পদ্ধতির তুলনা করুন

	পরিচালিত নেটওয়ার্ক বিস্তার বিশ্লেষণ	সমাজ নেটওয়ার্ক বিশ্লেষণ
ক্ষেত্র	নেটওয়ার্ক বিশ্লেষণ	নেটওয়ার্ক বিশ্লেষণ
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	2003 (influence maximization formalization); epidemic models traced to Kermack & McKendrick, 1927	1934 (sociometry); 1994 (modern formalization)
প্রবর্তক	Kempe, D.; Kleinberg, J.; Tardos, E. (influence maximization); Pastor-Satorras, R. et al. (epidemic spreading)	Moreno, J.L.; formalized by Wasserman & Faust
ধরন	Network spreading and cascade analysis	Structural/relational analysis framework
মৌলিক উৎস	Kempe, D., Kleinberg, J., & Tardos, E. (2003). Maximizing the spread of influence through a social network. Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 137–146.	Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
অপর নাম	directed diffusion model, information spreading on directed networks, directed cascade analysis, directed influence propagation	SNA, network analysis, sociometric analysis, relational analysis
সম্পর্কিত	6	5
সারসংক্ষেপ	Directed network diffusion analysis studies how information, disease, behavior, or influence spreads through a network in which edges carry direction — meaning transmission flows one way along each link. It combines graph-theoretic representations with stochastic spreading models such as independent cascade, linear threshold, or SIR/SIS, and is central to influence maximization, epidemic forecasting, and information propagation research.	Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system.