On Crawling Community-aware Online Social Network Data
Author:
Affiliation:
1. University of California, Santa Barbara, Santa Barbara, CA, USA
2. National Tsing Hua University, Hsinchu, Taiwan Roc
Funder
Ministry of Science and Technology, Taiwan
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3342220.3344937
Reference11 articles.
1. Clique Relaxations in Social Network Analysis: The Maximumk-Plex Problem
2. Efficient influence maximization in social networks
3. Finding maximal cliques in massive networks by H*-graph
4. Effective community search for large attributed graphs
5. Practical Recommendations on Crawling Online Social Networks
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1. Real-Time Focused Extraction of Social Media Users;IEEE Access;2022
2. Diversity-Optimized Group Extraction in Social Networks;IEEE Transactions on Computational Social Systems;2022
3. WMEgo: Willingness Maximization for Ego Network Data Extraction in Online Social Networks;Proceedings of the 29th ACM International Conference on Information & Knowledge Management;2020-10-19
4. CrawlSN: community-aware data acquisition with maximum willingness in online social networks;Data Mining and Knowledge Discovery;2020-09
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