Producing a unified graph representation from multiple social network views
|Title:||Producing a unified graph representation from multiple social network views||Authors:||Greene, Derek
|Permanent link:||http://hdl.handle.net/10197/5250||Date:||2-May-2013||Abstract:||In many social networks, several different link relations will exist between the same set of users. Additionally, attribute or textual information will be associated with those users, such as demographic details or user-generated content. For many data analysis tasks, such as community finding and data visualisation, the provision of multiple heterogeneous types of user data makes the analysis process more complex. We propose an unsupervised method for integrating multiple data views to produce a single unified graph representation, based on the combination of the k-nearest neighbour sets for users derived from each view. These views can be either relationbased or feature-based. The proposed method is evaluated on a number of annotated multi-view Twitter datasets, where it is shown to support the discovery of the underlying community structure in the data.||Type of material:||Conference Publication||Publisher:||Association for Computing Machinery||Copyright (published version):||ACM, 2013||Keywords:||Data integration; Social network analysis; Social media||DOI:||10.1145/2464464.2464471||Language:||en||Status of Item:||Not peer reviewed||Is part of:||WebSci '13: Proceedings of the 5th Annual ACM Web Science Conference||Conference Details:||5th Annual ACM Web Science Conference (WebSci'13), Paris, May 2-4th, 2013|
|Appears in Collections:||Computer Science Research Collection|
Show full item record
Page view(s) 5067
This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.