may reveal underlying structures and help in making predictions.
- Social robots: Technology has the potential to support the ageing in place of healthy older adults. I have investigated how home automation could enable older people to live independently for longer, while exploring the engagement of older adults with technology.
- Web-based horizon scanning: My research focused on the acquisition of real-time, web-based information on emerging trends, opportunities and constraints that might affect the probability of achieving management goals and objectives. At the time, my work allowed for better preparedness and the incorporation of mitigation and exploitation into the policy making process.
- Web crawling: Search engines make use of large indices of word occurrences on Web pages to cross-reference Web sites to keywords. Such indices are maintained by crawlers, a special kind of computer program that browses the Web autonomously.
Memberships and Affiliations
- Internal Memberships
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At present, Dr Marco Palomino is the Athena Swan Lead for the School of Natural and Computing Sciences. He is helping to shape the School’s next submission to the Athena Swan Charter.
- External Memberships
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Professional Memberships
- Fellow of the Higher Education Academy (Advance HE).
Peer Review
- Guest Editor for the special issue of Applied Sciences (ISSN 2076-3417; Impact Factor: 2.5) on New Developments in Computational Linguistics to Support Decision Making.
- Former member of the Reviewer Board of the Big Data and Cognitive Computing (BDCC) journal (ISSN 2504-2289; Impact Factor: 3.7).
- Former member of the Reviewer Board of the Mathematics journal (ISSN 2227-7390; Impact Factor: 2.3).
Prizes and Awards
In 2014, Dr Marco Palomino won a Highly Commended Paper award by the Emerald Literati Network. The award was granted at the 2014 Meeting of the Academy of Management. Emerald runs these awards to acknowledge the excellent contributions made by its authors, editors, and reviewers.
- Research
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Research Overview
My research lies in the field of social media analytics, which is closely related to data science and employs a variety of tools and techniques to examine large volumes of data and extract meaningful insights to inform decision makers. I have followed an interdisciplinary approach to contribute to the understanding of public opinion, trends, and behaviours across several topics. This has led me to address questions at the cutting edge of news, politics, and marketing.
Research Areas
Accepting PhDs
I am currently accepting PhDs in Computing Science.
Please get in touch if you would like to discuss your research ideas further.
Computing Science
Accepting PhDsCurrent Research
Recently, Dr Marco Palomino has published research on the following topics.
Spatiotemporal databases: A spatiotemporal database is a repository that records and manages both space and time information. Typically, such databases capture the movement of objects. I am interested in detecting periodic patterns on such databases, because this may reveal underlying structures and help in making predictions. You can read about my recent work at https://www.mdpi.com/2504-2289/8/6/59
- Publications
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An X Study of the Evolution of COVID-19-Related Sentiments in the UK
Emotions in Code - The AI Frontier of Sentiment Analysis. Li, J. (ed.). IntechOpenChapters in Books, Reports and Conference Proceedings: ChaptersThe Influence of Human Factors on Adaptive Social Media Cybersecurity Training and Education
Chapters in Books, Reports and Conference Proceedings: Conference ProceedingsTowards a System Dynamics Framework for Human–Machine Learning Decisions: A Case Study of New York Citi Bike
Applied Sciences, vol. 14, no. 22, 10647Contributions to Journals: ArticlesEnsembling Machine Learning Models for Malware Detection.
Chapters in Books, Reports and Conference Proceedings: Conference ProceedingsAn Efficient Probabilistic Algorithm to Detect Periodic Patterns in Spatio-Temporal Datasets
Big data and cognitive computing, vol. 8, no. 6, 59Contributions to Journals: ArticlesAn Adaptive Cybersecurity Training Framework for the Education of Social Media Users at Work
Applied Sciences, vol. 13, no. 17, 9595Contributions to Journals: ArticlesEvaluating the Risks of Human Factors Associated with Social Media Cybersecurity Threats
Human Aspects of Information Security and Assurance: 17th IFIP WG 11.12 International Symposium, HAISA 2023, Kent, UK, July 4–6, 2023, Proceedings. Springer, pp. 349-363, 15 pagesChapters in Books, Reports and Conference Proceedings: Chapters- [ONLINE] DOI: https://doi.org/10.1007/978-3-031-38530-8_28
Visualizing the recovery of patients in Critical Care Units
Information Visualization, vol. 22, no. 3, pp. 209-222Contributions to Journals: ArticlesI am Robot, Your Health Adviser for Older Adults: Do You Trust My Advice?
International Journal of Social RoboticsContributions to Journals: ArticlesA Modeling Approach for Measuring the Performance of a Human-AI Collaborative Process
Applied Sciences, vol. 12, no. 22, 11642Contributions to Journals: Articles