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{Oehmichen:2019:10.1109/access.2019.2938389,
author = {Oehmichen, A and Hua, K and Lopez, JAD and Molina-Solana, M and Gomez-Romero, J and Guo, Y},
doi = {10.1109/access.2019.2938389},
journal = {IEEE Access},
pages = {126305--126314},
title = {Not all lies are equal. A study into the engineering of political misinformation in the 2016 US presidential election},
url = {http://dx.doi.org/10.1109/access.2019.2938389},
volume = {7},
year = {2019}
}
TY - JOUR
AB - We investigated whether and how political misinformation is engineered using a datasetof four months worth of tweets related to the 2016 presidential election in the United States. The datacontained tweets that achieved a significant level of exposure and was manually labelled into misinformationand regular information. We found that misinformation was produced by accounts that exhibit differentcharacteristics and behaviour from regular accounts. Moreover, the content of misinformation is more novel,polarised and appears to change through coordination. Our findings suggest that engineering of politicalmisinformation seems to exploit human traits such as reciprocity and confirmation bias. We argue thatinvestigating how misinformation is created is essential to understand human biases, diffusion and ultimatelybetter produce public policy.
AU - Oehmichen,A
AU - Hua,K
AU - Lopez,JAD
AU - Molina-Solana,M
AU - Gomez-Romero,J
AU - Guo,Y
DO - 10.1109/access.2019.2938389
EP - 126314
PY - 2019///
SN - 2169-3536
SP - 126305
TI - Not all lies are equal. A study into the engineering of political misinformation in the 2016 US presidential election
T2 - IEEE Access
UR - http://dx.doi.org/10.1109/access.2019.2938389
VL - 7
ER -