**Please note the later than usual time for this seminar in our series. This talk will start at 2pm UK.
This seminar will be conducted through Zoom. Please register to join this seminar. You will then receive an email with the dial in details. Please check your spam/junk folders.
The meeting is set up so that you will join muted and without video. You will be held in a virtual waiting room until the speaker is ready to start. There will be time at the end for a Q&A session. Please use the 'raise your hand' function and the presenter will unmute you. A video on how to do this is here.
With the speakers permission, we will be recording the presentation portion of this talk. The Q&A will not be recorded and any Chat will not be saved. We will make these talks available upon request via a password protected/time sensitive link. To request a copy of the recording please email email@example.com.
Successful navigation of the Covid-19 pandemic is predicated on public cooperation with safety measures and appropriate perception of risk, in which emotion and attention play important roles. Signatures of public emotion and attention are present in social media data, thus natural language analysis of this text enables near-to-real-time monitoring of indicators of public risk perception. We compare key epidemiological indicators of the progression of the pandemic with indicators of the public perception of the pandemic constructed from ∼20 million unique Covid-19-related tweets from 12 countries posted between 10th March and 14th June 2020. We find evidence of psychophysical numbing: Twitter users increasingly fixate on mortality, but in a decreasingly emotional and increasingly analytic tone. Semantic network analysis based on word co-occurrences reveals changes in the emotional framing of Covid-19 casualties that are consistent with this hypothesis. We also find that the average attention afforded to national Covid-19 mortality rates is modelled accurately with the Weber–Fechner and power law functions of sensory perception. Our parameter estimates for these models are consistent with estimates from psychological experiments, and indicate that users in this dataset exhibit differential sensitivity by country to the national Covid-19 death rates. Our work illustrates the potential utility of social media for monitoring public risk perception and guiding public communication during crisis scenarios.
Read the full paper at https://rdcu.be/cclMa.