Abstract
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.
| Original language | English |
|---|---|
| Article number | 45 |
| Journal | Frontiers in Artificial Intelligence |
| Volume | 3 |
| DOIs | |
| Publication status | Published - 02.07.2020 |
Funding
This work was funded by the State of North Rhine-Westphalia, Germany under the grant number 005-1709-0006, project Digitale Mündigkei and project number 1706dgn017.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 4 Quality Education
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SDG 8 Decent Work and Economic Growth
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 11 Sustainable Cities and Communities
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SDG 13 Climate Action
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SDG 16 Peace, Justice and Strong Institutions
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