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Social Recommender Systems: Impact on individual life and society


Special issue call for papers from Online Information Review

Introduction

Recommender systems (RSs) targeting the social domain have drawn the attention of the research community in recent years because of their significant potential in assisting users to cope with the proliferation of social media. The massive adoption of social applications, including social networks (e.g. Facebook and Twitter), collaborative tagging systems (e.g. Flickr and Delicious) and online communities (e.g. Linkedin and Foursquare), leads to a large volume of user-generated, heterogeneous social media. Finding relevant content, users or other knowledge, and considering also their context (e.g. mobile applications), is a challenging task for existing recommendation approaches.

Techniques in the fields of data and text mining, pattern recognition, behaviour and sentiment analysis and opinion mining, for example, enable more precise recommendations and personalised services. However, several concerns arise in the development of social recommender systems. These concerns include effectively mining multiple and heterogeneous sources of knowledge, modeling not only users but also groups and communities, considering ubiquity and context-awareness of mobile applications, developing infrastructures for supporting social big data, and dealing with security and privacy, among many others.

This special issue seeks contributions focusing on the value, impact and implications of Social Recommender Systems in both the daily activities of individuals and society as a whole. In this context, the articles are expecting to reporting novel methods and applications of Social Recommender Systems at both the theoretical and practical levels.

Researchers are invited to submit papers that illustrate research results, project findings, surveys of the field, and critical analyses of significant advances in the following areas, among others:

  • RSs for online social networks such as Twitter, Facebook, etc.
  • RSs for Collaborative Social Tagging Systems such as Delicious, Flickr, etc.
  • RSs for groups and communities
  • Context-aware social recommendation
  • RSs for location-based social networks
  • Emerging applications of social RSs
  • User interfaces for social RSs
  • Social RSs in the enterprise
  • Evaluation methods and datasets for social RSs
  • Social RSs on the Semantic Web
  • RSs over Big social Data

Guest editors

Daniela Godoy  (Corresponding editor)
ISISTAN (CONICET - UNCPBA)
Tandil, Bs. As., Argentina
Email: daniela.godoy@isistan.unicen.edu.ar

Jason J. Jung
Department of Computer Engineering
Chung-Ang University
Seoul, Republic of Korea
Email: j2jung@gmail.com

Silvia Schiaffino
ISISTAN (CONICET - UNCPBA)
Tandil, Bs. As., Argentina
Email: silvia.schiaffino@isistan.unicen.edu.ar

Important dates

  • First submission papers due: 24 Feb 2017
  • First round decisions made: 15 April 2017
  • Revised manuscripts due: 30 May 2017
  • Final decisions made: 1 July 2017
  • Publication: To be announced

Author Guidelines

Please see our author guidelines for more details and submission instructions. Papers should be submitted via the ScholarOne system in use by Online Information Review. Please be sure to select this special issue option when you submit your paper through ScholarOne.

There are several types of submissions that OIR generally rejects:

  • Papers that require mathematics to develop, test or analyse concepts or findings, where non-mathematical explanations accessible to the readership of OIR are not offered
  • Questionnaire-based studies with low levels of novelty and advance on previous knowledge. Further, if convenience samples are used, their use needs to be convincingly argued.

Prospective authors should ensure their papers meet the Special Issue scope and must adhere to OIR author guidelines. For further information, please go to http://www.emeraldinsight.com/products/journals/journals.htm?id=oir.

All papers must be submitted online. Submissions to Online Information Review are made using ScholarOne Manuscripts, the online submission and peer review system.

Full information and guidance on using ScholarOne Manuscripts is available at the Emerald ScholarOne Manuscripts Support Centre.

About the Journal

Online Information Review is an international, double blind peer-reviewed, ISI-listed (2014 Impact Factor is 0.918) journal devoted to research in the broad field of online information in academic, government, corporate, scientific and commercial contexts. Within this broad framework the journal seeks to provide a forum for experts from a range of information-related disciplines, including information science, information technology, information management, knowledge management and related social sciences.

‘Online information’ encompasses any information that is stored and viewed in electronic form, from e-books to databases, document management systems and any other information-bearing artefacts in electronic format.

OIR focuses on issues relating to online systems, services and resources, and their use, with a particular focus on the processes and procedures involved in creating, managing, utilizing, disseminating and repackaging online information (including social, political and ethical aspects).

For more information on the journal visit the homepage.