Machine learning techniques for hate speech classification of twitter data: State-of-the-art, future challenges and research directions

FE Ayo, O Folorunso, FT Ibharalu, IA Osinuga - Computer Science Review, 2020 - Elsevier
Twitter is a microblogging tool that allow the creation of big data through short digital
contents. This study provides a survey of machine learning techniques for hate speech …

The role of explainable Artificial Intelligence in high-stakes decision-making systems: a systematic review

B Sahoh, A Choksuriwong - Journal of Ambient Intelligence and …, 2023 - Springer
A high-stakes event is an extreme risk with a low probability of occurring, but severe
consequences (eg, life-threatening conditions or economic collapse). The accompanying …

Design and analysis of a large-scale COVID-19 tweets dataset

R Lamsal - applied intelligence, 2021 - Springer
Abstract As of July 17, 2020, more than thirteen million people have been diagnosed with
the Novel Coronavirus (COVID-19), and half a million people have already lost their lives …

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 …

HAN, image captioning, and forensics ensemble multimodal fake news detection

P Meel, DK Vishwakarma - Information Sciences, 2021 - Elsevier
Nowadays, news publication, propagation, and consumption have been diverted to online
social media networks and web portals, which has given rise to falsified and fabricated news …

Multimodal tweet classification in disaster response systems using transformer-based bidirectional attention model

R Koshy, S Elango - Neural Computing and Applications, 2023 - Springer
The goal of this research is to use social media to gain situational awareness in the wake of
a crisis. With the developments in information and communication technologies, social …

[HTML][HTML] Improving crisis events detection using distilbert with hunger games search algorithm

H Adel, A Dahou, A Mabrouk, M Abd Elaziz, M Kayed… - Mathematics, 2022 - mdpi.com
This paper presents an alternative event detection model based on the integration between
the DistilBERT and a new meta-heuristic technique named the Hunger Games Search …

Extracting the location of flooding events in urban systems and analyzing the semantic risk using social sensing data

Y Zhang, Z Chen, X Zheng, N Chen, Y Wang - Journal of Hydrology, 2021 - Elsevier
The aggregation of the same type of socio-economic activities in urban space generates
urban functional zones, each of which has one function as the main (eg, residential …

Humaid: Human-annotated disaster incidents data from twitter with deep learning benchmarks

F Alam, U Qazi, M Imran, F Ofli - … of the International AAAI Conference on …, 2021 - ojs.aaai.org
Social networks are widely used for information consumption and dissemination, especially
during time-critical events such as natural disasters. Despite its significantly large volume …

Exploring the potential of social media crowdsourcing for post-earthquake damage assessment

L Li, M Bensi, G Baecher - International Journal of Disaster Risk Reduction, 2023 - Elsevier
Following disaster events, a significant hindrance to emergency response is a lack of
information on the spatial extent and severity of damages. Social media crowdsourcing has …