Sentiment analysis using deep learning architectures: a review
Social media is a powerful source of communication among people to share their sentiments
in the form of opinions and views about any topic or article, which results in an enormous …
in the form of opinions and views about any topic or article, which results in an enormous …
Social media for intelligent public information and warning in disasters: An interdisciplinary review
Social media offers participatory and collaborative structure and collective knowledge
building capacity to the public information and warning approaches. Therefore, the author …
building capacity to the public information and warning approaches. Therefore, the author …
[HTML][HTML] Twitter discussions and emotions about the COVID-19 pandemic: Machine learning approach
Background It is important to measure the public response to the COVID-19 pandemic.
Twitter is an important data source for infodemiology studies involving public response …
Twitter is an important data source for infodemiology studies involving public response …
Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter
The study aims to understand Twitter users' discourse and psychological reactions to COVID-
19. We use machine learning techniques to analyze about 1.9 million Tweets (written in …
19. We use machine learning techniques to analyze about 1.9 million Tweets (written in …
VictimFinder: Harvesting rescue requests in disaster response from social media with BERT
Social media platforms are playing increasingly critical roles in disaster response and
rescue operations. During emergencies, users can post rescue requests along with their …
rescue operations. During emergencies, users can post rescue requests along with their …
Social media data analytics to improve supply chain management in food industries
This paper proposes a big-data analytics-based approach that considers social media
(Twitter) data for the identification of supply chain management issues in food industries. In …
(Twitter) data for the identification of supply chain management issues in food industries. In …
Sentiment analysis of customers' reviews using a hybrid evolutionary SVM-based approach in an imbalanced data distribution
Online media has an increasing presence on the restaurants' activities through social media
websites, coinciding with an increase in customers' reviews of these restaurants. These …
websites, coinciding with an increase in customers' reviews of these restaurants. These …
Using AI and social media multimodal content for disaster response and management: Opportunities, challenges, and future directions
Abstract People increasingly use Social Media (SM) platforms such as Twitter and Facebook
during disasters and emergencies to post situational updates including reports of injured or …
during disasters and emergencies to post situational updates including reports of injured or …
[HTML][HTML] Real-time social media sentiment analysis for rapid impact assessment of floods
L Bryan-Smith, J Godsall, F George, K Egode… - Computers & …, 2023 - Elsevier
Traditional approaches to flood modelling mostly rely on hydrodynamic physical simulations.
While these simulations can be accurate, they are computationally expensive and …
While these simulations can be accurate, they are computationally expensive and …
[HTML][HTML] A roadmap for the future of crowd safety research and practice: Introducing the Swiss Cheese Model of Crowd Safety and the imperative of a Vision Zero …
M Haghani, M Coughlan, B Crabb, A Dierickx… - Safety science, 2023 - Elsevier
Crowds can be subject to intrinsic and extrinsic sources of risk, and previous records have
shown that, in the absence of adequate safety measures, these sources of risk can …
shown that, in the absence of adequate safety measures, these sources of risk can …