Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.
@article{Fernando:2020:10.1016/j.future.2019.10.013,
author = {Fernando, S and AmadorDíazLópez, J and erban, O and Gómez-Romero, J and Molina-Solana, M and Guo, Y},
doi = {10.1016/j.future.2019.10.013},
journal = {Future Generation Computer Systems},
pages = {976--983},
title = {Towards a large-scale twitter observatory for political events},
url = {http://dx.doi.org/10.1016/j.future.2019.10.013},
volume = {110},
year = {2020}
}
TY - JOUR
AB - Explosion in usage of social media has made its analysis a relevant topic of interest, and particularly so in the political science area. Within Data Science, no other techniques are more widely accepted and appealing than visualisation. However, with datasets growing in size, visualisation tools also require a paradigm shift to remain useful in big data contexts. This work presents our proposal for a Large-Scale Twitter Observatory that enables researchers to efficiently retrieve, analyse and visualise data from this social network to gain actionable insights and knowledge related with political events. In addition to describing the supporting technologies, we put forward a working pipeline and validate the setup with different examples.
AU - Fernando,S
AU - AmadorDíazLópez,J
AU - erban,O
AU - Gómez-Romero,J
AU - Molina-Solana,M
AU - Guo,Y
DO - 10.1016/j.future.2019.10.013
EP - 983
PY - 2020///
SN - 0167-739X
SP - 976
TI - Towards a large-scale twitter observatory for political events
T2 - Future Generation Computer Systems
UR - http://dx.doi.org/10.1016/j.future.2019.10.013
UR - https://www.sciencedirect.com/science/article/pii/S0167739X19309720?via%3Dihub
UR - http://hdl.handle.net/10044/1/74658
VL - 110
ER -