Social Approach for Context Analysis: Modelling and Predicting Social Network Evolution using Homophily
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | Modeling and Using Context |
| Subtitle of host publication | 9th International and Interdisciplinary Conference, CONTEXT 2015, Lanarca, Cyprus, Novemer 2-6,2015. Proceedings |
| Publisher | Springer International Publishing |
| Pages | 513-519 |
| Number of pages | 7 |
| ISBN (Electronic) | 978-3-319-25591-0 |
| ISBN (Print) | 978-3-319-25590-3 |
| DOIs | |
| Publication status | Published - 2015 |
| Publication type | A4 Article in a conference publication |
| Event | International and Interdisciplinary Conference on Modeling and Using Context - Duration: 1 Jan 1900 → … |
Publication series
| Name | Lecture Notes in Artificial Intelligence |
|---|---|
| Volume | 9405 |
Conference
| Conference | International and Interdisciplinary Conference on Modeling and Using Context |
|---|---|
| Period | 1/01/00 → … |
Abstract
Understanding the user’s context is important for mobile applications to provide personalized services. Such context is typically based on the user’s own information. In this paper, we show how social network analysis and the study of the individual in a social network can provide meaningful contextual information. According to the phenomenon of homophily, similar users tend to be connected more frequently than dissimilar. We model homophily in social networks over time. Such models strengthen context inference algorithms, which helps determine future status of the user, resulting in prediction accuracy improvements of up to 118% with respect to a naïve classifier.
Keywords
- Social network analysis, Homophily, Context Inference