Locations, eg, countries, states, cities, and point-of-interests, are central to news, emergency
events, and people's daily lives. Automatic identification of locations associated with or …

Social media user geolocation is vital to many applications such as event detection. In this
paper, we propose GCN, a multiview geolocation model based on Graph Convolutional …

Geographical locations of microblog users are essential for user profiling, event localization
and target advertising, to name a few. Automatic identification of user locations from the …

Public health thrives on high-quality evidence, yet acquiring meaningful data on a
population remains a central challenge of public health research and practice. Social …

The COVID-19 pandemic has exposed the world's population to unprecedented health
threats and changes to social life. High uncertainty about the novel disease and its social …

We propose a simple yet effective text-based user geolocation model based on a neural
network with one hidden layer, which achieves state of the art performance over three …

We propose a label propagation approach to geolocation prediction based on Modified
Adsorption, with two enhancements:(1) the removal of" celebrity" nodes to increase location …

We propose a novel geolocation prediction model using a complex neural network.
Geolocation prediction in social media has attracted many researchers to use information of …

Automated geolocation of social media messages can benefit a variety of downstream
applications. However, these geolocation systems are typically evaluated without attention …

Much research has shown that social media platforms have substantial population biases.
However, very little is known about how these population biases affect the many algorithms …