Matt Gee
Matt Gee works in the field of Corpus Linguistics, developing research and teaching tools as a member of the Research and Development Unit for English Studies. This includes the WebCorp suite of online search and analysis tools, which are designed to treat the web as a source of linguistic data. WebCorp Live refines the results returned by commercial web search engines, presenting them in a manner suitable for linguistic study. It is used by teachers, researchers and translators around the world. WebCorp LSE provides access to pre-processed web-corpora for Corpus Linguistic analysis (including wildcard and part-of-speech search, concordancing, collocation, and time-series analysis). It is now being tested for use in teaching by English language learners under the name WebCorp Learn.
Matt developed a tool for online collaborative annotation called eMargin. eMargin is a web-based tool that replicates the practice of close reading by allowing the annotation and discussion of digital texts. eMargin is used by educational institutions of all levels for literature studies, language learning, literary skills development, linguistic annotation and humanities research. It is also used outside of education, for example in the discussion of policy documents by political groups.
As part of the TRAC:COVID project, Matt developed an online dashboard combining text analysis methods with data visualisation to assist users from a variety of backgrounds in interpreting a large dataset of tweets. The project investigated the online conversation surrounding the COVID-19 pandemic from a linguistic perspective, examining the clarity and reception of official messaging and the trustworthiness of information sources.
As a continuation of his research into tools and methods to support linguistic analysis, Matt developed XTranscript. XTranscript is an online tool to convert transcripts encoded with Conversational Analysis notation into XML. The resulting XML can then be subjected to quantitative analysis using mature XML processing technologies, such as XPath and XQuery.
In his recent research, Matt has used automated methods to study topic and user interactions on web-forums, cultural and sociolinguistic phenomena on Twitter, and lexical and semantic change in online news. He is also working on a visualisation tool for the analysis of open-text questions in surveys, with a focus on the National Student Survey.