Reading Concordances in the 21st Century - University of Birmingham

The Reading Concordances in the 21st Century project proposes an innovative approach to reading concordances. In today's world, the amount of text communicated in electronic form is ever-increasing and there is a growing need for approaches to extract meanings from texts at scale.

Through the collaboration between the University of Birmingham and Friedrich-Alexander-Universität Erlangen-Nürnberg we combine strengths in theoretical work in corpus linguistics with expertise in computational algorithms in order to develop a systematic methodology for reading concordances and corresponding algorithms for the semi-automatic analysis of concordance lines.

We will specifically implement the software FlexiConc to support the corpus linguist researcher in organising and interpreting concordances. To develop and test our approach, we will conduct two case studies. The first case study will focus on body language in fiction compared to non-fiction texts. The second case study will focus on political argumentation in social media, formalising its findings as corpus queries that can be used for automatic argumentation mining. Both case studies include a comparative dimension between English and German.

Project team

Professor Michaela Mahlberg (PI), University of Birmingham

Professor Mahlberg's research focuses on language as a social phenomenon. A large part of Professor Mahlberg’s research deals with the language of Dickens’s fiction, literary linguistics, and discourse analysis. She is the editor of the International Journal of Corpus Linguistics (published by John Benjamins) and, together with Gavin Brookes, she edits the book series Corpus and Discourse (published by Bloomsbury). She is the Vice President of the international Dickens Society, she is a Fellow of the Alan Turing Institute in London, and she hosts the podcast “Life and Language”.

Professor Stephanie Evert (PI), FAU Erlangen-Nürnberg

Professor Dr. Stephanie Evert is Chair of Computational Corpus Linguistics at Friedrich-Alexander Universität Erlangen-Nürnberg. After studying mathematics, physics and English linguistics, she received a PhD degree in computational linguistics from the University of Stuttgart, Germany. Her research interests encompass the quantitative methodology of corpus linguistics, multivariate analysis and distributional semantics, applied corpus studies and digital humanities, tools for processing large text corpora, the combination of human interpretation with machine learning (digital hermeneutics), as well as language technology and its applications.

Natalie Finlayson (RF), University of Birmingham

Natalie joined the RC21 team in May 2023, having previously held roles as a Research Associate in Language Education (2022-23) and Learning Resource Developer (2019-2022) at the University of York, and various teaching positions at the University of Glasgow. She received her PhD in English Language and Linguistics from the University of Glasgow in 2022. In her research, she has used corpus methods in combination with other approaches to answer questions in cognitive semantics, EAP, language education, and medical humanities, and to inform the development of materials, tools and methodological processes for applied linguistics purposes. She is assistant editor of the International Journal of Corpus Linguistics.

Alexander Piperski (RF), FAU Erlangen-Nürnberg

After completing my studies in Germanic Philology at Lomonosov Moscow State University in 2010, I continued my education with M.A. studies in Bremen and Palermo, graduating in 2012. I received my PhD from Lomonosov Moscow State University in 2015, and from then until 2022, I taught corpus linguistics and other related courses at various universities in Moscow. Since 2023, I have been working as a postdoctoral researcher at the University of Erlangen–Nuremberg. My research interests include corpus linguistics and quantitative methods in linguistics.

Connect with us

For feedback and questions please contact us at @rc21project.