Dr Martin Sykora PhD., BSc.
Lecturer in Information Management
Social media analytics; natural language processing and text-mining; advanced sentiment analysis (micro-blogging / Twitter); applied machine learning and data-mining; Big Data handling techniques; Web 2.0 and digital citizenship; information retrieval; information management
Martin has published research articles in the Journal of Social Science & Medicine, PLOS One, the Lancet, Journal of Systems and Information Technology, among many others and regularly contributes to prestigious international conferences such as Hawaii International Conference on Computer Systems (HICCS), European Conference on Social Media (ECSM), International Conference on Knowledge Engineering and Ontology Development (KEOD), or International Conference on Machine Learning (ICML). He serves on the peer review college for UK Research and Innovation Future Leaders Fellowships (UKRI FLF) scheme, regularly reviews grants for UKRI, and acts as a reviewer for several leading academic journals such as the International Journal of Human Computer Studies, Social Science and Medicine, Information Technology and People, Semantic Web Journal, Social Media and Society, PLOS One among others.
Martin successful secured over £340,000 (£640,000 with his O3C mini-CDT award as Co-I) in research funding from various funding bodies, including EU Horizon 2020, SSHRC (Social Sciences and Humanities Research Council, Canada), Metropolitan Police (Mayor’s Office, London), EPSRC (Engineering and Physical Sciences Research Council), and DSTL (Defence Science and Technology Lab; the executive agency of Ministry of Defence for the UK).
Martin’s teaching interests are in big data analytics, social media research, machine learning and computational linguistics, and more generally across various information science topics. He has taught across undergraduate (i.e., bachelor's) and postgraduate (master's) level, and has been supervising a number of doctoral researchers (i.e., PhD students). He is the director of School of Business and Economics' undergraduate Information Management and Business (BSc. in IMB) programme.
- Social-Media Analytics
- Natural Language Processing and Text-Mining
- Practical Machine Learning Applications and Data-Mining
- Advanced Sentiment Analysis (Micro-blogging / Twitter)
- Big data handling techniques
- Multimedia and Text Mining
- Web 2.0 and digital citizenship
- Information Retrieval and Information Management