TY - GEN
T1 - Distorting Political Communication
T2 - 2019 INFOCOM IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019
AU - Papakyriakopoulos, Orestis
AU - Shahrezaye, Morteza
AU - Serrano, Juan Carlos Medina
AU - Hegelich, Simon
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - Online Social Networks (OSNs) are used increasingly for political purposes. Among others, politicians externalize their views on issues, and users respond to them, initiating political discussions. Part of the discussions are shaped by hyperactive users. These are users that are over-proportionally active in relation to the mean. In this paper, we define the hyperactive user on the social media platform Facebook, both theoretically and mathematically. We apply a geometric topic modelling algorithm (GTM) on German political parties' posts and user comments to identify the topics discussed. We prove that hyperactive users have a significant role in the political discourse: They become opinion leaders, as well as set the content of discussions, thus creating an alternate picture of the public opinion. Given that, we discuss the dangers of replicating the specific bias by statistical and deep learning algorithms, which are used widely for recommendation systems and the profiling of OSN users.
AB - Online Social Networks (OSNs) are used increasingly for political purposes. Among others, politicians externalize their views on issues, and users respond to them, initiating political discussions. Part of the discussions are shaped by hyperactive users. These are users that are over-proportionally active in relation to the mean. In this paper, we define the hyperactive user on the social media platform Facebook, both theoretically and mathematically. We apply a geometric topic modelling algorithm (GTM) on German political parties' posts and user comments to identify the topics discussed. We prove that hyperactive users have a significant role in the political discourse: They become opinion leaders, as well as set the content of discussions, thus creating an alternate picture of the public opinion. Given that, we discuss the dangers of replicating the specific bias by statistical and deep learning algorithms, which are used widely for recommendation systems and the profiling of OSN users.
UR - http://www.scopus.com/inward/record.url?scp=85073232587&partnerID=8YFLogxK
U2 - 10.1109/INFCOMW.2019.8845094
DO - 10.1109/INFCOMW.2019.8845094
M3 - Conference contribution
AN - SCOPUS:85073232587
T3 - INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019
SP - 157
EP - 164
BT - INFOCOM 2019 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 April 2019 through 2 May 2019
ER -