পদ্ধতির তুলনা করুন

	সময়ভিত্তিক মধ্যস্থতা কেন্দ্রিকতা	টেম্পোরাল ডিগ্রি সেন্ট্রালিটি
ক্ষেত্র	নেটওয়ার্ক বিশ্লেষণ	নেটওয়ার্ক বিশ্লেষণ
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	2012	2011–2012
প্রবর্তক	Kim, H. & Anderson, R.; Holme, P. & Saramäki, J.	Holme, P.; Saramaki, J.; Kim, H.; Anderson, R.
ধরন	Centrality measure for temporal networks	Centrality measure (temporal extension)
মৌলিক উৎস	Holme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.	Holme, P. & Saramaki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.
অপর নাম	TBC, time-varying betweenness centrality, dynamic betweenness centrality, time-respecting betweenness	time-varying degree centrality, dynamic degree centrality, temporal node degree, TDC
সম্পর্কিত	6	6
সারসংক্ষেপ	Temporal Betweenness Centrality (TBC) extends classical betweenness centrality to time-stamped networks by counting how often a node lies on time-respecting shortest paths — paths that traverse edges in chronological order. It identifies nodes that act as temporal brokers, controlling information or resource flow as it evolves over time, rather than in a static snapshot.	Temporal degree centrality extends the classic degree centrality to time-varying networks by counting how many distinct contacts a node accumulates over time. Rather than collapsing a dynamic network into a single static graph, it preserves the temporal order of edges, yielding a more faithful measure of a node's activity and reachability across the observation window.