Activity: Talk or presentation › Talk or presentation at a conference
Betweenness is one of the most popular centrality measures in the analysis of social networks. Its computation has a high cost making it implausible for relatively large networks. The dynamic nature of many social networks opens up the possibility of developing faster algorithms for the dynamic version of the problem. In this work, we propose a new decremental algorithm to compute betweenness centrality of all nodes in directed graphs extracted from social networks. Our algorithm uses linear space, making it suitable for large scale applications. The experimental evaluation on a variety of real-world networks has shown our algorithm is faster than recalculation from scratch and competitive with recent approaches.
28 Jun 2019 → 30 Jun 2019
2nd International Scientific Convention: Workshop 2019 on Internet of Things and Artificial Intelligence