Online Information Review (OIR) is an international, double blind peer-reviewed, SSCI-listed journal devoted to research in the broad field of digital information and communication, and related technologies.

The journal provides a multi-disciplinary forum for scholars from a range of fields, including information studies/iSchools, data studies, internet studies, media and communication studies and information systems.

We are particularly interested in publishing research on the social, political and ethical aspects of emergent digital information practices and platforms, and welcome submissions that draw upon critical and socio-technical perspectives in order to address these developments. 

We welcome empirical, conceptual and methodological contributions on any topics relevant to the broad field of digital information and communication, however we are particularly interested in receiving submissions that address emerging issues around the below topics.

Coverage includes (but is not limited to):

    Online communities, social networking and social media, including online political communication; crowdsourcing; positive computing and wellbeing.
    The social drivers and implications of emerging data practices, including open data; big data; data journeys and flows; and research data management.
    Digital transformations including organisations’ use of information technologies (e.g. Internet of Things and digitisation of user experience) to improve economic and social welfare, health and wellbeing, and protect the environment.
    Developments in digital scholarship and the production and use of scholarly content.
    Online and digital research methods, including their ethical aspects

 Generally these types of submissions are rejected:  

    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