We’re using sophisticated computer-based linguistic analysis to understand how journalists write about health, including diabetes, obesity, disability, and other health-related conditions or issues.
We exploit the power of computer-based text analysis (corpus linguistics) for quantitative and qualitative insights into the language of health. We use computer software to monitor and analyse media coverage of diabetes, obesity, disability, and other health-related conditions or issues so we can better understand the ways in which they are represented in journalistic texts. We identify any problematic issues such as stigma, blame or invisibility, and aim to disseminate our results to relevant key stakeholders to achieve positive change. Through interdisciplinary research, we connect linguistic expertise with the expertise of scientists and health researchers.
We aim to:
Our work initially focussed on the representation of diabetes in the Australian news media. We analysed diabetes coverage in 12 Australian metropolitan/national newspapers over a period of five years (2013-2017). We identified the amount and type of coverage in 694 articles (about 250,000 words), as well as the labelling used to refer to people with diabetes. We also undertook a study on references to Aboriginal and Torres Strait Islander peoples or issues in this dataset. Our project on diabetes has now been completed and a summary of the project and links to all associated publications are available here.
We have also completed a collaborative study on disability in Australian newspapers (over a period of 20 years), with a short description available on Language on the Move.
For our more recent project on Australian media representations of obesity we collaborated with the Sydney Informatics Hub and the University of Lancaster. We built a new corpus of Australian newspaper coverage of obesity containing over 26,000 articles from 12 newspapers 2008-2019 (more than 16 million words). We then collaborated on a series of corpus linguistic and computational analyses of this dataset, largely centred on weight stigma/bias and including international comparisons with British newspapers. You can find a summary of the project and links to its outputs here.
We are striving to achieve greater awareness of media coverage and working towards improving practices of media representation. To this end, we created a range of stakeholder documents, including an information sheet to help scientists and other researchers engage with the media, a tip sheet for journalists, an executive summary of our research results, and a video for wide distribution. These resources can be accessed under ‘featured research areas’. We also regularly submit resources to the Analysis & Policy Observatory to make our research visible, discoverable, and usable.
Initially funded by a University of Sydney Multidisciplinary Arts and Social Sciences Inaugural Fellowship (2019) and a Sydney Research Accelerator (SOAR) fellowship (2019-2020). More recently supported through the Ho Kong Fung Ling Research Fund at the Charles Perkins Centre. Research infrastructure support came from our collaboration on the Australian Text Analytics Platform and the Language Data Commons of Australia (a co-investment partnership with the Australian Research Data Commons through the HASS and Indigenous Research Data Commons . We acknowledge the technical assistance provided by the Sydney Informatics Hub, a Core Research Facility of the University of Sydney.
URL
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Diabetes in the media
Phone: +61 2 8627 1616
Email: info.perkins@sydney.edu.au
John Hopkins Drive, Camperdown NSW 2006
Opening hours: Monday to Friday, 9am to 5pm
