GazPNE2: A general place name extractor for microblogs fusing gazetteers and pretrained transformer models
The concept of “human as sensors” defines a new sensing model, in which humans act as
sensors by contributing their observations, perceptions, and sensations. This is crucial for …
sensors by contributing their observations, perceptions, and sensations. This is crucial for …
GazPNE: annotation-free deep learning for place name extraction from microblogs leveraging gazetteer and synthetic data by rules
Extracting precise location information from microblogs is a crucial task in many
applications, particularly in disaster response, revealing where damages are, where people …
applications, particularly in disaster response, revealing where damages are, where people …
Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages
Social media messages posted by people during natural disasters often contain important
location descriptions, such as the locations of victims. Recent research has shown that many …
location descriptions, such as the locations of victims. Recent research has shown that many …
Geo-spatial text-mining from Twitter–a feature space analysis with a view toward building classification in urban regions
By the year 2050, it is expected that about 68% of global population will live in cities. To
understand the emerging changes in urban structures, new data sources like social media …
understand the emerging changes in urban structures, new data sources like social media …
Face off: Travel Habits, Road Conditions and Traffic City Characteristics Bared Using Twitter
A Agarwal, D Toshniwal - IEEE Access, 2019 - ieeexplore.ieee.org
The adequacy of traditional transport related issues detection is often limited by physical
sparse sensor coverage and reporting incident/issues to the emergency response system is …
sparse sensor coverage and reporting incident/issues to the emergency response system is …
Location name extraction from targeted text streams using gazetteer-based statistical language models
Extracting location names from informal and unstructured social media data requires the
identification of referent boundaries and partitioning compound names. Variability …
identification of referent boundaries and partitioning compound names. Variability …
An approximate model for event detection from twitter data
A Dhiman, D Toshniwal - IEEE Access, 2020 - ieeexplore.ieee.org
The abundance and real-time availability of Twitter data have proved beneficial in detecting
events in various domains such as emergency situations, crime detection, public health …
events in various domains such as emergency situations, crime detection, public health …
Microblog dimensionality reduction—a deep learning approach
Exploring potentially useful information from huge amount of textual data produced by
microblogging services has attracted much attention in recent years. An important …
microblogging services has attracted much attention in recent years. An important …
How do people describe locations during a natural disaster: an analysis of tweets from Hurricane Harvey
Y Hu, J Wang - arXiv preprint arXiv:2009.12914, 2020 - arxiv.org
Social media platforms, such as Twitter, have been increasingly used by people during
natural disasters to share information and request for help. Hurricane Harvey was a category …
natural disasters to share information and request for help. Hurricane Harvey was a category …
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 …