Sentiment analysis using deep learning architectures: a review

A Yadav, DK Vishwakarma - Artificial Intelligence Review, 2020 - Springer
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 …

Social media for intelligent public information and warning in disasters: An interdisciplinary review

C Zhang, C Fan, W Yao, X Hu, A Mostafavi - International Journal of …, 2019 - Elsevier
Social media offers participatory and collaborative structure and collective knowledge
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

J Xue, J Chen, R Hu, C Chen, C Zheng, Y Su… - Journal of medical …, 2020 - jmir.org
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 …

Public discourse and sentiment during the COVID 19 pandemic: Using Latent Dirichlet Allocation for topic modeling on Twitter

J Xue, J Chen, C Chen, C Zheng, S Li, T Zhu - PloS one, 2020 - journals.plos.org
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 …

VictimFinder: Harvesting rescue requests in disaster response from social media with BERT

B Zhou, L Zou, A Mostafavi, B Lin, M Yang… - … Environment and Urban …, 2022 - Elsevier
Social media platforms are playing increasingly critical roles in disaster response and
rescue operations. During emergencies, users can post rescue requests along with their …

Social media data analytics to improve supply chain management in food industries

A Singh, N Shukla, N Mishra - … Part E: Logistics and Transportation Review, 2018 - Elsevier
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 …

Sentiment analysis of customers' reviews using a hybrid evolutionary SVM-based approach in an imbalanced data distribution

R Obiedat, R Qaddoura, AZ Ala'M, L Al-Qaisi… - IEEE …, 2022 - ieeexplore.ieee.org
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 …

Using AI and social media multimodal content for disaster response and management: Opportunities, challenges, and future directions

M Imran, F Ofli, D Caragea, A Torralba - Information Processing & …, 2020 - Elsevier
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 …

[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 …

[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 …