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Nghiên cứu về các biện pháp trung tâm trong các mạng xã hội: một cuộc khảo sát
Tóm tắt
Mạng xã hội chắc chắn là nơi hữu ích và quan trọng để kết nối mọi người trong thế giới. Một vấn đề cơ bản trong một mạng xã hội là xác định những cá nhân quan trọng trong đó. Đây là lý do mà nhiều biện pháp trung tâm đã được phát hiện trong suốt những năm qua. Trong bài khảo sát này, chúng tôi trình bày các công trình nghiên cứu đã qua và hiện tại về các biện pháp trung tâm trong mạng xã hội. Để thực hiện kế hoạch này, chúng tôi thảo luận về các định nghĩa toán học và các biện pháp trung tâm khác nhau đã được phát triển. Chúng tôi cũng trình bày một số ứng dụng của các biện pháp trung tâm trong sinh học, nghiên cứu, an ninh, giao thông, vận tải, dược phẩm, và lớp học. Cuối cùng, chúng tôi đưa ra công trình nghiên cứu tương lai về biện pháp trung tâm.
Từ khóa
#mạng xã hội #biện pháp trung tâm #ứng dụng #nghiên cứu #an ninh #giao thông #sinh họcTài liệu tham khảo
Bae J, Kim S (2014) Identifying and ranking influential spreaders in complex networks by neighborhood coreness. Phys A 395:549–559
Barrat A et al (2004) The architecture of complex weighted networks. Proc Natl Acad Sci 101(11):3747–3752
Bavelas A (1948) A mathematical model for group structures. Appl Anthropol 7:16–30
Bavelas A (1950) Communication patterns in task oriented groups. J Acoust Soc Am 22:725–730
Beauchamp MA (1965) An improved index of centrality. Behav Sci 10:161–163
Boccaletti S et al (2006) Complex networks: structure and dynamics. Phys Rep 424:175–308
Bonacich P (1972) Factoring and weighing approaches to status scores and clique identification. J Math Sociol 2(1):113–120
Bonacich P (1987) Power and centrality: a family of measures. Am J Sociol 92(5):1170–1182
Bonacich P (2007) Some unique properties of eigenvector centrality. Soc Netw 29:555–564
Bonacich P, Lloyd P (2001) Eigenvector-like measures of centrality for asymmetric relations. Soc Netw 23(3):191–201
Borgatti SP (2006) Identifying sets of key players in a social network. Comput Math Organ Theory 12:21–34
Borgatti SP et al (2009) Network analysis in the social sciences. Sci New Ser 323(5916):892–895
Brandes U (2001) A faster algorithm for betweenness centrality. J Math Sociol 25(2):163–177
Brandes U (2008) On variants of shortest-path betweenness centrality and their generic computation. Soc Netw 302:136–145
Bruun J, Brewe E (2013) Talking and learning physics: predicting future grades from network measures and Force Concept Inventory pretest scores. Phys Rev Phys Educ Res 9:020109
Chen CM (2006) Cite space II: detecting and visualizing emerging trends and transient patterns in scientific literature. J Am Soc Inform Sci Technol 57(3):359377
Coles N (2001) Analyzing serious crime groups as social network. Br J Criminol 41:580–594
Costenbader E, Valente TW (2003) The stability of centrality measures when networks are sampled. Soc Netw 25:283–307
Dijkstra EW (1959) A note on two problems in connexion with graphs. Numer Math 1:269–271
Estrada E, Rodriguez-Velazquez JA (2005) Subgraph centrality in complex networks. Phys Rev 71:056103
Everett MG, Borgatti SP (1999) The centrality of groups and classes. J Math Sociol 23(3):181–201
Fletcher JM, Wennekers T (2017) From structure to activity: using centrality measures to predict neuronal activity. Int J Neural Syst 27:1750013
Freeman LC (1977) A set of measures of centrality based on betweenness. Sociometry 40(1):35–41
Freeman LC (1978) Centrality in social networks conceptual clarification. Soc Netw 1:215–239
Freeman LC, Borgatti SP, White DR (1991) Centrality in valued graphs: a measure of betweenness based on network flow. Soc Netw 13(2):141–154
Garas A, Schweitzer F, Havlin S (2012) A k-shell decomposition method for weighted networks. New J Phys 14:083030
Grunspan DZ, Wiggins BL, Goodreau SM (2014) Understanding classrooms through social network analysis: a primer for social network analysis in education research. CBE Life Sci Educ 13:167–178
Guimera R et al (2005) The worldwide air transportation network: anomalous centrality, community structure, and cities global roles. Proc Natl Acad Sci 102(22):7794–7799
Hage P, Harary F (1995) Eccentricity and centrality in networks. Soc Netw 17:57–63
Holme P (2003) Congestion and centrality in traffic flow on complex networks. Adv Complex Syst 6(2):163–176
Jayaweera IMLN, Perera KKKR, Munasinghe J (2017) Centrality measures to identify traffic congestion on road networks: a case study of Sri Lanka. IOSR J Math 13(2):13–19
Jeong H et al (2001) Lethality and centrality in protein networks. Nature 411(6833):41–42
Joyce KE et al (2010) A new measure of centrality for brain networks. PLoS ONE 5(8):12200
Katz L (1953) A new status index derived from sociometric analysis. Psychometrika 18(1):39–43
Kitsak M et al (2010) Identification of influential spreaders in complex networks. Nat Phys 6(11):888–893
Koschutzki D et al. (2005) Centrality indices. In: Brandes U, Erlebach T (eds.) Network analysis: methodological foundations 3418:16–61
Koschutzki D, Schreiber F (2008) Centrality analysis methods for biological networks and their application to gene regulatory networks. Gene Regul Syst Biol 2:193–201
Koschützki D, Schreiber F (2004) Comparison of centralities for biological networks. German Conf Bioinf 53:199–206
Liu X et al (2005) Co-authorship networks in the digital library research community. Inf Process Manage 41:1462–1480
Liu LG et al (2007) Weighted network properties of Chinese nature science basic research. Phys A Stat Mech Appl 377(1):302–314
Liu JG, Ren ZM, Guo Q (2014) Ranking the spreading influence in complex networks. Phys A 392(18):4154–4159
Liu Y et al (2015) Identify influential spreaders in complex networks: the role of neighborhood. Phys A 452:289–298
Newman MEJ (2001) Scientific collaboration networks I. Network construction and fundamental results. Phys Rev E 64:016131
Newman MEJ (2004) Analysis of weighted networks. Phys Rev E 389:2134–2142
Newman MEJ (2010) Networks: an introduction. Oxford University Press, New York
Nieminen J (1974) On the centrality in a graph. Scand J Psychol 15:322–336
Opsahl T, Panzarasa P (2009) Clustering in weighted networks. Soc Netw 31:155–163
Opsahl T, Agneessens F, Skvoretz J (2010) Node centrality in weighted networks. Generalizing degree and shortest paths. Soc Netw 32(3):245–251
Rhemtulla M et al (2016) Network analysis of substance abuse and dependence symptoms. Drug Alcohol Depend 161:230–237
Rodriguez JA, Estrada E, Gutierrez A (2006) Functional centrality in graphs. Linear Multilinear Algebra 55:293–302
Sabidussi G (1966) The centrality index of a graph. Psychometrika 31(4):581–603
Shaw ME (1954) Group structure and the behavior of individuals in small groups. J Psychol 38:139–149
Shimbel A (1953) Structural parameters of communication networks. Bull Math Biophys 15(4):501–507
Sparrow MK (1991) The application of network analysis to criminal intelligence: an assessment of the prospects. Soc Netw 13(3):251–274
Stephenson K, Zelen M (1989) Rethinking centrality: methods and examples. Soc Netw 11:1–37
Tew KL, Li XL, Tan SH (2007) Functional centrality: detecting lethality of proteins in protein interaction networks. Genome Inform 19:166–177
Wang K and Xiufen F (2017) Research on centrality of urban transport network nodes, AIP Conference Proceedings 1839, 020181
Wang J et al (2017) A novel weight neighborhood centrality algorithm for identifying influential spreaders in complex networks. Phys A S0378–4371(17):30121–30128
White DR, Borgatti SP (1994) Betweenness centrality measures for directed graphs. Soc Netw 16:335–346
Wuchty S, Stadler PF (2003) Centers of complex networks. J Theor Biol 223(1):45–53
Yan E, Ding Y (2009) Applying centrality measures to impact analysis: a co-authorship network analysis. J Am Soc Inform Sci Technol 60(10):2107–2118
Zeng A, Zhang CJ (2013) Ranking spreaders by decomposing complex networks. Phys Lett A 377(14):1031–1035