IJSNM 2013 - Special Issue on Mining Social Networks for Recommender Systems

Social networks such as Facebook, Linkedin, etc. contain gigabytes of data that can be mined to make recommendations for products, events or even friendships. The premise of these recommendations is that individuals might only be a few steps from a desirable social friend, event or product, but not realise it.
In such systems, people often belong to multiple explicit or implicit social networks because of different interpersonal interactions. That is, besides the explicit friendship relations between the users, there are also other implicit relations. For example, users can co-comment on products and they can co-rate products or co-tag a photo.
The aim of this special issue is to study how mining of social networks can leverage the quality of recommendations. The analysis of social influence and the inference of social rating networks and social media can help in providing more accurate and effective product, friend, activity and event recommendations.
Subject Coverage
Suitable topics include but are not limited to:
Link prediction in social networks
Rating prediction in social rating networks
Recommendation in social rating networks
Cross-domain recommendation in social rating networks
Group recommendation in social networks
Top-N friend recommendation in social networks
Top-N item recommendation in social networks
Recommendation in social networks with distrust
Recommendation in time-evolving social networks
Social network analysis for recommendation
Memory-based methods for recommendation in social networks
Model-based methods for recommendation in social networks
Recommendation by combining multiple social networks
Privacy of recommendation in social networks
Event and activity recommendation in mobile social networks
Recommendation in location-based social networks
Collaborative filtering in social networks
Context-aware recommendation in social networks
Explaining recommendation in social networks
Recommendation in social media
Multi-criteria recommendation in social networks
Notes for Prospective Authors
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper was not originally copyrighted and if it has been completely re-written).
All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page.
Important Dates
Paper submission due: 1 February, 2013
First round notification: 1 May, 2013
Revised version due: 1 August, 2013