The study of (social) structures in real-world networks is known as (social) network analysis. Nodes and linkages make up networks. Communities are subnetworks in which nodes have more connections to nodes within the subnetwork than to nodes outside the subnetwork. The difficulty of detecting nodes in networks that belong to more than one sub-network is known as overlapping community detection. The goal of this work is to extend our existing bot detection framework to include community detection functionality.
Thesis Type |
|
Status |
Cancelled |
Supervisor(s) |
Ralf Klamma |
Advisor(s) |
Michal Slupczynski |
Contact |
slupczynski@dbis.rwth-aachen.de |
If you are interested in this thesis, a related topic or have additional questions, please do not hesitate to send a message to slupczynski@dbis.rwth-aachen.de
Please apply with a meaningful CV and a recent transcript of your academic performance.
- [Abokhodair et al. 2015] Dissecting a Social Botnet: Growth, Content and Influence in Twitter https://doi.org/10.1145/2675133.2675208
- [Bastos et al. 2017] The Brexit Botnet and User-Generated Hyperpartisan News https://doi.org/10.1177/0894439317734157
- [Wang et al. 2017] Botnet detection based on anomaly and community detection https://doi.org/10.1109/TCNS.2016.2532804
- [Lingam et al. 2020] Social Botnet Community Detection: A Novel Approach based on Behavioral Similarity in Twitter Network using Deep Learning https://doi.org/10.1145/3320269.3384770
- [Peng et al. 2021] TCDABCF: A Trust-Based Community Detection Using Artificial Bee Colony by Feature Fusion https://doi.org/10.1155/2021/6675759
- [Samper-Escalante et al. 2021] Bot Datasets on Twitter: Analysis and Challenges https://doi.org/10.3390/app11094105
- Web Technologies
- Java