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Biography

My research lies in the field of computational social media analytics, a domain closely aligned with data science and concerned with extracting meaningful insights from large‑scale digital data to inform decisions and strategies. I take an interdisciplinary approach to understanding public opinion, trends and behaviours across a range of topics, addressing questions at the intersection of news, politics and digital communication.

Previously, I have published on the following areas:

• Sentiment Analysis: The computational identification and categorisation of opinions expressed in text. My work has examined the of sentiment analysis tools and the influence of text on their accuracy.

• Spatiotemporal databases: Repositories that record and manage information about both space and time, typically capturing the movement of objects. I investigate periodic in such data to reveal underlying structures and support predictive modelling.

• Social robots: Technology has the potential to support healthy to age in place. I have explored how home automation and assistive technologies can promote independent living and how older adults with these .

• Web-based horizon scanning: This research focused on acquiring real‑time, web‑based information on emerging trends, opportunities and constraints that may affect the achievement of management goals. contributed to improved preparedness and informed the incorporation of mitigation and exploitation strategies into policy‑making.

• Web crawling: Search engines rely on large indices of word occurrences on web pages to cross‑reference sites with keywords. These indices are maintained by autonomous , and my research has examined methods for efficient large‑scale crawling and indexing.

Prizes and Awards

In 2014, Dr Marco Palomino won a Highly Commended Paper award by the . The award was granted at the . Emerald runs these awards to acknowledge the excellent contributions made by its authors, editors, and reviewers.

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.

Current 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