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Volumn 51, Issue 1, 2018, Pages

Analysis of online social network connections for identification of influential users: Survey and open research issues

Author keywords

Big data; Complex networks; Identification algorithms; Influential users; OSNs; Social media

Indexed keywords

BIG DATA; COMPLEX NETWORKS; ONLINE SYSTEMS; SURVEYS; VIRUSES; WEBSITES;

EID: 85042495487     PISSN: 03600300     EISSN: 15577341     Source Type: Journal    
DOI: 10.1145/3155897     Document Type: Article
Times cited : (102)

References (198)
  • 2
    • 85003986559 scopus 로고    scopus 로고
    • Identification of influential spreaders in online social networks using interaction weighted K-core decomposition method
    • M. A. Al-Garadi, K. D. Varathan, and S. D. Ravana. 2017. Identification of influential spreaders in online social networks using interaction weighted K-core decomposition method. Physica A: Statistical Mechanics and its Applications 468, 278–288.
    • (2017) Physica A: Statistical Mechanics and Its Applications , vol.468 , pp. 278-288
    • Al-Garadi, M.A.1    Varathan, K.D.2    Ravana, S.D.3
  • 4
    • 0034721164 scopus 로고    scopus 로고
    • Error and attack tolerance of complex networks
    • R. Albert, H. Jeong, and A.-L. Barabási. 2000. Error and attack tolerance of complex networks. Nature 406, 378–382.
    • (2000) Nature , vol.406 , pp. 378-382
    • Albert, R.1    Jeong, H.2    Barabási, A.-L.3
  • 8
    • 84866156151 scopus 로고    scopus 로고
    • Social science: Poked to vote
    • S. Aral. 2012. Social science: Poked to vote. Nature 489, 212–214.
    • (2012) Nature , vol.489 , pp. 212-214
    • Aral, S.1
  • 9
    • 85006024667 scopus 로고    scopus 로고
    • Engineering social contagions: Optimal network seeding in the presence of homophily
    • S. Aral, L. Muchnik, and A. Sundararajan. 2013. Engineering social contagions: Optimal network seeding in the presence of homophily. Network Science 1, 125–153.
    • (2013) Network Science , vol.1 , pp. 125-153
    • Aral, S.1    Muchnik, L.2    Sundararajan, A.3
  • 10
    • 84863993298 scopus 로고    scopus 로고
    • Identifying influential and susceptible members of social networks
    • S. Aral and D. Walker. 2012. Identifying influential and susceptible members of social networks. Science 337, 337–341.
    • (2012) Science , vol.337 , pp. 337-341
    • Aral, S.1    Walker, D.2
  • 13
    • 0038483826 scopus 로고    scopus 로고
    • Emergence of scaling in random networks
    • A.-L. Barabási and R. Albert. 1999. Emergence of scaling in random networks. Science 286, 509–512.
    • (1999) Science , vol.286 , pp. 509-512
    • Barabási, A.-L.1    Albert, R.2
  • 15
    • 84898954996 scopus 로고    scopus 로고
    • Structural measures for multiplex networks
    • F. Battiston, V. Nicosia, and V. Latora. 2014. Structural measures for multiplex networks. Physical Review E 89, 032804.
    • (2014) Physical Review E , vol.89 , pp. 032804
    • Battiston, F.1    Nicosia, V.2    Latora, V.3
  • 16
    • 84926486486 scopus 로고
    • Communication patterns in task-oriented groups
    • 1950
    • A. Bavelas. 1950. Communication patterns in task-oriented groups. Journal of the Acoustical Society of America. 22, 6 (1950), 725–730.
    • (1950) Journal of The Acoustical Society of America , vol.22 , Issue.6 , pp. 725-730
    • Bavelas, A.1
  • 19
    • 35148833196 scopus 로고    scopus 로고
    • Some unique properties of eigenvector centrality
    • P. Bonacich. 2007. Some unique properties of eigenvector centrality. Social Networks 29, 555–564.
    • (2007) Social Networks , vol.29 , pp. 555-564
    • Bonacich, P.1
  • 21
    • 33746192198 scopus 로고    scopus 로고
    • A graph-theoretic perspective on centrality
    • S. P. Borgatti and M. G. Everett. 2006. A graph-theoretic perspective on centrality. Social Networks 28, 466–484.
    • (2006) Social Networks , vol.28 , pp. 466-484
    • Borgatti, S.P.1    Everett, M.G.2
  • 22
    • 84857764370 scopus 로고    scopus 로고
    • Absence of influential spreaders in rumor dynamics
    • J. Borge-Holthoefer and Y. Moreno. 2012. Absence of influential spreaders in rumor dynamics. Physical Review E 85, 026116.
    • (2012) Physical Review E , vol.85 , pp. 026116
    • Borge-Holthoefer, J.1    Moreno, Y.2
  • 24
    • 0035648637 scopus 로고    scopus 로고
    • A faster algorithm for betweenness centrality
    • U. Brandes. 2001. A faster algorithm for betweenness centrality*. Journal of Mathematical Sociology 25, 163–177.
    • (2001) Journal of Mathematical Sociology , vol.25 , pp. 163-177
    • Brandes, U.1
  • 25
    • 84870444130 scopus 로고    scopus 로고
    • Reprint of: The anatomy of a large-scale hypertextual web search engine
    • S. Brin and L. Page. 2012. Reprint of: The anatomy of a large-scale hypertextual web search engine. Computer Networks 56, 3825–3833.
    • (2012) Computer Networks , vol.56 , pp. 3825-3833
    • Brin, S.1    Page, L.2
  • 28
    • 38949109629 scopus 로고    scopus 로고
    • Complex contagions and the weakness of long ties
    • D. Centola and M. Macy. 2007. Complex contagions and the weakness of long ties. American Journal of Sociology 113, 702–734.
    • (2007) American Journal of Sociology , vol.113 , pp. 702-734
    • Centola, D.1    Macy, M.2
  • 30
    • 84890768200 scopus 로고    scopus 로고
    • Measuring user influence in twitter: The million follower fallacy
    • M. Cha, H. Haddadi, F. Benevenuto, and P. K. Gummadi. 2010. Measuring user influence in Twitter: The million follower fallacy. Icwsm, 10, 30.
    • (2010) Icwsm , vol.10 , pp. 30
    • Cha, M.1    Haddadi, H.2    Benevenuto, F.3    Gummadi, P.K.4
  • 31
    • 84928485387 scopus 로고    scopus 로고
    • ACQR: A novel framework to identify and predict influential users in microblogging
    • W. Chai, W. Xu, M. Zuo, and X. Wen. 2013. ACQR: A novel framework to identify and predict influential users in microblogging. PACIS. 20.
    • (2013) PACIS , vol.20
    • Chai, W.1    Xu, W.2    Zuo, M.3    Wen, X.4
  • 33
    • 84906259033 scopus 로고    scopus 로고
    • Predicting the evolution of spreading on complex networks
    • D.-B. Chen, R. Xiao, and A. Zeng. 2014. Predicting the evolution of spreading on complex networks. Scientific Reports 4, 6108. DOI:10.1038/srep06108.
    • (2014) Scientific Reports , vol.4 , pp. 6108
    • Chen, D.-B.1    Xiao, R.2    Zeng, A.3
  • 40
    • 85042468376 scopus 로고    scopus 로고
    • 2017
    • S. Cobb. 2017. RoT: Ransomware of Things. cdn2-prodint.esetstatic.com 2017. https://cdn2prodint.esetstatic.com/ESET/US/Newsroom/2017/03/ESET_Trends-and-Prediction_2017_Ransomware.pdf.
    • (2017) RoT: Ransomware of Things
    • Cobb, S.1
  • 42
    • 81555203120 scopus 로고    scopus 로고
    • Identifying the starting point of a spreading process in complex networks
    • C. H. Comin and L. Da Fontoura Costa. 2011. Identifying the starting point of a spreading process in complex networks. Physical Review E 84, 056105.
    • (2011) Physical Review E , vol.84 , pp. 056105
    • Comin, C.H.1    Da Fontoura Costa, L.2
  • 47
  • 48
    • 33750736202 scopus 로고    scopus 로고
    • Mining social networks for viral marketing
    • P. Domingos. 2005. Mining social networks for viral marketing. IEEE Intelligent Systems, 20, 80–82.
    • (2005) IEEE Intelligent Systems , vol.20 , pp. 80-82
    • Domingos, P.1
  • 49
    • 84867539048 scopus 로고    scopus 로고
    • A few useful things to know about machine learning
    • P. Domingos. 2012. A few useful things to know about machine learning. Communications of the ACM 55, 78–87.
    • (2012) Communications of The ACM , vol.55 , pp. 78-87
    • Domingos, P.1
  • 52
    • 84861833360 scopus 로고    scopus 로고
    • Using social media to build community disaster resilience
    • N. Dufty. 2012. Using social media to build community disaster resilience. Australian Journal of Emergency Management 27, 40.
    • (2012) Australian Journal of Emergency Management , vol.27 , pp. 40
    • Dufty, N.1
  • 55
    • 0031116726 scopus 로고    scopus 로고
    • Centrality in affiliation networks
    • K. Faust. 1997. Centrality in affiliation networks. Social Networks 19, 157–191.
    • (1997) Social Networks , vol.19 , pp. 157-191
    • Faust, K.1
  • 59
    • 84865730611 scopus 로고
    • A set of measures of centrality based on betweenness
    • L. C. Freeman. 1977. A set of measures of centrality based on betweenness. Sociometry 35–41.
    • (1977) Sociometry , pp. 35-41
    • Freeman, L.C.1
  • 60
    • 33750177351 scopus 로고
    • Centrality in social networks conceptual clarification
    • L. C. Freeman. 1979. Centrality in social networks conceptual clarification. Social Networks 1, 215–239.
    • (1979) Social Networks , vol.1 , pp. 215-239
    • Freeman, L.C.1
  • 61
    • 79955073428 scopus 로고    scopus 로고
    • Network immunization and virus propagation in email networks: Experimental evaluation and analysis
    • C. Gao, J. Liu, and N. Zhong. 2011a. Network immunization and virus propagation in email networks: experimental evaluation and analysis. Knowledge and Information Systems 27, 253–279.
    • (2011) Knowledge and Information Systems , vol.27 , pp. 253-279
    • Gao, C.1    Liu, J.2    Zhong, N.3
  • 63
    • 79959545846 scopus 로고    scopus 로고
    • Harnessing the crowdsourcing power of social media for disaster relief
    • H. Gao, G. Barbier, and R. Goolsby. 2011c. Harnessing the crowdsourcing power of social media for disaster relief. IEEE Intelligent Systems 26, 10–14.
    • (2011) IEEE Intelligent Systems , vol.26 , pp. 10-14
    • Gao, H.1    Barbier, G.2    Goolsby, R.3
  • 64
    • 84865790046 scopus 로고    scopus 로고
    • A k-shell decomposition method for weighted networks
    • A. Garas, F. Schweitzer, and S. Havlin. 2012. A k-shell decomposition method for weighted networks. New Journal of Physics 14, 083030.
    • (2012) New Journal of Physics , vol.14 , pp. 083030
    • Garas, A.1    Schweitzer, F.2    Havlin, S.3
  • 67
    • 80053589695 scopus 로고    scopus 로고
    • Ranking stability and super-stable nodes in complex networks
    • G. Ghoshal and A.-L. Barabási. 2011. Ranking stability and super-stable nodes in complex networks. Nature Communications 2, 394.
    • (2011) Nature Communications , vol.2 , pp. 394
    • Ghoshal, G.1    Barabási, A.-L.2
  • 77
    • 84887422995 scopus 로고    scopus 로고
    • Information diffusion in online social networks: A survey
    • A. Guille, H. Hacid, C. Favre, and D. A. Zighed. 2013. Information diffusion in online social networks: A survey. ACM SIGMOD Record 42, 17–28.
    • (2013) ACM SIGMOD Record , vol.42 , pp. 17-28
    • Guille, A.1    Hacid, H.2    Favre, C.3    Zighed, D.A.4
  • 78
  • 81
    • 0034486891 scopus 로고    scopus 로고
    • The mathematics of infectious diseases
    • H. W. Hethcote. 2000. The mathematics of infectious diseases. SIAM Review 42, 599–653.
    • (2000) SIAM Review , vol.42 , pp. 599-653
    • Hethcote, H.W.1
  • 82
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • G. E. Hinton, S. Osindero, and Y.-W. Teh. 2006. A fast learning algorithm for deep belief nets. Neural Computation 18, 1527–1554.
    • (2006) Neural Computation , vol.18 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.-W.3
  • 83
    • 77955274269 scopus 로고    scopus 로고
    • Viral marketing: Motivations to forward online content
    • J. Y. Ho and M. Dempsey. 2010. Viral marketing: Motivations to forward online content. Journal of Business Research 63, 1000–1006.
    • (2010) Journal of Business Research , vol.63 , pp. 1000-1006
    • Ho, J.Y.1    Dempsey, M.2
  • 84
    • 72449167636 scopus 로고    scopus 로고
    • Security issues and recommendations for online social networks
    • G. Hogben. 2007. Security issues and recommendations for online social networks. ENISA Position Paper.
    • (2007) ENISA Position Paper
    • Hogben, G.1
  • 86
    • 84862273647 scopus 로고    scopus 로고
    • Validity issues in the use of social network analysis with digital trace data
    • J. Howison and A. Wiggins. 2011. Validity issues in the use of social network analysis with digital trace data Journal of the Association for Information Systems 12, 767–797.
    • (2011) Journal of The Association for Information Systems , vol.12 , pp. 767-797
    • Howison, J.1    Wiggins, A.2
  • 88
    • 68649108167 scopus 로고    scopus 로고
    • Impact of human activity patterns on the dynamics of information diffusion
    • J. L. Iribarren and E. Moro. 2009. Impact of human activity patterns on the dynamics of information diffusion. Physical Review Letters 103, 038702.
    • (2009) Physical Review Letters , vol.103 , pp. 038702
    • Iribarren, J.L.1    Moro, E.2
  • 89
    • 84867512125 scopus 로고    scopus 로고
    • Active microbloggers: Identifying influencers, leaders and discussers in microblogging networks
    • Springer
    • L. B. Jabeur, L. Tamine, and M. Boughanem. 2012. Active microbloggers: Identifying influencers, leaders and discussers in microblogging networks. In String Processing and Information Retrieval. Springer, 111–117.
    • (2012) String Processing and Information Retrieval , pp. 111-117
    • Jabeur, L.B.1    Tamine, L.2    Boughanem, M.3
  • 93
    • 84874432228 scopus 로고    scopus 로고
    • Analysis of social networking sites: A study on effective communication strategy in developing brand communication
    • P. S. Jothi, M. Neelamalar, and R. S. Prasad. 2011. Analysis of social networking sites: A study on effective communication strategy in developing brand communication. Journal of Media and Communication Studies 3, 234.
    • (2011) Journal of Media and Communication Studies , vol.3 , pp. 234
    • Jothi, P.S.1    Neelamalar, M.2    Prasad, R.S.3
  • 96
    • 0002827622 scopus 로고
    • A new status index derived from sociometric analysis
    • L. Katz. 1953. A new status index derived from sociometric analysis. Psychometrika 18, 39–43.
    • (1953) Psychometrika , vol.18 , pp. 39-43
    • Katz, L.1
  • 98
    • 85015168531 scopus 로고    scopus 로고
    • Virtual community detection through the association between prime nodes in online social networks and its application to ranking algorithms
    • M. S. Khan, A. W. A. Wahab, T. Herawan, G. Mujtaba, S. Danjuma, and M. A. Al-Garadi. 2016a. Virtual community detection through the association between prime nodes in online social networks and its application to ranking algorithms. IEEE Access 4, 9614–9624.
    • (2016) IEEE Access , vol.4 , pp. 9614-9624
    • Khan, M.S.1    Wahab, A.W.A.2    Herawan, T.3    Mujtaba, G.4    Danjuma, S.5    Al-Garadi, M.A.6
  • 101
  • 103
    • 33745841483 scopus 로고    scopus 로고
    • Efficient parallel computation of PageRank
    • Springer
    • C. Kohlschütter, P.-A. Chirita, and W. Nejdl. 2006. Efficient parallel computation of PageRank. ECIR, 2006. Springer, 241–252.
    • (2006) ECIR , vol.2006 , pp. 241-252
    • Kohlschütter, C.1    Chirita, P.-A.2    Nejdl, W.3
  • 106
    • 67349254527 scopus 로고    scopus 로고
    • The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption
    • S. Kulviwat, G. C. Bruner, and O. AL-Shuridah. 2009. The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption. Journal of Business Research 62, 706–712.
    • (2009) Journal of Business Research , vol.62 , pp. 706-712
    • Kulviwat, S.1    Bruner, G.C.2    AL-Shuridah, O.3
  • 109
    • 84924043785 scopus 로고    scopus 로고
    • Understanding the influence of all nodes in a network
    • G. Lawyer. 2015. Understanding the influence of all nodes in a network. Scientific Reports 5, 8665. DOI:10.1038/srep08665
    • (2015) Scientific Reports , vol.5 , pp. 8665
    • Lawyer, G.1
  • 110
    • 84890653327 scopus 로고    scopus 로고
    • Information contagion: An empirical study of the spread of news on digg and twitter social networks
    • K. Lerman and R. Ghosh. 2010. Information contagion: An empirical study of the spread of news on digg and Twitter social networks. ICWSM 10, 90–97.
    • (2010) ICWSM , vol.10 , pp. 90-97
    • Lerman, K.1    Ghosh, R.2
  • 115
  • 120
    • 84908208162 scopus 로고    scopus 로고
    • Identifying domain-dependent influential microblog users: A post-feature based approach
    • N. Liu, L. Li, G. XU, and Z. Yang. 2014. Identifying domain-dependent influential microblog users: A post-feature based approach. In 28th AAAI Conference on Artificial Intelligence, 2014.
    • (2014) 28th AAAI Conference on Artificial Intelligence , vol.2014
    • Liu, N.1    Li, L.2    Xu, G.3    Yang, Z.4
  • 121
    • 79955879494 scopus 로고    scopus 로고
    • Controllability of complex networks
    • Y.-Y. Liu, J.-J. Slotine, and A.-L. Barabási. 2011. Controllability of complex networks. Nature 473, 167–173.
    • (2011) Nature , vol.473 , pp. 167-173
    • Liu, Y.-Y.1    Slotine, J.-J.2    Barabási, A.-L.3
  • 122
    • 84929191771 scopus 로고    scopus 로고
    • Core-like groups result in invalidation of identifying super-spreader by k-shell decomposition
    • Y. Liu, M. Tang, T. Zhou, and Y. Do. 2015a. Core-like groups result in invalidation of identifying super-spreader by k-shell decomposition. Scientific Reports 5, 9602. DOI:10.1038/srep09602
    • (2015) Scientific Reports , vol.5 , pp. 9602
    • Liu, Y.1    Tang, M.2    Zhou, T.3    Do, Y.4
  • 125
    • 79959575935 scopus 로고    scopus 로고
    • Leaders in social networks, the delicious case
    • L. Lü, Y.-C. Zhang, C. H. Yeung, and T. Zhou. 2011. Leaders in social networks, the delicious case. PloS One 6, e21202.
    • (2011) PloS One , vol.6 , pp. e21202
    • Lü, L.1    Zhang, Y.-C.2    Yeung, C.H.3    Zhou, T.4
  • 127
    • 85018327321 scopus 로고    scopus 로고
    • Seeking powerful information initial spreaders in online social networks: A dense group perspective
    • S. Ma, G. Chen, L. Fu, W. Wu, X. Tian, J. Zhao, and X. Wang. 2017. Seeking powerful information initial spreaders in online social networks: A dense group perspective. Wireless Networks 1–19. https://doi.org/10.1007/s11276-017-1478-1.
    • (2017) Wireless Networks , pp. 1-19
    • Ma, S.1    Chen, G.2    Fu, L.3    Wu, W.4    Tian, X.5    Zhao, J.6    Wang, X.7
  • 128
    • 84946888056 scopus 로고    scopus 로고
    • Ranking nodes in growing networks: When PageRank fails
    • M. S. Mariani, M. Medo, and Y.-C. Zhang. 2015. Ranking nodes in growing networks: When PageRank fails. Scientific Reports 5, 16181. DOI:10.1038/srep16181
    • (2015) Scientific Reports , vol.5 , pp. 16181
    • Mariani, M.S.1    Medo, M.2    Zhang, Y.-C.3
  • 132
    • 84938769668 scopus 로고    scopus 로고
    • Influence maximization in complex networks through optimal percolation
    • F. Morone and H. A. Makse. 2015. Influence maximization in complex networks through optimal percolation. Nature 524, 65–68.
    • (2015) Nature , vol.524 , pp. 65-68
    • Morone, F.1    Makse, H.A.2
  • 133
    • 84979556440 scopus 로고    scopus 로고
    • Collective influence algorithm to find influencers via optimal percolation in massively large social media
    • F. Morone, B. Min, L. Bo, R. Mari, and H. A. Makse. 2016. Collective Influence algorithm to find influencers via optimal percolation in massively large social media. Scientific Reports 6, 30062. DOI:10.1038/srep30062
    • (2016) Scientific Reports , vol.6 , pp. 30062
    • Morone, F.1    Min, B.2    Bo, L.3    Mari, R.4    Makse, H.A.5
  • 134
    • 84877734662 scopus 로고    scopus 로고
    • Origins of power-law degree distribution in the heterogeneity of human activity in social networks
    • L. Muchnik, S. Pei, L. C. Parra, S. D. Reis, J. S. Andrade Jr., S. Havlin, and H. A. Makse. 2013. Origins of power-law degree distribution in the heterogeneity of human activity in social networks. Scientific Reports 3, 1783. DOI:10.1038/srep01783
    • (2013) Scientific Reports , vol.3 , pp. 1783
    • Muchnik, L.1    Pei, S.2    Parra, L.C.3    Reis, S.D.4    Andrade, J.S.5    Havlin, S.6    Makse, H.A.7
  • 135
    • 84863449762 scopus 로고    scopus 로고
    • Controlling edge dynamics in complex networks
    • T. Nepusz and T. Vicsek. 2012. Controlling edge dynamics in complex networks. Nature Physics 8, 568–573.
    • (2012) Nature Physics , vol.8 , pp. 568-573
    • Nepusz, T.1    Vicsek, T.2
  • 140
    • 84903996783 scopus 로고    scopus 로고
    • Searching for superspreaders of information in real-world social media
    • S. Pei, L. Muchnik, J. S. Andrade Jr., Z. Zheng, and H. A. Makse. 2014. Searching for superspreaders of information in real-world social media. Scientific Reports, 4, 5547.
    • (2014) Scientific Reports , vol.4 , pp. 5547
    • Pei, S.1    Muchnik, L.2    Andrade, J.S.3    Zheng, Z.4    Makse, H.A.5
  • 143
    • 84916910047 scopus 로고    scopus 로고
    • A framework for validating the merit of properties that predict the influence of a twitter user
    • S. Räbiger and M. Spiliopoulou. 2015. A framework for validating the merit of properties that predict the influence of a Twitter user. Expert Systems with Applications 42, 2824–2834.
    • (2015) Expert Systems with Applications , vol.42 , pp. 2824-2834
    • Räbiger, S.1    Spiliopoulou, M.2
  • 144
    • 79951778842 scopus 로고    scopus 로고
    • Who is the best player ever? A complex network analysis of the history of professional tennis
    • F. Radicchi. 2011. Who is the best player ever? A complex network analysis of the history of professional tennis. PloS One 6, e17249.
    • (2011) PloS One , vol.6 , pp. e17249
    • Radicchi, F.1
  • 145
    • 84977263449 scopus 로고    scopus 로고
    • Leveraging percolation theory to single out influential spreaders in networks
    • F. Radicchi and C. Castellano. 2016. Leveraging percolation theory to single out influential spreaders in networks. Physical Review E 93, 062314.
    • (2016) Physical Review E , vol.93 , pp. 062314
    • Radicchi, F.1    Castellano, C.2
  • 150
    • 84856698456 scopus 로고    scopus 로고
    • Efficient discovery of influential nodes for SIS models in social networks
    • K. Saito, M. Kimura, K. Ohara, and H. Motoda. 2012. Efficient discovery of influential nodes for SIS models in social networks. Knowledge and Information Systems 30, 613–635.
    • (2012) Knowledge and Information Systems , vol.30 , pp. 613-635
    • Saito, K.1    Kimura, M.2    Ohara, K.3    Motoda, H.4
  • 152
    • 85016562928 scopus 로고    scopus 로고
    • Efficient collective influence maximization in cascading processes with first-order transitions
    • X. T. Sen Pei, J. Shaman, F. Morone, and H. A. Makse. 2017. Efficient collective influence maximization in cascading processes with first-order transitions. Scientific Reports 7, 45240. DOI:10.1038/srep45240
    • (2017) Scientific Reports , vol.7 , pp. 45240
    • Sen Pei, X.T.1    Shaman, J.2    Morone, F.3    Makse, H.A.4
  • 153
    • 85018977435 scopus 로고    scopus 로고
    • Identification of multi-spreader users in social networks for viral marketing
    • A. Sheikhahmadi and M. A. Nematbakhsh. 2017. Identification of multi-spreader users in social networks for viral marketing. Journal of Information Science 43, 412–423.
    • (2017) Journal of Information Science , vol.43 , pp. 412-423
    • Sheikhahmadi, A.1    Nematbakhsh, M.A.2
  • 155
    • 84881357427 scopus 로고    scopus 로고
    • Threshold-limited spreading in social networks with multiple initiators
    • P. Singh, S. Sreenivasan, B. K. Szymanski, and G. Korniss. 2013. Threshold-limited spreading in social networks with multiple initiators. Scientific Reports 3, 2330. DOI:10.1038/srep02330
    • (2013) Scientific Reports , vol.3 , pp. 2330
    • Singh, P.1    Sreenivasan, S.2    Szymanski, B.K.3    Korniss, G.4
  • 159
    • 84874479541 scopus 로고    scopus 로고
    • Social media and political communication: A social media analytics framework
    • S. Stieglitz and L. Dang-Xuan. 2013. Social media and political communication: A social media analytics framework. Social Network Analysis and Mining 3, 1277–1291.
    • (2013) Social Network Analysis and Mining , vol.3 , pp. 1277-1291
    • Stieglitz, S.1    Dang-Xuan, L.2
  • 160
    • 0035826155 scopus 로고    scopus 로고
    • Exploring complex networks
    • S. H. Strogatz. 2001. Exploring complex networks. Nature 410, 268–276.
    • (2001) Nature , vol.410 , pp. 268-276
    • Strogatz, S.H.1
  • 161
    • 33749999452 scopus 로고    scopus 로고
    • Knowledge-sharing and influence in online social networks via viral marketing
    • M. R. Subramani and B. Rajagopalan. 2003. Knowledge-sharing and influence in online social networks via viral marketing. Communications of the ACM 46, 300–307.
    • (2003) Communications of The ACM , vol.46 , pp. 300-307
    • Subramani, M.R.1    Rajagopalan, B.2
  • 162
    • 84907921332 scopus 로고    scopus 로고
    • The association of suicide-related twitter use with suicidal behaviour: A cross-sectional study of young internet users in Japan
    • H. Sueki. 2015. The association of suicide-related Twitter use with suicidal behaviour: A cross-sectional study of young Internet users in Japan. Journal of Affective Disorders 170, 155–160.
    • (2015) Journal of Affective Disorders , vol.170 , pp. 155-160
    • Sueki, H.1
  • 166
    • 84992646534 scopus 로고    scopus 로고
    • Collective influence of multiple spreaders evaluated by tracing real information flow in large-scale social networks
    • X. Teng, S. Pei, F. Morone, and H. A. Makse. 2016. Collective influence of multiple spreaders evaluated by tracing real information flow in large-scale social networks. Scientific Reports 6, 36043. DOI:10.1038/srep36043
    • (2016) Scientific Reports , vol.6 , pp. 36043
    • Teng, X.1    Pei, S.2    Morone, F.3    Makse, H.A.4
  • 167
    • 79955720045 scopus 로고    scopus 로고
    • Retrieved December 7, 2017 from
    • D. Tunkelang. 2009. A Twitter analog to PageRank. Retrieved December 7, 2017 from http://thenoisychannel.com/2009/01/13/a-twitter-analog-to-PageRank.
    • (2009) A Twitter Analog to PageRank
    • Tunkelang, D.1
  • 171
    • 36749044180 scopus 로고    scopus 로고
    • Influentials, networks, and public opinion formation
    • D. J. Watts and P. S. Dodds. 2007. Influentials, networks, and public opinion formation. Journal of Consumer Research 34, 441–458.
    • (2007) Journal of Consumer Research , vol.34 , pp. 441-458
    • Watts, D.J.1    Dodds, P.S.2
  • 178
    • 84983048319 scopus 로고    scopus 로고
    • Effectively identifying the influential spreaders in large-scale social networks
    • Y. Xia, X. Ren, Z. Peng, J. Zhang, and L. She. 2016. Effectively identifying the influential spreaders in large-scale social networks. Multimedia Tools Applications 75, 8829–8841.
    • (2016) Multimedia Tools Applications , vol.75 , pp. 8829-8841
    • Xia, Y.1    Ren, X.2    Peng, Z.3    Zhang, J.4    She, L.5
  • 180
    • 84885920886 scopus 로고    scopus 로고
    • Predicting user influence in social media
    • C. Xiao, Y. Zhang, X. Zeng and Y. Wu. 2013. Predicting user influence in social media. Journal of Networks 8, 2649–2655.
    • (2013) Journal of Networks , vol.8 , pp. 2649-2655
    • Xiao, C.1    Zhang, Y.2    Zeng, X.3    Wu, Y.4
  • 183
    • 85040768049 scopus 로고    scopus 로고
    • Identifying opinion leader nodes in online social networks with a new closeness evaluation algorithm
    • L. Yang, Y. Qiao, Z. Liu, J. Ma, and X. Li. 2016. Identifying opinion leader nodes in online social networks with a new closeness evaluation algorithm. Soft Computing 1–12. https://doi.org/10.1007/s00500-016-2335-3.
    • (2016) Soft Computing , pp. 1-12
    • Yang, L.1    Qiao, Y.2    Liu, Z.3    Ma, J.4    Li, X.5
  • 184
    • 84939502615 scopus 로고    scopus 로고
    • An immunization strategy for social network worms based on network vertex influence
    • W. Yang, H. Wang, and Y. Yao. 2015. An immunization strategy for social network worms based on network vertex influence. Communications, China 12, 154–166.
    • (2015) Communications, China , vol.12 , pp. 154-166
    • Yang, W.1    Wang, H.2    Yao, Y.3
  • 185
    • 78650516347 scopus 로고    scopus 로고
    • Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake
    • D. Yates and S. Paquette. 2011. Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake. International Journal of Information Management 31, 6–13.
    • (2011) International Journal of Information Management , vol.31 , pp. 6-13
    • Yates, D.1    Paquette, S.2
  • 190
    • 84875220788 scopus 로고    scopus 로고
    • Ranking spreaders by decomposing complex networks
    • A. Zeng and C.-J. Zhang. 2013. Ranking spreaders by decomposing complex networks. Physics Letters A 377, 1031–1035.
    • (2013) Physics Letters A , vol.377 , pp. 1031-1035
    • Zeng, A.1    Zhang, C.-J.2
  • 191
    • 84994121036 scopus 로고    scopus 로고
    • Dynamics of information diffusion and its applications on complex networks
    • Z.-K. Zhang, C. Liu, X.-X. Zhan, X. Lu, C.-X. Zhang, and Y.-C. Zhang. 2016. Dynamics of information diffusion and its applications on complex networks. Physics Reports 651, 1–34.
    • (2016) Physics Reports , vol.651 , pp. 1-34
    • Zhang, Z.-K.1    Liu, C.2    Zhan, X.-X.3    Lu, X.4    Zhang, C.-X.5    Zhang, Y.-C.6
  • 192
    • 85007009687 scopus 로고    scopus 로고
    • Leader identification in an online health community for cancer survivors: A social network-based classification approach
    • K. Zhao, G. E. Greer, J. Yen, P. Mitra, and K. Portier. 2014a. Leader identification in an online health community for cancer survivors: a social network-based classification approach. Information Systems and e-Business Management 1–17.
    • (2014) Information Systems and E-Business Management , pp. 1-17
    • Zhao, K.1    Greer, G.E.2    Yen, J.3    Mitra, P.4    Portier, K.5
  • 196
    • 84878015841 scopus 로고    scopus 로고
    • Discovering the influential users oriented to viral marketing based on online social networks
    • Z. Zhu. 2013. Discovering the influential users oriented to viral marketing based on online social networks. Physica A: Statistical Mechanics and its Applications 392, 3459–3469.
    • (2013) Physica A: Statistical Mechanics and Its Applications , vol.392 , pp. 3459-3469
    • Zhu, Z.1
  • 198
    • 34248995311 scopus 로고    scopus 로고
    • Modeling and simulation study of the propagation and defense of internet e-mail worms
    • C. C. Zou, D. Towsley, and W. Gong. 2007. Modeling and simulation study of the propagation and defense of Internet e-mail worms. IEEE Transactions on Dependable and Secure Computing 4, 105–118.
    • (2007) IEEE Transactions on Dependable and Secure Computing , vol.4 , pp. 105-118
    • Zou, C.C.1    Towsley, D.2    Gong, W.3


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