Social network analysis and mining: challenges and applications
Resumo
Social network analysis and mining (SNAM) is a powerful tool to dis- close relevant information hidden in large volumes of raw data. Its application to several research fields, powered by automation and advanced computing infrastructure, expanded its use and brought along new challenges. In this paper, we provide a critical perspective on SNAM’s major challenges, by discussing a few examples. We also address some promising applications that can potentially translate SNAM results into practical knowledge.
Palavras-chave:
social network analysis, challenges, applications, mining
Referências
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Fonseca, B. d. P. F., Fernandes, E., and Fonseca, M. V. A. (2016). Collaboration in science and technology organizations of the public sector: A network perspective. Science and Public Policy, 44(1):37–49.
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Morel, C. M., Serruya, S. J., Penna, G. O., and Guimarães, R. (2009). Co-authorship network analysis: A powerful tool for strategic planning of research, development and capacity building programs on neglected diseases. PLoS Neglected Tropical Diseases, 3(8):e501.
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Vasconcellos, A. G. and Morel, C. M. (2012). Enabling policy planning and innovation management through patent information and co-authorship network analyses: A study of tuberculosis in Brazil. PLoS ONE, 7(10):e45569.
Windzio, M., Teney, C., and Lenkewitz, S. (2021). A network analysis of intra-EU migration flows: how regulatory policies, economic inequalities and the network-topology shape the intra-EU migration space. Journal of Eth- nic and Migration Studies, 47(5):951–969. Publisher: Routledge eprint: https://doi.org/10.1080/1369183X.2019.1643229.
CDC (2020). Cases, Data, and Surveillance.
Cunha, B. R. d. and Gonc ̧alves, S. (2018). Topology, robustness, and structural controlla- bility of the Brazilian Federal Police criminal intelligence network. Applied Network Science, 3(1):1–20. Number: 1 Publisher: SpringerOpen.
Fonseca, B. d. P. F., Fernandes, E., and Fonseca, M. V. A. (2016). Collaboration in science and technology organizations of the public sector: A network perspective. Science and Public Policy, 44(1):37–49.
Fonseca, B. d. P. F. E., Silva, M. V. P. d., Arau ́jo, K. M. d., Sampaio, R. B., and Moraes, M. O. (2017). Network analysis for science and technology management: Evidence from tuberculosis research in Fiocruz, Brazil. PloS One, 12(8):e0181870.
Lee, C.-Y., Chong, H. Y., Liao, P., and Wang, X. (2018). Critical Review of Social Network Analysis Applications in Complex Project Management. Journal of Manage- ment in Engineering, 34(2). Accepted: 2018-02-01T05:24:34Z Publisher: ASCE.
Morel, C. M., Serruya, S. J., Penna, G. O., and Guimarães, R. (2009). Co-authorship network analysis: A powerful tool for strategic planning of research, development and capacity building programs on neglected diseases. PLoS Neglected Tropical Diseases, 3(8):e501.
Vasconcellos, A. G., Fonseca, B. d. P. F. e., and Morel, C. M. (2018). Revisiting the con- cept of Innovative Developing Countries (IDCs) for its relevance to health innovation and neglected tropical diseases and for the prevention and control of epidemics. PLOS Neglected Tropical Diseases, 12(7):e0006469.
Vasconcellos, A. G. and Morel, C. M. (2012). Enabling policy planning and innovation management through patent information and co-authorship network analyses: A study of tuberculosis in Brazil. PLoS ONE, 7(10):e45569.
Windzio, M., Teney, C., and Lenkewitz, S. (2021). A network analysis of intra-EU migration flows: how regulatory policies, economic inequalities and the network-topology shape the intra-EU migration space. Journal of Eth- nic and Migration Studies, 47(5):951–969. Publisher: Routledge eprint: https://doi.org/10.1080/1369183X.2019.1643229.
Publicado
18/07/2021
Como Citar
FONSECA, Bruna P.; ALBUQUERQUE, Priscila C.; ZICKER, Fabio; MOREL, Carlos M..
Social network analysis and mining: challenges and applications. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 10. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 287-294.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2021.16149.
