Monika Bednarek es doctora por la Universidad de Ausburgo, Alemania, en 2005. Realizó el posdoctorado en la Universidad de Sidney (2006-2008) y Universidad de Tecnología, Sydney (2008-2009). Investiga en lenguaje evaluativo entre la prensa “popular” y la prensa “seria”, el discurso emocional en los distintos registros de la lengua inglesa, y recientemente, el lenguaje de la ficción televisiva.
Entre sus campos de interés, se incluyen los campos de lingüística de corpus, eco-linguistica, análisis del discurso, sociolingüística, pragmática, lingüística cognitiva, y, específicamente, discurso mediático, expresión lingüística de las emociones, etc. Además es editora de la revista Discourse and Communication, y traductora jurada con certificación NAATI (inglés-alemán).
Investigating ‘most shared’ news from a corpus linguistic perspective
The sharing of news via social media platforms such as Facebook is now a significant part of mainstream online media use and is an increasingly important consideration in journalism practice and production. This paper discusses the results of a corpus linguistic approach to the analysis of online news-sharing on Facebook, with a focus on most-shared news stories that originate with print and broadcast English-language ‘heritage’ news media organisations (such as New York Times, Guardian, CNN). This is part of a larger, interdisciplinary project funded by the Australian Research, which brings together methods from computing science, linguistics, and audience research with the aim of developing an analytical framework for monitoring, classifying and interpreting news-sharing practices that can inform media industry development, journalism education and digital media policy. The project team includes researchers in journalism studies, information technologies and linguistics, working in collaboration with Australian media industry partners Mi9 and Share Wars.
This paper presents key findings from a corpus linguistic analysis of the top 100 ‘most shared’ news stories – a small corpus which allows for the combination of quantitative and qualitative corpus and discourse analytical techniques. Analyses combine the application of classic corpus linguistic tools (such as frequency analysis and concordancing) with manual, computer-aided annotation. The main focus is on discursive news values analysis (DNVA), as developed by Bednarek & Caple (2012a, b). This type of analysis focuses on newsworthiness, i.e. the worth of a happening or issue to be reported as news, as established via a set of news values (such as Negativity, Proximity, Eliteness, Unexpectedness, etc). Discursive news values analysis examines how this ‘worth’ – and these news values – are established through semiotic resources and practices. In this way we can gain fuller insights into the types of news that are widely shared in today’s new media landscape.
Bednarek, M. and Caple, H. 2012a. News discourse. London/New York: Continuum.
Bednarek, M. and Caple, H. 2012b. ‘‘‘Value Added’: Language, image and news value”. Discourse, Context & Media 1: 103-113.
Laurence Anthony es profesor en la Facultad de Ciencias e Ingeniería en la Universidad de Waseda, Japón. Fue director del Center for English Language Education (CELESE) y coordinador del programa de inglés técnico CELESE. Es Máster en Enseñanza de inglés como lengua extranjera y doctor en Lingüística aplicada por la Universidad de Birmingham, Reino Unido, además de ser graduado en física matemática por la Universidad de Mánchester. Sus intereses de investigación son la lingüística de corpus, tecnología educativa, procesamiento del lenguaje natural (PLN) y análisis de género.
Tailoring corpus tools for academia and the language industry: A developer’s perspective
Researchers in academia and industry are becoming increasingly interested in the development and application of corpus tools not only in areas such as applied linguistics, EFL materials development, and lexicography, but also in new areas, such as data science and digital humanities. In this presentation, I will first discuss the overlapping and differing needs of users in academia and industry and show how some of the most popular corpus tools have been designed with these audiences in mind. As part of the discussion, I will explain some of the advantages and disadvantages of using proprietary commercial tools and compare these with the advantages and disadvantages of using freeware, open source tools, or perhaps even creating custom tools using a programming language such as Python or R. Next, I will introduce some of my own software tools and explain how in some cases they have been adapted to meet the needs of a wide range of users across different academic disciplines and languages of interest, and in other cases, have been carefully customized to meet a very specific group of users in an industrial setting. I will conclude the presentation with some thoughts on the future of corpus tools development and suggestions for ways in which the audience may be able to contribute to this future.
“The company it keeps” – the Business of Corpus Linguistics
I have had a large variety of jobs since I started my working life in 1966 at the age of 18: weekly jobs via an employment agency; short-term contracts in engineering, schoolteaching, hospitals, and the railways; longer-term posts in the UK civil service and in universities; and a 7-year period of self-employment. I also completed 2 first degree courses, and a 3-year postgraduate research post.
In this paper, I will focus on my 30-plus years in corpus linguistics, and on academic and commercial projects that I have been involved in, and try to give an insight into the factors: participants (individuals and institutions), knowledge, technology, finances, skills, and processes, including managerial and administrative, that have shaped the discipline; the problems it has overcome or failed as yet to find solutions for; and tentatively suggest some ways forward.