Towards Social Big Data-Based Affective Group Recommendation
- Authors
- Hong, Minsung; Jung, Jason J.
- Issue Date
- Aug-2018
- Publisher
- SPRINGER
- Keywords
- Social big data; Social influence; Emotional contagion; Conformity; Group recommendation
- Citation
- MOBILE NETWORKS & APPLICATIONS, v.23, no.4, pp 1111 - 1122
- Pages
- 12
- Journal Title
- MOBILE NETWORKS & APPLICATIONS
- Volume
- 23
- Number
- 4
- Start Page
- 1111
- End Page
- 1122
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/18691
- DOI
- 10.1007/s11036-018-1076-1
- ISSN
- 1383-469X
1572-8153
- Abstract
- Social big data is currently an emergent issue, especially for recommender systems. In particular, with respect to social big data, various data mining techniques have been applied in group recommender systems. However, three social phenomena (i.e., social influence, emotional contagion, and conformity) have not been applied enough in existing studies. In this paper, a novel method for a group recommendation is proposed based upon the affective social network from social big data. In this regard, to explore and measure the social phenomena, a variety of similarity measures were applied in a content-based recommendation. Moreover, the proposed method has a computational complexity of O(N (2)), where N is the number of users in a group. Therefore, it is appropriate for big data environments, since the N is generally small for user groups. This study's results revealed that the Mahalanobis distance was suitable for the affective group recommendation. Moreover, the proposed method outperformed the other group recommender systems, those with large groups.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/18691)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.