arXiv Open Access 2018

Discovering Key Nodes in a Temporal Social Network

Jinshuo Liu Chenghao Mou Donghong Ji

Lihat Sumber

Abstrak

[Background]Discovering key nodes plays a significant role in Social Network Analysis(SNA). Effective and accurate mining of key nodes promotes more successful applications in fields like advertisement and recommendation. [Methods] With focus on the temporal and categorical property of users' actions - when did they re-tweet or reply a message, as well as their social intimacy measured by structural embeddings, we designed a more sensitive PageRank-like algorithm to accommodate the growing and changing social network in the pursue of mining key nodes. [Results] Compared with our baseline PageRank algorithm, key nodes selected by our ranking algorithm noticeably perform better in the SIR disease simulations with SNAP Higgs dataset. [Conclusion] These results contributed to a better understanding of disseminations of social events over the network.

Topik & Kata Kunci

cs.SI physics.soc-ph

Penulis (3)

Jinshuo Liu

Chenghao Mou

Donghong Ji

Format Sitasi

APA MLA BibTeX

Liu, J., Mou, C., Ji, D. (2018). Discovering Key Nodes in a Temporal Social Network. https://arxiv.org/abs/1802.10083

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓