Special Issue on Social Media Analytics

Introduction

Social media have become ubiquitous and are playing an increasingly critical role in society. The wide use of social media platforms has generated massive user-generated contents (UGCs). To leverage these UGCs, it is important for organisations to develop capability in collecting, storing and analysing social media data for the purpose of harvesting information and actionable knowledge for decision making and forecasting.

As one consequence of these developments, social media analytics has emerged as an important area of study. Social media analytics is concerned with using advanced informatics tools and analytics techniques to collect, monitor, and analyse social media data to extract useful patterns and intelligence. Therefore, the development of effective and efficient analytics techniques for social media analytics becomes essential. To conduct social media analytics, data mining, text analysis and sentiment analysis techniques are frequently adopted. Recently there has been strong interest in the power of social media analytics in creating new value, supporting decision-making and enhancing competitive advantage.

As social media analytics is a young and emerging interdisciplinary research topic, limited studies have been devoted to unveiling the value, impact and implications of social media analytics for the management and use of online information. Accordingly, the primary goal of this special issue of Online Information Review is to showcase cutting-edge research advances in social media analytics in order to provide a landscape of recent research progress and novel applications, techniques and strategies in analysing online information posted on various social media platforms. This special issue solicits high-quality innovative papers related to social media analytics to unveiling the value, impact and implications of social media analytics for the management and use of online information.

Topics of interest include (but are not limited to):

• Novel applications of social media analytics
• Novel techniques, methods and strategies for analysing social media data
• Social media analytics and business value
• Social media analytics and privacy
• Social media analytics and human behavior
• Search in social networks and social media
• Community detection and evolution
• Knowledge discovery (collective wisdom, trend analysis and topic detection)
• Analysis of different forms of user-generated content in the online context
• Social reputation and recommendation systems

Dr Wu He
Department of Information Technology & Decision Sciences
College of Business and Public Administration
Old Dominion University, Norfolk, VA 23529 whe@odu.edu

Dr Guandong Xu
Advanced Analytics Institute
University of Technology Sydney, Australia
Guandong.Xu@uts.edu.au

Please feel free to contact either Guest Editor if you have questions or queries about the issue or submissions.

Important Dates:

• Papers due: 1 Jun 2015
• First round decisions made: 15 Jul 2015
• Revised manuscript due: 30 Aug 2015
• Final decisions made: 1 Oct 2015
• Publication: OIR Vol 40, no 1 (2016)

Submissions:

Every submission must spell out the implications of findings in the paper for online information as distinct from implications for e-commerce, education, etc. (These implications should be mentioned in the introduction, discussion and conclusion sections of your paper.) Papers which focus on findings for specific sectors without adequate attention to the online environment will not be accepted.

There are several types of submissions that OIR generally rejects:

• Papers that require mathematics to develop, test or analyse concepts or findings (these require non-mathematical explanations for the readership of OIR)
• Questionnaire-based studies based on convenience samples that expand previous studies only moderately (these should focus on a new topic, and argue convincingly that convenience sampling is necessary, to be acceptable)
• TAM or other standard model-based submissions applied in a formulaic way to a limited population and which do not significantly advance our knowledge of the topic

Prospective authors should ensure their papers meet the Special Issue scope and must adhere to the author guidelines. For further information, please go to

http://www.emeraldinsight.com/loi/oir.

All papers must be submitted online. Submissions to Online Information Review are made using ScholarOne Manuscripts, the online submission and peer review system. Registration and access is available at http://mc.manuscriptcentral.com/oir. Full information and guidance on using ScholarOne Manuscripts is available at the Emerald ScholarOne Manuscripts Support Centre: http://msc.emeraldinsight.com.

About the Journal:

Online Information Review is an international, double blind peer-reviewed, ISI-listed (2013 Impact Factor is 1.443) 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, go to

http://www.emeraldinsight.com/loi/oir

 

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