Abstract
Music and singers are influential in local society. An in-depth study on singers is beneficial to various sectors. However, the evolutional characteristic and the daunting complexity of the interrelationship among singers made the problem technically intriguing. In this paper, we present a novel commentary-based social network analysis (CBSNA) methodology to analyze the singer relationships. Developing weighting schemes and adopting k-nearest-neighbors (kNN) approach from network theory as a visualization technique, we simplify the resulting dense network to ease understanding and further investigations. Proof-of-concept experiments are conducted by using two popular datasets to verify the effectiveness of the proposed approach and the empirical results are promising.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2010 |
| Editors | Orland Hoeber, Yuefeng Li, Xangji Jimmy Huang |
| Publisher | IEEE |
| Pages | 9-12 |
| Number of pages | 4 |
| ISBN (Electronic) | 9780769541914 |
| ISBN (Print) | 9781424484829 |
| DOIs | |
| Publication status | Published - 31 Aug 2010 |
| Event | 2010 3rd IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2010 - Toronto, ON, Canada Duration: 31 Aug 2010 → 3 Sept 2010 |
Publication series
| Name | Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT |
|---|---|
| Publisher | IEEE |
Conference
| Conference | 2010 3rd IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2010 |
|---|---|
| Country/Territory | Canada |
| City | Toronto, ON |
| Period | 31/08/10 → 3/09/10 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
User-Defined Keywords
- Network construction
- Social network analysis
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