Information visualisation for social media analytics
Rozenn Dahyot, Conor Brady, Cyril Bourges, Abdullah Bülbül · 2015
This paper tackles the audio visual renderings of geolocated datasets harvested from social networks. These datasets are noisy, multimodal and heterogeneous by nature, providing different fields of information. We focus here on the information of location (GPS), time (timestamp) and text from tweets from which sentiment is extracted. We provide two ways for visualising datasets and for which demos can be seen online.