On Predicting Geolocation of Tweets using Convolutional Neural Networks
Abstract
In many Twitter studies, it is important to know where a tweet came from in order to use the tweet content to study regional user behavior. However, researchers using Twitter to understand user behavior often lack sufficient geo-tagged data. Given the huge volume of Twitter data there is a need for accurate automated geolocating solutions. Herein, we present a new method to predict a Twitter user's location based on the information in a single tweet. We integrate text and user profile meta-data into a single model using a convolutional neural network. Our experiments demonstrate that our neural model substantially outperforms baseline methods, achieving 52.8% accuracy and 92.1% accuracy on city-level and country-level prediction respectively.
Cite
@article{arxiv.1704.05146,
title = {On Predicting Geolocation of Tweets using Convolutional Neural Networks},
author = {Binxuan Huang and Kathleen M. Carley},
journal= {arXiv preprint arXiv:1704.05146},
year = {2017}
}