All Outputs (2)

Predicting the environment from social media: A collective classification approach (2020)
Journal Article
Jeawak, S. S., Jones, C. B., & Schockaert, S. (2020). Predicting the environment from social media: A collective classification approach. Computers, Environment and Urban Systems, 82, https://doi.org/10.1016/j.compenvurbsys.2020.101487

We propose a method which uses Flickr tags to predict a wide variety of environmental features, such as climate data, land cover categories, species occurrence, and human assessments of scenicness. The role of Flickr tags in our method is two-fold. F... Read More about Predicting the environment from social media: A collective classification approach.

Predicting environmental features by learning spatiotemporal embeddings from social media (2019)
Journal Article
Jeawak, S. S., Jones, C. B., & Schockaert, S. (2020). Predicting environmental features by learning spatiotemporal embeddings from social media. Ecological Informatics, 55, https://doi.org/10.1016/j.ecoinf.2019.101031

Spatiotemporal modelling is an important task for ecology. Social media tags have been found to have great potential to assist in predicting aspects of the natural environment, particularly through the use of machine learning methods. Here we propose... Read More about Predicting environmental features by learning spatiotemporal embeddings from social media.