Big Data & Society大数据与社会

Big Data & Society(英文缩写 BIG DATA SOC),ISSN 2053-9517,eISSN 2053-9517,中文译名:大数据与社会 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。

2026 年数据 · 影响因子
7.800
JCR 分区
Q1
CAS 分区
B1
近一年发文量
0
本站 PubMed 收录统计

发文量统计区间:2025-09-24 至 2026-09-24,按本站收录文献的发表日期统计。

ISSN: 2053-9517 · eISSN: 2053-9517 · 缩写: BIG DATA SOC ·中文: 大数据与社会

期刊介绍

选择期刊介绍栏目

期刊简介

《Big Data & Society》是一本聚焦大数据与社会交叉领域的开放获取期刊,致力于探讨数据驱动技术对社会、文化、政治和经济的影响。期刊涵盖数据科学、社会学、传播学、伦理学、政策研究等,读者群包括学者、政策制定者和技术专家。

研究方向

主要研究方向包括大数据的社会影响、数据伦理与隐私、算法治理、数字不平等、数据科学与社会科学方法融合等。论文类型以原创研究、综述、评论和案例研究为主,鼓励跨学科视角。

期刊特色

期刊强调批判性、理论性与实证研究并重,关注数据技术的社会后果和权力关系。论文通常具有跨学科深度,适合社会科学、人文及数据科学领域的研究者、政策分析人员阅读。

投稿难度

投稿难度较高,因期刊跨学科性强且对理论贡献要求严格。建议作者确保研究问题清晰、方法严谨,并突出对社会与数据的批判性思考,避免仅描述技术应用。

历年影响因子趋势

JCR 数据年份影响因子JCR 分区
20218.731Q1
20228.500Q1
20236.500Q1
20245.900Q1
20257.800Q1

Big Data & Society 最新收录文献

  1. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    1. Understanding 'passivity' in digital health through imaginaries and experiences of coronavirus disease 2019 contact tracing apps.

    作者:
    Alessia Costa, Richard Milne
    日期:
    2022-01-01

    Growing interest is being directed to the health applications of so-called 'passive data' collected through wearables and sensors without active input by users. High promises are attached to passive d…

  2. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    2. Digital phenotyping and the (data) shadow of Alzheimer's disease.

    作者:
    Richard Milne, Alessia Costa, Natassia Brenman
    日期:
    2022-01-01

    In this paper, we examine the practice and promises of digital phenotyping. We build on work on the 'data self' to focus on a medical domain in which the value and nature of knowledge and relations wi…

  3. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    3. Ideological variation in preferred content and source credibility on Reddit during the COVID-19 pandemic.

    作者:
    Wallace Chipidza, Christopher Krewson, Nicole Gatto, Elmira Akbaripourdibazar, Tendai Gwanzura
    日期:
    2022-01-01

    In this exploratory study, we examine political polarization regarding the online discussion of the COVID-19 pandemic. We use data from Reddit to explore the differences in the topics emphasized by di…

  4. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    4. Political affiliation moderates subjective interpretations of COVID-19 graphs.

    作者:
    Jonathan D Ericson, William S Albert, Ja-Nae Duane
    日期:
    2022-01-01

    We examined the relationship between political affiliation, perceptual (percentage, slope) estimates, and subjective judgements of disease prevalence and mortality across three chart types. An online …

  5. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    5. The data will not save us: Afropessimism and racial antimatter in the COVID-19 pandemic.

    作者:
    Anthony Ryan Hatch
    日期:
    2022-01-01

    The Trump Administration's governance of COVID-19 racial health disparities data has become a key front in the viral war against the pandemic and racial health injustice. In this paper, I analyze how …

  6. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    6. Phenotyping as disciplinary practice: data infrastructure and the interprofessional conflict over drug use in California.

    作者:
    Mustafa I Hussain, Geoffrey C Bowker
    日期:
    2021-07-01

    The narrative of the digital phenotype as a transformative vector in healthcare is nearly identical to the concept of "data drivenness" in other fields such as law enforcement. We examine the role of …

  7. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    7. Disruption and dislocation in post-COVID futures for digital health.

    作者:
    Richard Milne, Alessia Costa
    日期:
    2020-07-01

    In this piece we explore the COVID pandemic as an opportunity for the articulation and realization of digital health futures. Our discussion draws on an engagement with emergent discourse around COVID…

  8. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    8. COVID-19 is spatial: Ensuring that mobile Big Data is used for social good.

    作者:
    Age Poom, Olle Järv, Matthew Zook, Tuuli Toivonen
    日期:
    2020-07-01

    The mobility restrictions related to COVID-19 pandemic have resulted in the biggest disruption to individual mobilities in modern times. The crisis is clearly spatial in nature, and examining the geog…

  9. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    9. Learning from lines: Critical COVID data visualizations and the quarantine quotidian.

    作者:
    Emily Bowe, Erin Simmons, Shannon Mattern
    日期:
    2020-07-01

    In response to the ubiquitous graphs and maps of COVID-19, artists, designers, data scientists, and public health officials are teaming up to create counter-plots and subaltern maps of the pandemic. I…

  10. JCR分区: Q1 CAS分区: B1 影响因子: 7.8

    10. Seven intersectional feminist principles for equitable and actionable COVID-19 data.

    作者:
    Catherine D'Ignazio, Lauren F Klein
    日期:
    2020-07-01

    This essay offers seven intersectional feminist principles for equitable and actionable COVID-19 data, drawing from the authors' prior work on data feminism. Our book, Data Feminism (D'Ignazio and Kle…

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指标接近的期刊