About

About this project

The project investigates questions of public health, communication, and social variation among residents of Edinburgh and the Lothians in relation to COVID-19. The project draws on individuals’ personal accounts of the pandemic, in the form of video/audio diary data recorded by Lothian residents between 1 May 2020 and 15 July 2021. The intimate, immediate, and spontaneous nature of video/audio diaries makes them a unique, time-sensitive data resource for assessing drivers of individual experience, including:

uptake of public health measures,
impacts on mental health, and
drivers of hardship, anxiety, and stigma.

https://www.youtube.com/watch?v=jB__kfaleoQ&feature=youtu.be

The Lothian Diary Project is made possible by a cross-School collaboration among data scientists, linguists, psychotherapists, public health researchers, and political scientists.

Publications

Cowie, Claire, Lauren, Hall-Lew, Zuzana Elliott, Anita Klingler, Nina Markl, and Stephen Joseph McNulty. “Imagining the city in lockdown: Place in the COVID-19 self-recordings of the Lothian Diary Project”. In: Frontiers in Artificial Intelligence 5 (2022). doi: 10.3389/frai.2022.945643. https://www.frontiersin.org/articles/10.3389/frai.2022.945643/full

Hall-Lew, Lauren, Claire Cowie, Catherine Lai, Nina Markl, Stephen Joseph McNulty, Shan-Jan Sarah Liu, Clare Llewellyn, Beatrice Alex, Zuzana Elliott, and Anita Klingler. 2022. The Lothian Diary Project: Sociolinguistic Methods during the COVID-19 Lockdown. Linguistics Vanguard. https://www.degruyter.com/document/doi/10.1515/lingvan-2021-0053/html

Hall-Lew, Lauren, Claire Cowie, Stephen Joseph McNulty, Nina Markl, Catherine Lai, Clare Llewellyn, Beatrice Alex, Nini Fang, Zuzana Elliott, and Anita Klinger. 2021. The Lothian Diary Project: Investigating the Impact of the COVID-19 Pandemic on Edinburgh and Lothian Residents. Journal of Open Humanities Data 7(4):1–5. DOI: https://doi.org/10.5334/johd.25

Markl, Nina & Catherine Lai. 2021. Context-sensitive evaluation of automatic speech recognition: Considering user experience & language variation. Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing, 34–40. Association for Computational Linguistics. April 20. https://www.aclweb.org/anthology/2021.hcinlp-1.6/