Deep Learning for Social Network Information Cascade Analysis: a survey
| العنوان: | Deep Learning for Social Network Information Cascade Analysis: a survey |
|---|---|
| المؤلفون: | Haiyang Wang, Bin Zhou, Ye Wang, Tu Hongkui, Chen Chenguang, Hongwu Zhuang, Yan Jia, Liqun Gao |
| المصدر: | DSC |
| بيانات النشر: | IEEE, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | 0209 industrial biotechnology, Social network, business.industry, Computer science, Process (engineering), Deep learning, Feature extraction, Information Dissemination, 02 engineering and technology, 01 natural sciences, Data science, 020901 industrial engineering & automation, 0103 physical sciences, Data analysis, Artificial intelligence, Information cascade, business, 010301 acoustics, Social network analysis |
| الوصف: | The phenomenon of information dissemination in social networks is widespread, and Social Network Information Cascade Analysis (SNICA) aims to acquire valuable knowledge in the process of information dissemination in social networks. As the number, volume, and resolution of social network data increase rapidly, traditional social network data analysis methods, especially the analysis method of social network graph (SNG) data becoming overwhelmed in SNICA. Recently, deep learning models have changed this situation, and it has achieved success in SNICA with its powerful implicit feature extraction capabilities. In this paper, we provide a comprehensive survey of recent progress in applying deep learning techniques for SNICA. We first introduce related concepts and summarize the advantages of deep learning technology in SNICA. Then, we propose a general framework for deep learning technology, which applies to SNICA. Then, different SNICA application scenarios in the framework are classified and discussed according to user behavior analysis, information cascade analysis, rumor detection, and social network event analysis. Finally, we discuss the limitations of current work and suggest future directions. |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::276ca5ea18880abb01ff8077dacd47fa https://doi.org/10.1109/dsc50466.2020.00022 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........276ca5ea18880abb01ff8077dacd47fa |
| قاعدة البيانات: | OpenAIRE |
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