Community Detection Framework Using Deep Learning in Social Media Analysis
Social media analysis aims to collect and analyze social media user information and communication content. When people communicate through messages, phone calls, emails, and social media platforms, they leave various records on their devices and the Internet, forming a huge social network. Community...
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MDPI AG
2024-12-01
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| author | Ao Shen Kam-Pui Chow |
| author_facet | Ao Shen Kam-Pui Chow |
| author_sort | Ao Shen |
| collection | DOAJ |
| description | Social media analysis aims to collect and analyze social media user information and communication content. When people communicate through messages, phone calls, emails, and social media platforms, they leave various records on their devices and the Internet, forming a huge social network. Community detection can help investigators analyze group leaders and community structure, which is significant to further crime control, identifying coordinated campaigns, and analyzing social network dynamics. This paper proposes the application of deep learning methods for community detection. Our main idea is to utilize social network topology and social network communication content to construct user features. The proposed end-to-end community detection framework is the implementation of Graph Convolution Network and can display the social network topology, locate the core members of the community, and show the connections between users. We evaluate our framework on the Enron email dataset. Experimental results indicate that our proposed model achieves a 1.1% higher modularity score than the unsupervised benchmark methods. We also concluded that the community detection framework should be able to analyze social networks, enabling investigators to reveal connections between people. |
| format | Article |
| id | doaj-art-537a51863a41400b85d1f8fbe678d7e2 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-537a51863a41400b85d1f8fbe678d7e22024-12-27T14:08:14ZengMDPI AGApplied Sciences2076-34172024-12-0114241174510.3390/app142411745Community Detection Framework Using Deep Learning in Social Media AnalysisAo Shen0Kam-Pui Chow1School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai 201209, ChinaDepartment of Computer Science, The University of Hong Kong, Hong Kong, ChinaSocial media analysis aims to collect and analyze social media user information and communication content. When people communicate through messages, phone calls, emails, and social media platforms, they leave various records on their devices and the Internet, forming a huge social network. Community detection can help investigators analyze group leaders and community structure, which is significant to further crime control, identifying coordinated campaigns, and analyzing social network dynamics. This paper proposes the application of deep learning methods for community detection. Our main idea is to utilize social network topology and social network communication content to construct user features. The proposed end-to-end community detection framework is the implementation of Graph Convolution Network and can display the social network topology, locate the core members of the community, and show the connections between users. We evaluate our framework on the Enron email dataset. Experimental results indicate that our proposed model achieves a 1.1% higher modularity score than the unsupervised benchmark methods. We also concluded that the community detection framework should be able to analyze social networks, enabling investigators to reveal connections between people.https://www.mdpi.com/2076-3417/14/24/11745community detectiondeep learningsocial mediadata mining |
| spellingShingle | Ao Shen Kam-Pui Chow Community Detection Framework Using Deep Learning in Social Media Analysis Applied Sciences community detection deep learning social media data mining |
| title | Community Detection Framework Using Deep Learning in Social Media Analysis |
| title_full | Community Detection Framework Using Deep Learning in Social Media Analysis |
| title_fullStr | Community Detection Framework Using Deep Learning in Social Media Analysis |
| title_full_unstemmed | Community Detection Framework Using Deep Learning in Social Media Analysis |
| title_short | Community Detection Framework Using Deep Learning in Social Media Analysis |
| title_sort | community detection framework using deep learning in social media analysis |
| topic | community detection deep learning social media data mining |
| url | https://www.mdpi.com/2076-3417/14/24/11745 |
| work_keys_str_mv | AT aoshen communitydetectionframeworkusingdeeplearninginsocialmediaanalysis AT kampuichow communitydetectionframeworkusingdeeplearninginsocialmediaanalysis |