TY - JOUR
T1 - Opinion Formation on the Internet
T2 - The Influence of Personality, Network Structure, and Content on Sharing Messages Online
AU - Burbach, Laura
AU - Halbach, Patrick
AU - Ziefle, Martina
AU - Calero Valdez, André
N1 - Publisher Copyright:
© Copyright © 2020 Burbach, Halbach, Ziefle and Calero Valdez.
PY - 2020/7/2
Y1 - 2020/7/2
N2 - Today the majority of people uses online social networks not only to stay in contact with friends, but also to find information about relevant topics, or to spread information. While a lot of research has been conducted into opinion formation, only little is known about which factors influence whether a user of online social networks disseminates information or not. To answer this question, we created an agent-based model and simulated message spreading in social networks using a latent-process model. In our model, we varied four different content types, six different network types, and we varied between a model that includes a personality model for its agents and one that did not. We found that the network type has only a weak influence on the distribution of content, whereas the message type has a clear influence on how many users receive a message. Using a personality model helped achieved more realistic outcomes.
AB - Today the majority of people uses online social networks not only to stay in contact with friends, but also to find information about relevant topics, or to spread information. While a lot of research has been conducted into opinion formation, only little is known about which factors influence whether a user of online social networks disseminates information or not. To answer this question, we created an agent-based model and simulated message spreading in social networks using a latent-process model. In our model, we varied four different content types, six different network types, and we varied between a model that includes a personality model for its agents and one that did not. We found that the network type has only a weak influence on the distribution of content, whereas the message type has a clear influence on how many users receive a message. Using a personality model helped achieved more realistic outcomes.
UR - http://www.scopus.com/inward/record.url?scp=85117750174&partnerID=8YFLogxK
U2 - 10.3389/frai.2020.00045
DO - 10.3389/frai.2020.00045
M3 - Journal articles
AN - SCOPUS:85117750174
SN - 2624-8212
VL - 3
JO - Frontiers in Artificial Intelligence
JF - Frontiers in Artificial Intelligence
M1 - 45
ER -