Dr Matthew Rowe

Lecturer in Social Computing

Email: m.rowe@lancaster.ac.uk
Address: School of Computing and Communications, Infolab 21, Lancaster University,
Lancaster, LA1 4WA UK
URI:http://www.lancs.ac.uk/staff/rowem/foaf.rdf#me

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About

My core research interest is in the area of Social Computing where I examine how users engage with the social web and social media, and how such engagement changes over time and the factors that are linked with such changes. To facilitate my research I examine the following topics:
  • Automated prediction methods based on machine learning (i.e. objective optimisation techniques)
  • Data mining using statistical models and scalable pattern recognition techniques
  • The semantic web and linked data, including user and community representation paradigms
  • Identity disambiguation and coreference resolution

Before joining Lancaster I worked for two years (2010-2012) as a Research Assciate at the Knowledge Media Institute (KMi) at the Open University, Milton Keynes, on the EU-Funded Integrated Project ROBUST. On the project I worked on semantic models of user behaviour, role mining and community health and behaviour change prediction methods. Before joining KMi I studied for a Ph.D. (2006-2010) under the supervision of Prof. Fabio Ciravegna at the University of Sheffield. My Ph.D. thesis explored automated identity disambiguation methods and how such methods could be supported using Social Data leveraged from Social Web platforms such as Facebook, MySpace and Twitter.

Recent Publications

For a full list of my publications click here.

Teaching

I am director of the MSc Data Science with Computing Specialism (due to start 2014-2015). I currently teach the following four modules:
  • SCC130 Information Systems - Social and professional issues of information systems (censorship, privacy, surveillance, copyright, patent law, malware, viruses)
  • SCC321 Selected Research Topics - Social data analysis, reviewing methods and research skills
  • SCC403 Data Mining - Data representation using semantics, machine learning, and statistical methods
  • SCC413 Applied Data Mining - Semantic web, social networks, recommender systems, network and web science, information extraction and retrieval, and scalable data processing

Ph.D. Student Supervision

I currently supervise the following Ph.D. students:
  • Daniel Kershaw - Researching language diffusion through social networks
  • Faiza Samreen - Researching machine learning techniques to enhance cloud adoption strategies for data intensive applications
  • Maria Terzi - Researching review-based recommender systems

Projects

  • Analysis of historic drought and water scarcity in the UK: a systems-based study of drivers, impacts and their interactions. To start in June 2014. NERC funded for 4-years. SCC Role: Language Cascade Mining from Social Streams.
  • Pattern Analsysis for aTTention Economics in Social web systems (PATTES). 2013-2014. Lancaster Unviersity Internal Funding.

Program Committee Memberships

Journals

Conferences

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