Big Data & Society

Scope & Guideline

Connecting Scholars to the Frontiers of Data and Society

Introduction

Delve into the academic richness of Big Data & Society with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN2053-9517
PublisherSAGE PUBLICATIONS INC
Support Open AccessYes
CountryUnited Kingdom
TypeJournal
Convergefrom 2014 to 2024
AbbreviationBIG DATA SOC / Big Data Soc.
Frequency1 issue/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address2455 TELLER RD, THOUSAND OAKS, CA 91320

Aims and Scopes

Big Data & Society is dedicated to the exploration of the complex interactions between big data, society, and technology. The journal aims to provide a platform for interdisciplinary research that critically examines the implications of data-driven practices, ethics, and governance in various contexts. Below are the core areas of focus for the journal:
  1. Critical Data Studies:
    The journal emphasizes critical perspectives on data practices, exploring how data is produced, managed, and utilized across different sectors, including healthcare, policing, and social media.
  2. Ethics and Governance of Data:
    Research addressing the ethical implications and governance challenges associated with big data technologies and artificial intelligence is central, particularly concerning privacy, accountability, and bias.
  3. Socio-Technical Interactions:
    The journal investigates the socio-technical dimensions of big data, including how data technologies intersect with social structures, cultural practices, and power dynamics.
  4. Interdisciplinary Approaches:
    Big Data & Society encourages interdisciplinary methodologies, drawing insights from sociology, anthropology, political science, computer science, and more to understand the multifaceted nature of data.
  5. Global Perspectives:
    The journal includes research that examines data practices in a global context, particularly focusing on issues of coloniality, inequality, and the impact of data on marginalized communities.
  6. Innovations in Data Technologies:
    Exploration of emerging data technologies, including blockchain, AI, and machine learning, and their implications for society, governance, and ethical practices is a significant focus.
Recent publications in Big Data & Society reveal several emerging themes that reflect the changing landscape of data research and its societal implications. The following areas are gaining traction:
  1. Data Activism and Justice:
    There is an increasing focus on data activism, exploring how communities mobilize against data injustices and advocate for equitable data governance practices.
  2. Algorithmic Accountability:
    Research on the accountability of algorithms has surged, particularly concerning their role in decision-making processes in various sectors, including law enforcement, healthcare, and employment.
  3. Participatory Approaches to Data Governance:
    Emerging themes highlight the importance of participatory methods in data governance, emphasizing stakeholder engagement and co-design in developing data policies.
  4. Impact of AI on Society:
    The implications of artificial intelligence on social structures, including issues of bias, discrimination, and ethical considerations, are increasingly prominent in the journal's publications.
  5. Environmental Data and Sustainability:
    Research linking big data practices to environmental sustainability and climate change is becoming more prevalent, reflecting a growing awareness of the ecological implications of data.
  6. Intersectionality in Data Studies:
    There is a rising interest in intersectional analyses of data practices, exploring how race, gender, and socio-economic status intersect to shape data experiences and outcomes.

Declining or Waning

As the field of big data research evolves, certain themes have become less prominent in recent publications. The following areas appear to be waning in focus within the journal's scope:
  1. Traditional Quantitative Methods:
    There has been a noticeable decline in papers utilizing traditional quantitative methodologies in favor of qualitative and mixed-method approaches that emphasize critical analysis and context.
  2. Narrowly Defined Technical Frameworks:
    Research that strictly adheres to technical frameworks without considering socio-political implications is less frequently published, indicating a shift towards more integrative and critical perspectives.
  3. General Data Analytics:
    Papers focused on generic data analytics without a critical lens or societal implications are appearing less often, as the journal seeks to prioritize discussions that critically engage with the ethical and social dimensions of data.
  4. Technology-Centric Narratives:
    There is a reduction in technology-centric narratives that celebrate data technologies without critique, reflecting a growing focus on the critical examination of the societal impacts of these technologies.
  5. Historical Data Analysis:
    While historical perspectives remain relevant, there is a decreased emphasis on retrospective analyses of data practices in favor of forward-looking research that anticipates future implications.

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