Dataset Information

Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic.

ABSTRACT: COVID-19 represents the most severe global crisis to date whose public conversation can be studied in real time. To do so, we use a data set of over 350 million tweets and retweets posted by over 26 million English speaking Twitter users from January 13 to June 7, 2020. We characterize the retweet network to identify spontaneous clustering of users and the evolution of their interaction over time in relation to the pandemic's emergence. We identify several stable clusters (super-communities), and are able to link them to international groups mainly involved in science and health topics, national elites, and political actors. The science- and health-related super-community received disproportionate attention early on during the pandemic, and was leading the discussion at the time. However, as the pandemic unfolded, the attention shifted towards both national elites and political actors, paralleled by the introduction of country-specific containment measures and the growing politicization of the debate. Scientific super-community remained present in the discussion, but experienced less reach and became more isolated within the network. Overall, the emerging network communities are characterized by an increased self-amplification and polarization. This makes it generally harder for information from international health organizations or scientific authorities to directly reach a broad audience through Twitter for prolonged time. These results may have implications for information dissemination along the unfolding of long-term events like epidemic diseases on a world-wide scale.

SUBMITTER: Durazzi F

PROVIDER: S-EPMC8490394 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe COVID-19 pandemic has presented new challenges surrounding end-of-life planning and has been associated with increased online discussion about life support.Research questionHow has online communication about advance care planning (ACP) and specific life-sustaining interventions (LSIs) changed during the pandemic?Study design and methodsConversations on Twitter containing references to LSIs (eg, "ECMO") or ACP (eg, "DNR/DNI") were collected between January 2019 and May 2021. User account metadata were used to predict user demographic information and to classify users as organizations, individuals, clinicians, or influencers. The number of impressions was compared across these user categories and the content of tweets analyzed by using natural language processing models to identify topics of discussion and associated emotional sentiment.ResultsThere were 202,585 unique tweets about LSIs and 67,162 unique tweets about ACP. Users who were younger, male, or influencers were more likely to discuss LSIs online. Tweets about LSIs were associated with more positive emotional sentiment scores than tweets about ACP (LSIs, 0.3; ACP, -0.2; P < .001). Among tweets about ACP, most contained personal experiences related to the death of loved ones (27%) or discussed discrimination through do-not-resuscitate orders directed at the elderly and disabled (19%). Personal experiences had the greatest retweet-to-tweet-ratio (4.7), indicating high levels of user engagement. Tweets about discrimination contained the most negative net sentiment score (-0.5).InterpretationThe observed increase in tweets regarding LSIs and ACP suggests that Twitter was consistently used to discuss treatment modalities and preferences related to intensive care during the pandemic. Future interventions to increase online engagement with ACP may consider leveraging influencers and personal stories. Finally, we identified do-not-resuscitate-related discrimination as a commonly held public fear, which should be further explored as a barrier to ACP completion and can be proactively addressed by clinicians during bedside goals-of-care discussions.

Dataset Information

Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets