The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities

Chen, Yiqiao; Niu, Haifeng; Silva, Elisabete

doi:10.1016/j.cities.2022.104054

Cited by 12 publications

(12 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our result has 1 topic common with an existing study about the United States reopening in 2020 [14]-that social media discussions include emotions such as fear and anxiety toward potential infection (after the second postlockdown phase in the United States). Different to both US and UK reopening studies [14,24], we found that Weibo discussions surrounding COVID-19 medications in China after the zero-COVID policy focused more on seeking medical resources and sharing experiences with medication shortage.…”

Section: Topic Characteristics During China's Exit From the Zero-covi...contrasting

confidence: 91%

“…Few studies have specifically examined social media topics after the lifting of lockdowns or reopening policies, and their attention to COVID-19 medications was even less [14,24,64,65]. Our result has 1 topic common with an existing study about the United States reopening in 2020 [14]-that social media discussions include emotions such as fear and anxiety toward potential infection (after the second postlockdown phase in the United States).…”

Section: Topic Characteristics During China's Exit From the Zero-covi...mentioning

confidence: 50%

“…Lifting of lockdowns and monitoring programs could increase the (perceived) chances of infection for the general population [14]. Although psychobehavioral mechanisms are conditioned by many other factors, the termination of the zero-COVID policy or lockdowns can change the relative weight of these perceptions and therefore people's social media discussions [23,24].…”

Section: Personal Vs Social Risk Perceptionsmentioning

confidence: 99%

See 2 more Smart Citations

Topic and Trend Analysis of Weibo Discussions About COVID-19 Medications Before and After China’s Exit from the Zero-COVID Policy: Retrospective Infoveillance Study

Lan,

Ren,

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

Background After 3 years of its zero-COVID policy, China lifted its stringent pandemic control measures with the announcement of the 10 new measures on December 7, 2022. Existing estimates suggest 90%-97% of the total population was infected during December. This change created a massive demand for COVID-19 medications and treatments, either modern medicines or traditional Chinese medicine (TCM). Objective This study aimed to explore (1) how China’s exit from the zero-COVID policy impacted media and the public’s attention to COVID-19 medications; (2) how social COVID-19 medication discussions were related to existing model estimates of daily cases during that period; (3) what the diversified themes and topics were and how they changed and developed from November 1 to December 31, 2022; and (4) which topics about COVID-19 medications were focused on by mainstream and self-media accounts during the exit. The answers to these questions could help us better understand the consequences of exit strategies and explore the utilities of Sina Weibo data for future infoveillance studies. Methods Using a scrapper for data retrieval and the structural topic modeling (STM) algorithm for analysis, this study built 3 topic models (all data, before a policy change, and after a policy change) of relevant discussions on the Chinese social media platform Weibo. We compared topic distributions against existing estimates of daily cases and between models before and after the change. We also compared proportions of weibos published by mainstream versus self-media accounts over time on different topics. Results We found that Weibo discussions shifted sharply from concerns of social risks (case tracking, governmental regulations, etc) to those of personal risks (symptoms, purchases, etc) surrounding COVID-19 infection after the exit from the zero-COVID policy. Weibo topics of “symptom sharing” and “purchase and shortage” of modern medicines correlated more strongly with existing susceptible-exposed-infected-recovered (SEIR) model estimates compared to “TCM formulae” and other topics. During the exit, mainstream accounts showed efforts to specifically engage in topics related to worldwide pandemic control policy comparison and regulations about import and reimbursement of medications. Conclusions The exit from the zero-COVID policy in China was accompanied by a sudden increase in social media discussions about COVID-19 medications, the demand for which substantially increased after the exit. A large proportion of Weibo discussions were emotional and expressed increased risk concerns over medication shortage, unavailability, and delay in delivery. Topic keywords showed that self-medication was sometimes practiced alone or with unprofessional help from others, while mainstream accounts also tried to provide certain medication instructions. Of the 16 topics identified in all 3 STM models, only “symptom sharing” and “purchase and shortage” showed a considerable correlation with SEIR model estimates of daily cases. Future studies could consider topic exploration before conducting predictive infoveillance analysis, even with narrowly defined search criteria with Weibo data.

show abstract

Section: Topic Characteristics During China's Exit From the Zero-covi...contrasting

confidence: 91%

Section: Topic Characteristics During China's Exit From the Zero-covi...mentioning

confidence: 50%

Section: Personal Vs Social Risk Perceptionsmentioning

confidence: 99%

See 1 more Smart Citation

Topic and Trend Analysis of Weibo Discussions About COVID-19 Medications Before and After China’s Exit from the Zero-COVID Policy: Retrospective Infoveillance Study

Lan,

Ren,

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…platforms provides the public with a channel to express their emotions and concerns during the crisis (Crooks et al, 2013; Hauthal et al, 2019; Mandel et al, 2012; Osorio‐Arjona et al, 2021; Tagliacozzo & Magni, 2018; Yuan et al, 2021; Zhang et al, 2019). Particularly in the era of big data, these emerging social media have great potential for mining public opinion, concern and feeling during floods, thus providing unique opportunities to support urban disaster management from bottom to top (Chen et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

“…Particularly in the era of big data, these emerging social media have great potential for mining public opinion, concern and feeling during floods, thus providing unique opportunities to support urban disaster management from bottom to top (Chen et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Social media insights on public perception and sentiment during and after disasters: The European floods in 2021 as a case study

Li,

Haunert,

Knechtel

et al. 2023

Transactions in GIS

View full text Add to dashboard Cite

Detecting and collecting public opinion via social media can provide near real‐time information to decision‐makers, which plays a vital role in urban disaster management and sustainable development. However, there has been little work focusing on identifying the perception and the sentiment polarity expressed by users during and after disasters, particularly regional flood events. In this article, we comprehensively analyze tweets data related to the “European floods in 2021” over time, topic, and sentiment, forming a complete workflow from data processing, topic modeling, sentiment analysis, and topic and sentiment prediction. The aim is to address the following research questions: (1) What are the public perception and main concerns during and after floods? (2) How does the public sentiment change during and after floods? Results indicate that there is a significant correlation between a flood's trend and the heat of corresponding tweets. The three topics that receive the most public concern are: (1) climate change and global warming; (2) praying for the victims: and (3) disaster situations and information. Negative sentiments are predominant during the floods and will continue for some time. We tested five different classifiers, of which TextCNN‐attention turned out to deliver the best predictions in topic and sentiment prediction, and performed well for sparse flood tweets, it can be used to predict the topic and sentiment polarity of a single tweet in real‐time during the flood events. Our findings can help disaster agencies to better understand the dynamics of social networks and develop stronger situational awareness towards a disaster, which can contribute to scientifically justified decision‐making in urban risk management and also meet the challenges associated with the global sustainable development goal 11 (SDGs) on Sustainable Cities and Communities.

show abstract

Transformation of Local Communities from Neighborhoods to Urban Commons in the Production of Social Representations of Space

Antonov,

Gornova,

Kontsevik

et al. 2024

Lecture Notes in Computer Science

View full text Add to dashboard Cite

The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities

Cited by 12 publications

References 47 publications

Topic and Trend Analysis of Weibo Discussions About COVID-19 Medications Before and After China’s Exit from the Zero-COVID Policy: Retrospective Infoveillance Study

Topic and Trend Analysis of Weibo Discussions About COVID-19 Medications Before and After China’s Exit from the Zero-COVID Policy: Retrospective Infoveillance Study

Social media insights on public perception and sentiment during and after disasters: The European floods in 2021 as a case study

Transformation of Local Communities from Neighborhoods to Urban Commons in the Production of Social Representations of Space

Contact Info

Product

Resources

About