Dr Martin Sykora is a Senior Lecturer (which is equivalent to Associate Professor) in Information Management, at the Centre for Information Management (CIM). He is a multi-disciplinary scholar at the frontier of computational social media research and sentiment analysis, investigating the role of social media in public health as well as how it shapes our behaviours in relation to communication of emotion and affect, political discourse and civic culture. Martin’s established international body of research bridges the social media, information management, information retrieval, communication and health sciences fields to transform established approaches by leveraging social media user generated content and big data analytics including machine learning, natural language processing and semantic modelling in novel ways.

Martin has published research articles in the Journal of Social Science & Medicine, PLOS One, Big Data & Society, 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); with over 50 peer reviewed research papers across journals and conferences. He serves on the peer review college of the National Research Centre on Privacy, Harm Reduction and Adversarial Influence Online (REPHRAIN), the UK Research and Innovation Future Leaders Fellowships (UKRI FLF) scheme, and regularly reviews grants for UKRI. He 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 £635,000 (£935,000 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), Innovate UK (APC), Swiss School of Public Health (SSPH+), 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 information science topics relating to social media platforms. He has taught across undergraduate (i.e., bachelor's) and postgraduate (master's) level, and has successfully supervised six doctoral researchers (i.e., PhD students) to completion, across his research area.

Previously Martin also worked as a Research Associate at 含羞草视频's Computer Science and Information Science departments, as well as the University of Leicester, and he has some commercial experience in Data Science and Analytics. Martin obtained his PhD in Computer Science at 含羞草视频.

• Social Media Analytics
• Social Media Research
• Advanced Sentiment Analysis
• Natural Language Processing and Text Mining
• Applied Machine Learning and Data Science
• Semantic Modelling and Unstructured Data Processing
• Big Data Handling Techniques
• Algorithmic Bias on Social Platforms
• Consent, Privacy and Ethical Issues with Social Platforms
• Web 2.0 and digital citizenship
• Mis/Disinformation Research
• Information Retrieval and Information Management