TY - BOOK

T1 - Government crisis communication on social media

T2 - the multimodal discursive ecosystem of NHS COVID-19 policy messages

AU - Sha, Yuze

PY - 2025

Y1 - 2025

N2 - This thesis examines the multimodal ‘discursive ecosystem’ (Brookes & Hunt, 2021), formed by (1) the NHS’s COVID-19 policy messages on Twitter/X and (2) the associated comments. It focuses on the period from December 2020 to February 2022, when UK COVID-19 policy transitioned from stringent non-pharmaceutical interventions (NPIs) towards a vaccination-led approach, creating growing challenges for policy communication amid pandemic fatigue anddeclining compliance (Jørgensen et al., 2022).Social media platforms such as Twitter/X have played a growing role in government crisis communication, particularly within the broader e-Government initiative (OECD, 2003) and the NHS’s (2019) digital transformation strategy. Existing scholarship highlights social media as a primary public source of health information and a conduit for real-time updates during crises, yet this thesis is, to the best of my knowledge, the first to explore the multimodal social mediadialogues within government crisis communication.Understanding this multimodal discursive ecosystem is important, because it reveals how COVID-19 policy instructions were communicated by governmental institutions and received by Twitter/X users. Given the persistent accessibility of tweet threads, it holds the potential to reach a wide audience over time during the pandemic.Using ATLAS.ti to construct and analyse multimodal social media corpora, the thesis explores the multimodal discursive strategies employed by the NHS to communicate COVID-19 policy messages, and those used by the commenters to express stance and evaluation. The thesis offers insights into the multimodal discursive patterns that emerge in this ecosystem, which may not only reflect but also shape the public’s understanding of and attitudes toward the policyinstructions, and in turn their willingness to comply with these.

AB - This thesis examines the multimodal ‘discursive ecosystem’ (Brookes & Hunt, 2021), formed by (1) the NHS’s COVID-19 policy messages on Twitter/X and (2) the associated comments. It focuses on the period from December 2020 to February 2022, when UK COVID-19 policy transitioned from stringent non-pharmaceutical interventions (NPIs) towards a vaccination-led approach, creating growing challenges for policy communication amid pandemic fatigue anddeclining compliance (Jørgensen et al., 2022).Social media platforms such as Twitter/X have played a growing role in government crisis communication, particularly within the broader e-Government initiative (OECD, 2003) and the NHS’s (2019) digital transformation strategy. Existing scholarship highlights social media as a primary public source of health information and a conduit for real-time updates during crises, yet this thesis is, to the best of my knowledge, the first to explore the multimodal social mediadialogues within government crisis communication.Understanding this multimodal discursive ecosystem is important, because it reveals how COVID-19 policy instructions were communicated by governmental institutions and received by Twitter/X users. Given the persistent accessibility of tweet threads, it holds the potential to reach a wide audience over time during the pandemic.Using ATLAS.ti to construct and analyse multimodal social media corpora, the thesis explores the multimodal discursive strategies employed by the NHS to communicate COVID-19 policy messages, and those used by the commenters to express stance and evaluation. The thesis offers insights into the multimodal discursive patterns that emerge in this ecosystem, which may not only reflect but also shape the public’s understanding of and attitudes toward the policyinstructions, and in turn their willingness to comply with these.

KW - public health communication

KW - multimodal corpus

KW - social media discourse

KW - appraisal analysis

KW - social actor representation

U2 - 10.17635/lancaster/thesis/2838

DO - 10.17635/lancaster/thesis/2838

M3 - Doctoral Thesis

PB - Lancaster University

ER -