Twitter as a tool for the management and analysis of emergency situations: A systematic literature review
The importance of timely, accurate and effective use of available information is essential to
the proper management of emergency situations. In recent years, emerging technologies …
the proper management of emergency situations. In recent years, emerging technologies …
[PDF][PDF] Comparison of word embeddings and sentence encodings as generalized representations for crisis tweet classification tasks
Many machine learning and natural language processing approaches, including supervised
and domain adaptation algorithms, have been proposed and studied in the context of …
and domain adaptation algorithms, have been proposed and studied in the context of …
Development of a national-scale real-time Twitter data mining pipeline for social geodata on the potential impacts of flooding on communities
Social media, particularly Twitter, is increasingly used to improve resilience during extreme
weather events/emergency management situations, including floods: by communicating …
weather events/emergency management situations, including floods: by communicating …
[PDF][PDF] Deep neural networks versus naive bayes classifiers for identifying informative tweets during disasters
Traditional machine learning techniques have shown promising results in automating the
process of identifying useful information in crisis-related data posted through micro-blogging …
process of identifying useful information in crisis-related data posted through micro-blogging …
Detecting perceived emotions in hurricane disasters
Natural disasters (eg, hurricanes) affect millions of people each year, causing widespread
destruction in their wake. People have recently taken to social media websites (eg, Twitter) …
destruction in their wake. People have recently taken to social media websites (eg, Twitter) …
[PDF][PDF] Combining self-training with deep learning for disaster tweet classification
Significant progress has been made towards automated classification of disaster or crisis
related tweets using machine learning approaches. Deep learning models, such as …
related tweets using machine learning approaches. Deep learning models, such as …
A hybrid domain adaptation approach for identifying crisis-relevant tweets
Huge amounts of data generated on social media during emergency situations is regarded
as a trove of critical information. The use of supervised machine learning techniques in the …
as a trove of critical information. The use of supervised machine learning techniques in the …
Infrastructure ombudsman: Mining future failure concerns from structural disaster response
Current research concentrates on studying discussions on social media related to structural
failures to improve disaster response strategies. However, detecting social web posts …
failures to improve disaster response strategies. However, detecting social web posts …
Endea: Ensemble based decoupled adversarial learning for identifying infrastructure damage during disasters
Identifying tweets related to infrastructure damage during a crisis event is an important
problem. However, the unavailability of labeled data during the early stages of a crisis event …
problem. However, the unavailability of labeled data during the early stages of a crisis event …
[PDF][PDF] Classification of Twitter disaster data using a hybrid feature-instance adaptation approach
R Mazloom - 2018 - krex.k-state.edu
Huge amounts of data that are generated on social media during emergency situations are
regarded as troves of critical information. The use of supervised machine learning …
regarded as troves of critical information. The use of supervised machine learning …