On relational learning and discovery in social networks: a survey

Zhang, Ji and Tan, Leonard and Tao, Xiaohui (2018) On relational learning and discovery in social networks: a survey. International Journal of Machine Learning and Cybernetics. ISSN 1868-8071

Abstract

The social networking scene has evolved tremendously over the years. It has grown in relational complexities that extend a vast presence onto popular social media platforms on the internet. With the advance of sentimental computing and social complexity, relationships which were once thought to be simple have now become multi-dimensional and widespread in the online scene. This explosion in the online social scene has attracted much research attention. The main aims of this work revolve around the knowledge discovery and datamining processes of these feature-rich relations. In this paper, we provide a survey of relational learning and discovery through popular social analysis of different structure types which are integral to applications within the emerging field of sentimental and affective computing. It is hoped that this contribution will add to the clarity of how social networks are analyzed with the latest groundbreaking methods and provide certain directions for future improvements.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published online: 17 May 2018. Accepted version embargoed until 1 June 2019 (12 months), in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 18 Feb 2019 02:57
Last Modified: 19 Feb 2019 01:43
Uncontrolled Keywords: online social networks; social internetworking scenarios; homogeneous networks; heterogeneous networks; hybrid networks; multi-dimensional relational learning
Fields of Research : 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0802 Computation Theory and Mathematics > 080299 Computation Theory and Mathematics not elsewhere classified
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080107 Natural Language Processing
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080108 Neural, Evolutionary and Fuzzy Computation
Socio-Economic Objective: B Economic Development > 91 Economic Framework > 9199 Other Economic Framework > 919999 Economic Framework not elsewhere classified
C Society > 92 Health > 9299 Other Health > 929999 Health not elsewhere classified
C Society > 95 Cultural Understanding > 9599 Other Cultural Understanding > 959999 Cultural Understanding not elsewhere classified
B Economic Development > 89 Information and Communication Services > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified
D Environment > 96 Environment > 9699 Other Environment > 969999 Environment not elsewhere classified
A Defence > 81 Defence > 8101 Defence > 810199 Defence not elsewhere classified
Identification Number or DOI: 10.1007/s13042-018-0823-8
URI: http://eprints.usq.edu.au/id/eprint/35856

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