Abstract
Decision-making in many application domains needs to take into consideration of some sorts of networks. Examples include e-commerce and marketing [6, 10], strategic planning [21], knowledge management [12], and Web mining [5, 13]. Since the late 1990s a large number of articles have been published in Nature, Science, and other leading journals in many disciplines, proposing new network models, techniques, and applications (e.g., [3, 22, 25]). This trend has been accompanied by the increasing popularity of social networking sites such as FaceBook and MySpace. As a result, research on social network data mining, or simply network mining, has attracted much attention from both academics and practitioners.
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Acknowldgements
The editors would like to gratefully acknowledge the efforts of all those who have helped create this special edition. First, it would never be possible for an edition such as this one to provide such a broad and extensive look at the latest research in the field of social network mining without the efforts of all those expert researchers and practitioners who have authored and contributed papers. Their contributions made this special issue possible. In addition, we would like to thank the reviewers for their time and effort in the preparation of their thoughtful reviews. Their support was crucial for ensuring the quality of this special issue and for attracting wide readership. oreover, we would like to thank the series editors, Ramesh Sharda and Stefan Voß, for their valuable advice, support, and encouragement. We are also grateful for the pleasant cooperation with Neil Levine and Matthew Amboy from Springer and their professional support in publishing this volume.
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Memon, N., Xu, J.J., Hicks, D.L., Chen, H. (2010). Social Network Data Mining: Research Questions, Techniques, and Applications. In: Memon, N., Xu, J., Hicks, D., Chen, H. (eds) Data Mining for Social Network Data. Annals of Information Systems, vol 12. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6287-4_1
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