ArticleSustainable cities and society2021
SNS Big Data Analysis Framework for COVID-19 Outbreak Prediction in Smart Healthy City.
Article in Sustainable cities and society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Big data analytics and sentiment analysis for health misinformation detection: a systematic literature review of influencing factors, implementation challenges and a data-driven adoption framework.Frontiers in big data · 2026Pooled it
- Smart City and Crisis Management: Lessons for the COVID-19 Pandemic.International journal of environmental research and public health · 2021Pooled it
- Exploring Consumer Perception of Food Insecurity Using Big Data.Foods (Basel, Switzerland) · 2025Article
- A Forecast Model for COVID-19 Spread Trends Using Blog and GPS Data from Smartphones.Entropy (Basel, Switzerland) · 2025Article
- Implementation and improvement of policies for building healthy cities in China.Frontiers in public health · 2024Article
- COVID-19 case prediction using emotion trendsFrontiers in public health · 2023Article
- Population flow based spatial-temporal eigenvector filtering modeling for exploring effects of health risk factors on COVID-19.Sustainable cities and society · 2022Article
- Deep learning modeling of public's sentiments towards temporal evolution of COVID-19 transmission.Applied soft computing · 2022Article
- A visual review of artificial intelligence and Industry 4.0 in healthcare.Computers & electrical engineering : an international journal · 2022Article
- Missing Value Imputation Method for Multiclass Matrix Data Based on Closed Itemset.Entropy (Basel, Switzerland) · 2022Article
- Community public health safety emergency management and nursing insurance service optimization for digital healthy urban environment construction.Frontiers in public health · 2022Article
- Identification of sampling points for the detection of SARS-CoV-2 in the sewage system.Sustainable cities and society · 2022Article
- Tweet Analysis for Enhancement of COVID-19 Epidemic Simulation: A Case Study in Japan.Frontiers in public health · 2022Article
- Public Perception Before and After COVID-19 Vaccine Pass for the Unvaccinated to Eat Alone: Social Media Data Analytics.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nowadays, the world is experiencing a pandemic crisis due to the spread of COVID-19, a novel coronavirus disease. The contamination rate and death cases are expeditiously increasing. Simultaneously, people are no longer relying on traditional news channels to enlighten themselves about the epidemic situation. Alternately, smart cities citizens are relying more on Social Network Service (SNS) to follow the latest news and information regarding the outbreak, share their opinions, and express their feelings and symptoms. In this paper, we propose an SNS Big Data Analysis Framework for COVID-19 Outbreak Prediction in Smart Sustainable Healthy City, where Twitter platform is adopted. Over 10000 Tweets were collected during two months, 38% of users aged between 18 and 29, while 26% are between 30 and 49 years old. 56% of them are males and 44% are females. The geospatial location is USA, and the used language is English. Natural Language Processing (NLP) is deployed to filter the tweets. Results demonstrated an outbreak cluster predicted seven days earlier than the confirmed cases with an indicator of 0.989. Analyzing data from SNS platforms enabled predicting future outbreaks several days earlier, and scientifically reduce the infection rate in a smart sustainable healthy city environment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.