Subjects -> SOCIAL SCIENCES (Total: 1833 journals)
    - BIRTH CONTROL (22 journals)
    - CHILDREN AND YOUTH (270 journals)
    - FOLKLORE (30 journals)
    - MATRIMONY (16 journals)
    - MEN'S INTERESTS (16 journals)
    - MEN'S STUDIES (100 journals)
    - SEXUALITY (59 journals)
    - SOCIAL SCIENCES (1084 journals)
    - WOMEN'S INTERESTS (44 journals)
    - WOMEN'S STUDIES (192 journals)

SOCIAL SCIENCES (1084 journals)                  1 2 3 4 5 6     

Showing 1 - 136 of 136 Journals sorted alphabetically
(En)clave Comahue. Revista Patagónica de Estudios Sociales     Open Access   (Followers: 1)
3C Empresa     Open Access   (Followers: 4)
A contrario     Full-text available via subscription   (Followers: 3)
AAS Open Research     Open Access   (Followers: 2)
Abant Sosyal Bilimler Dergisi     Open Access   (Followers: 1)
Abordajes : Revista de Ciencias Sociales y Humanas     Open Access   (Followers: 1)
Aboriginal and Islander Health Worker Journal     Full-text available via subscription   (Followers: 18)
About Performance     Full-text available via subscription   (Followers: 13)
Academic Journal of Interdisciplinary Studies     Open Access   (Followers: 1)
Academicus International Scientific Journal     Open Access   (Followers: 3)
Access     Full-text available via subscription   (Followers: 31)
ACCESS: Critical Perspectives on Communication, Cultural & Policy Studies     Full-text available via subscription   (Followers: 16)
ACCORD Occasional Paper     Open Access   (Followers: 4)
Accountability in Research: Policies and Quality Assurance     Hybrid Journal   (Followers: 20)
Acta Academica     Full-text available via subscription   (Followers: 6)
Acta Humana     Open Access   (Followers: 1)
Acta Scientiarum. Human and Social Sciences     Open Access   (Followers: 11)
Acta Universitatis Sapientiae, Philologica     Open Access   (Followers: 2)
Actes de la Journée des Sciences et Savoirs     Open Access   (Followers: 9)
Adelphi series     Hybrid Journal   (Followers: 14)
Administrative Science Quarterly     Full-text available via subscription   (Followers: 258)
Administrative Theory & Praxis     Full-text available via subscription   (Followers: 8)
Adultspan Journal     Hybrid Journal   (Followers: 1)
Advances in Appreciative Inquiry     Hybrid Journal   (Followers: 1)
Advocate: Newsletter of the National Tertiary Education Union     Full-text available via subscription   (Followers: 1)
África     Open Access   (Followers: 1)
Africa Spectrum     Open Access   (Followers: 16)
African Affairs     Hybrid Journal   (Followers: 78)
African Renaissance     Full-text available via subscription   (Followers: 4)
African Research Review     Open Access   (Followers: 8)
African Social Science Review     Open Access   (Followers: 10)
Afrika Focus     Open Access   (Followers: 1)
Ágora : revista de divulgação científica     Open Access  
Ágora de Heterodoxias     Open Access   (Followers: 1)
Akademika : Journal of Southeast Asia Social Sciences and Humanities     Open Access   (Followers: 8)
AKADEMOS     Open Access   (Followers: 2)
Al-Mabsut : Jurnal Studi Islam dan Sosial     Open Access   (Followers: 1)
AL-Qadissiya Magzine for Human Sciences     Open Access   (Followers: 3)
Aleph : UCLA Undergraduate Research Journal for the Humanities and Social Sciences     Open Access   (Followers: 6)
Aletheia : Revista de Desarrollo Humano, Educativo y Social Contemporáneo     Open Access   (Followers: 1)
Algarrobo-MEL     Open Access   (Followers: 10)
Alinteri Journal of Social Sciences     Open Access   (Followers: 2)
Alliage     Free  
Alteridade     Open Access  
Ambigua : Revista de Investigaciones sobre Género y Estudios Culturales     Open Access   (Followers: 1)
American Communist History     Hybrid Journal   (Followers: 21)
Anais do Congresso de Pesquisa e Extensão e da Semana de Ciências Sociais da UEMG/Barbacena     Open Access  
Anais Eletrônicos do Congresso Epistemologias do Sul     Open Access   (Followers: 1)
ANALES de la Universidad Central del Ecuador     Open Access   (Followers: 3)
Anales de la Universidad de Chile     Open Access  
Análisis     Open Access  
Analysis     Full-text available via subscription   (Followers: 4)
Andamios. Revista de Investigacion Social     Open Access   (Followers: 1)
Anduli : Revista Andaluza de Ciencias Sociales     Open Access  
Ankara Üniversitesi Sosyal Bilimler Dergisi     Open Access  
Ankara University SBF Journal     Open Access   (Followers: 1)
Annals of Humanities and Development Studies     Open Access   (Followers: 6)
Annals of the American Academy of Political and Social Science     Hybrid Journal   (Followers: 50)
Annuaire de l’EHESS     Open Access  
Anthropocene Review     Hybrid Journal   (Followers: 8)
Anthurium : A Caribbean Studies Journal     Open Access   (Followers: 7)
Approches inductives : Travail intellectuel et construction des connaissances     Open Access  
Apuntes : Revista de Ciencias Sociales     Open Access   (Followers: 2)
Apuntes de Investigación del CECYP     Open Access  
Arbejdspapirer : Professionshøjskolen Metropol     Open Access   (Followers: 3)
Arbetsliv i omvandling     Open Access  
Arbor     Open Access  
Argomenti. Rivista di economia, cultura e ricerca sociale     Open Access   (Followers: 3)
Argumentos : Revista do Departamento de Ciências Sociais da Unimontes     Open Access  
Argumentos. Revista de crítica social     Open Access  
Around the Globe     Full-text available via subscription   (Followers: 1)
Arquivos do CMD : Cultura, Memória e Desenvolvimento     Open Access  
ArtefaCToS : Revista de estudios sobre la ciencia y la tecnología     Open Access   (Followers: 1)
Articulo - Journal of Urban Research     Open Access   (Followers: 8)
Asia Pacific Journal of Sport and Social Science     Hybrid Journal   (Followers: 6)
Asian Journal of German and European Studies     Open Access  
Asian Journal of Quality of Life     Open Access   (Followers: 1)
Asian Journal of Social Sciences and Management Studies     Open Access   (Followers: 8)
Asian Research Journal of Arts & Social Sciences     Open Access   (Followers: 1)
Asian Social Science     Open Access   (Followers: 7)
Astrolabio, Nueva Época     Open Access  
Ateneo Chinese Studies Program Lecture Series     Open Access  
Aurum Journal of Social Sciences     Open Access  
Australasian Review of African Studies, The     Full-text available via subscription   (Followers: 2)
Australian Aboriginal Studies     Full-text available via subscription   (Followers: 10)
Australian and Aotearoa New Zealand Psychodrama Association Journal     Full-text available via subscription   (Followers: 2)
Australian Journal of Emergency Management     Full-text available via subscription   (Followers: 31)
Australian Journal on Volunteering     Full-text available via subscription   (Followers: 3)
Australian Population Studies     Open Access  
Austrian Journal of South-East Asian Studies     Open Access   (Followers: 1)
Bandung : Journal of the Global South     Open Access   (Followers: 1)
BARATARIA. Revista Castellano-Manchega de Ciencias sociales     Open Access  
Barn : Forskning om barn og barndom i Norden     Open Access   (Followers: 1)
Basic and Applied Social Psychology     Hybrid Journal   (Followers: 46)
Basic Income Studies     Hybrid Journal   (Followers: 9)
Bayero Journal of Pure and Applied Sciences     Open Access   (Followers: 2)
Behavioural Sciences Undergraduate Journal     Open Access   (Followers: 6)
Berkeley Undergraduate Journal     Full-text available via subscription   (Followers: 1)
Bhakti Persada : Jurnal Aplikasi IPTEKS     Open Access  
Big Data & Society     Open Access   (Followers: 53)
Bildhaan : An International Journal of Somali Studies     Open Access   (Followers: 4)
Bingöl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi     Open Access  
Black Sea Journal of Public and Social Science     Open Access  
Black Women, Gender & Families     Full-text available via subscription   (Followers: 19)
BMC Medical Ethics     Open Access   (Followers: 25)
Bodhi : An Interdisciplinary Journal     Open Access   (Followers: 2)
Body Image     Hybrid Journal   (Followers: 17)
BOGA : Basque Studies Consortium Journal     Open Access   (Followers: 2)
Boletín Cultural y Bibliográfico     Open Access   (Followers: 2)
Boletín Memoria     Open Access  
Border Crossing : Transnational Working Papers     Open Access   (Followers: 3)
Borderlands Journal : Culture, Politics, Law and Earth     Open Access  
Brain and Cognition     Hybrid Journal   (Followers: 40)
British Review of New Zealand Studies     Full-text available via subscription   (Followers: 5)
BU Academic Review     Open Access  
Bulletin de l’Institut Français d’Études Andines     Open Access   (Followers: 4)
Bulletin of Social Informatics Theory and Application     Open Access   (Followers: 1)
Búsqueda     Open Access  
Caderno CRH     Open Access   (Followers: 2)
Cadernos de Ciências Sociais Aplicadas     Open Access   (Followers: 1)
Cadernos de Estudos Sociais     Open Access   (Followers: 2)
Cadernos de Saúde     Open Access   (Followers: 1)
California Italian Studies Journal     Full-text available via subscription   (Followers: 8)
California Journal of Politics and Policy     Open Access   (Followers: 2)
Cambio : Rivista sulle Trasformazioni Sociali     Open Access  
Caminho Aberto : Revista de Extensão do IFSC     Open Access  
Campos en Ciencias Sociales     Open Access  
Canadian Journal of Human Sexuality     Hybrid Journal   (Followers: 3)
Canadian Social Science     Open Access   (Followers: 14)
Caradde : Jurnal Pengabdian Kepada Masyarakat     Open Access  
Caribbean Studies     Full-text available via subscription   (Followers: 12)
Castalia : Revista de Psicología de la Academia     Open Access  
Catalan Social Sciences Review     Open Access   (Followers: 1)
Catalyst : A Social Justice Forum     Open Access   (Followers: 10)
Catholic Social Science Review     Open Access   (Followers: 4)
CBU International Conference Proceedings     Open Access   (Followers: 2)
Cemoti, Cahiers d'études sur la méditerranée orientale et le monde turco-iranien     Open Access   (Followers: 3)
Challenges     Open Access   (Followers: 2)
Chandrakasem Rajabhat University Journal of Graduate School     Open Access  
Changing Societies & Personalities     Open Access   (Followers: 1)
China Journal of Social Work     Hybrid Journal   (Followers: 2)
Chinese Journal of Social Science and Management     Open Access  
Chinese Studies     Open Access   (Followers: 8)
Cidadania em Ação : Revista de Extensão e Cultura: Notícias     Open Access  
Ciencia e Interculturalidad     Open Access   (Followers: 2)
Ciência ET Praxis     Open Access  
Ciencia Sociales y Económicas     Open Access  
Ciencia y Sociedad     Open Access   (Followers: 2)
Ciencia, Cultura y Sociedad     Open Access   (Followers: 1)
Ciencia, Técnica y Mainstreaming Social     Open Access  
Ciencias Holguin     Open Access   (Followers: 2)
Ciências Sociais Unisinos     Open Access   (Followers: 2)
Ciencias Sociales y Educación     Open Access   (Followers: 4)
Ciencias Sociales y Humanidades     Open Access   (Followers: 3)
Ciencias Sociales y Religión/Ciências Sociais e Religião     Open Access  
CienciaUAT     Open Access   (Followers: 1)
Científic@ : Multidisciplinary Journal     Open Access  
Circular Economy and Sustainability     Hybrid Journal   (Followers: 1)
Citizen Science : Theory and Practice     Open Access   (Followers: 2)
Citizenship Teaching & Learning     Hybrid Journal   (Followers: 9)
Ciudad Paz-ando     Open Access   (Followers: 1)
Civilizar Ciencias Sociales y Humanas     Open Access   (Followers: 2)
Civitas - Revista de Ciências Sociais     Open Access   (Followers: 2)
Claroscuro     Open Access   (Followers: 1)
CLIO América     Open Access   (Followers: 2)
CMU Journal of Law and Social Sciences     Open Access   (Followers: 3)
Cogent Social Sciences     Open Access   (Followers: 3)
Cognitive and Behavioral Practice     Hybrid Journal   (Followers: 13)
Colección Académica de Ciencias Sociales     Open Access  
Colonial Academic Alliance Undergraduate Research Journal     Open Access   (Followers: 3)
Communication, Politics & Culture     Open Access   (Followers: 13)
Communities, Children and Families Australia     Full-text available via subscription   (Followers: 4)
Community Empowerment     Open Access  
Compendium     Open Access   (Followers: 2)
Comprehensive Results in Social Psychology     Hybrid Journal   (Followers: 1)
Comprehensive Therapy     Hybrid Journal   (Followers: 3)
Comuni@cción     Open Access   (Followers: 1)
Comunitania : Revista Internacional de Trabajo Social y Ciencias Sociales     Open Access   (Followers: 1)
ConCiencia     Open Access  
Confluenze Rivista di Studi Iberoamericani     Open Access  
Connections     Open Access  
Conocimiento, Investigación y Educación CIE     Open Access   (Followers: 1)
Contemporary Journal of African Studies     Full-text available via subscription   (Followers: 4)
Contemporary Social Science     Hybrid Journal   (Followers: 15)
CONTRA : RELATOS desde el Sur     Open Access  
Contribuciones desde Coatepec     Open Access   (Followers: 1)
Convergencia     Open Access   (Followers: 2)
Cooperativismo y Desarrollo     Open Access   (Followers: 1)
Corporate Reputation Review     Hybrid Journal   (Followers: 6)
CRDCN Research Highlight / RCCDR en évidence     Open Access   (Followers: 1)
Creative and Knowledge Society     Open Access   (Followers: 11)
Creative Approaches to Research     Full-text available via subscription   (Followers: 14)
Critical Psychology     Hybrid Journal   (Followers: 10)
Critical Studies on Terrorism     Hybrid Journal   (Followers: 58)
Crossing the Border : International Journal of Interdisciplinary Studies     Open Access   (Followers: 5)
CTheory     Open Access  
Cuadernos de la Facultad de Humanidades y Ciencias Sociales - Universidad Nacional de Jujuy     Open Access   (Followers: 1)
Cuadernos de la Facultad de Humanidades y Ciencias Sociales. Universidad Nacional de Jujuy     Open Access  
Cultura Latinoamericana     Open Access  
Cultura y Representaciones Sociales     Open Access   (Followers: 1)

        1 2 3 4 5 6     

Similar Journals
Journal Cover
Big Data & Society
Number of Followers: 53  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2053-9517
Published by Sage Publications Homepage  [1144 journals]
  • Identifying how COVID-19-related misinformation reacts to the announcement
           of the UK national lockdown: An interrupted time-series study

    • Authors: Mark Green, Elena Musi, Francisco Rowe, Darren Charles, Frances Darlington Pollock, Chris Kypridemos, Andrew Morse, Patricia Rossini, John Tulloch, Andrew Davies, Emily Dearden, Henrdramoorthy Maheswaran, Alex Singleton, Roberto Vivancos, Sally Sheard
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      COVID-19 is unique in that it is the first global pandemic occurring amidst a crowded information environment that has facilitated the proliferation of misinformation on social media. Dangerous misleading narratives have the potential to disrupt ‘official’ information sharing at major government announcements. Using an interrupted time-series design, we test the impact of the announcement of the first UK lockdown (8–8.30 p.m. 23 March 2020) on short-term trends of misinformation on Twitter. We utilise a novel dataset of all COVID-19-related social media posts on Twitter from the UK 48 hours before and 48 hours after the announcement (n = 2,531,888). We find that while the number of tweets increased immediately post announcement, there was no evidence of an increase in misinformation-related tweets. We found an increase in COVID-19-related bot activity post-announcement. Topic modelling of misinformation tweets revealed four distinct clusters: ‘government and policy’, ‘symptoms’, ‘pushing back against misinformation’ and ‘cures and treatments’.
      Citation: Big Data & Society
      PubDate: 2021-05-09T05:58:54Z
      DOI: 10.1177/20539517211013869
      Issue No: Vol. 8, No. 1 (2021)
       
  • Countering misinformation: A multidisciplinary approach

    • Authors: Kacper T Gradoń, Janusz A. Hołyst, Wesley R Moy, Julian Sienkiewicz, Krzysztof Suchecki
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      The article explores the concept of infodemics during the COVID-19 pandemic, focusing on the propagation of false or inaccurate information proliferating worldwide throughout the SARS-CoV-2 health crisis. We provide an overview of disinformation, misinformation and malinformation and discuss the notion of “fake news”, and highlight the threats these phenomena bear for health policies and national and international security. We discuss the mis-/disinformation as a significant challenge to the public health, intelligence, and policymaking communities and highlight the necessity to design measures enabling the prevention, interdiction, and mitigation of such threats. We then present an overview of selected opportunities for applying technology to study and combat disinformation, outlining several approaches currently being used to understand, describe, and model the phenomena of misinformation and disinformation. We focus specifically on complex networks, machine learning, data- and text-mining methods in misinformation detection, sentiment analysis, and agent-based models of misinformation spreading and the detection of misinformation sources in the network. We conclude with the set of recommendations supporting the World Health Organization’s initiative on infodemiology. We support the implementation of integrated preventive procedures and internationalization of infodemic management. We also endorse the application of the cross-disciplinary methodology of Crime Science discipline, supplemented by Big Data analysis and related information technologies to prevent, disrupt, and detect mis- and disinformation efficiently.
      Citation: Big Data & Society
      PubDate: 2021-05-06T05:06:07Z
      DOI: 10.1177/20539517211013848
      Issue No: Vol. 8, No. 1 (2021)
       
  • The COVID-19 Infodemic: Twitter versus Facebook

    • Authors: Kai-Cheng Yang, Francesco Pierri, Pik-Mai Hui, David Axelrod, Christopher Torres-Lugo, John Bryden, Filippo Menczer
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      The global spread of the novel coronavirus is affected by the spread of related misinformation—the so-called COVID-19 Infodemic—that makes populations more vulnerable to the disease through resistance to mitigation efforts. Here, we analyze the prevalence and diffusion of links to low-credibility content about the pandemic across two major social media platforms, Twitter and Facebook. We characterize cross-platform similarities and differences in popular sources, diffusion patterns, influencers, coordination, and automation. Comparing the two platforms, we find divergence among the prevalence of popular low-credibility sources and suspicious videos. A minority of accounts and pages exert a strong influence on each platform. These misinformation “superspreaders” are often associated with the low-credibility sources and tend to be verified by the platforms. On both platforms, there is evidence of coordinated sharing of Infodemic content. The overt nature of this manipulation points to the need for societal-level solutions in addition to mitigation strategies within the platforms. However, we highlight limits imposed by inconsistent data-access policies on our capability to study harmful manipulations of information ecosystems.
      Citation: Big Data & Society
      PubDate: 2021-05-06T05:06:07Z
      DOI: 10.1177/20539517211013861
      Issue No: Vol. 8, No. 1 (2021)
       
  • Assessing biases, relaxing moralism: On ground-truthing practices in
           machine learning design and application

    • Authors: Florian Jaton
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      This theoretical paper considers the morality of machine learning algorithms and systems in the light of the biases that ground their correctness. It begins by presenting biases not as a priori negative entities but as contingent external referents—often gathered in benchmarked repositories called ground-truth datasets—that define what needs to be learned and allow for performance measures. I then argue that ground-truth datasets and their concomitant practices—that fundamentally involve establishing biases to enable learning procedures—can be described by their respective morality, here defined as the more or less accounted experience of hesitation when faced with what pragmatist philosopher William James called “genuine options”—that is, choices to be made in the heat of the moment that engage different possible futures. I then stress three constitutive dimensions of this pragmatist morality, as far as ground-truthing practices are concerned: (I) the definition of the problem to be solved (problematization), (II) the identification of the data to be collected and set up (databasing), and (III) the qualification of the targets to be learned (labeling). I finally suggest that this three-dimensional conceptual space can be used to map machine learning algorithmic projects in terms of the morality of their respective and constitutive ground-truthing practices. Such techno-moral graphs may, in turn, serve as equipment for greater governance of machine learning algorithms and systems.
      Citation: Big Data & Society
      PubDate: 2021-05-06T05:06:06Z
      DOI: 10.1177/20539517211013569
      Issue No: Vol. 8, No. 1 (2021)
       
  • The case for tracking misinformation the way we track disease

    • Authors: Erika Bonnevie, Jennifer Sittig, Joe Smyser
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      While public health organizations can detect disease spread, few can monitor and respond to real-time misinformation. Misinformation risks the public’s health, the credibility of institutions, and the safety of experts and front-line workers. Big Data, and specifically publicly available media data, can play a significant role in understanding and responding to misinformation. The Public Good Projects uses supervised machine learning to aggregate and code millions of conversations relating to vaccines and the COVID-19 pandemic broadly, in real-time. Public health researchers supervise this process daily, and provide insights to practitioners across a range of disciplines. Through this work, we have gleaned three lessons to address misinformation. (1) Sources of vaccine misinformation are known; there is a need to operationalize learnings and engage the pro-vaccination majority in debunking vaccine-related misinformation. (2) Existing systems can identify and track threats against health experts and institutions, which have been subject to unprecedented harassment. This supports their safety and helps prevent the further erosion of trust in public institutions. (3) Responses to misinformation should draw from cross-sector crisis management best practices and address coordination gaps. Real-time monitoring and addressing misinformation should be a core function of public health, and public health should be a core use case for data scientists developing monitoring tools. The tools to accomplish these tasks are available; it remains up to us to prioritize them.
      Citation: Big Data & Society
      PubDate: 2021-05-06T05:06:05Z
      DOI: 10.1177/20539517211013867
      Issue No: Vol. 8, No. 1 (2021)
       
  • Big Data in the workplace: Privacy Due Diligence as a human rights-based
           approach to employee privacy protection

    • Authors: Isabel Ebert, Isabelle Wildhaber, Jeremias Adams-Prassl
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      Data-driven technologies have come to pervade almost every aspect of business life, extending to employee monitoring and algorithmic management. How can employee privacy be protected in the age of datafication' This article surveys the potential and shortcomings of a number of legal and technical solutions to show the advantages of human rights-based approaches in addressing corporate responsibility to respect privacy and strengthen human agency. Based on this notion, we develop a process-oriented model of Privacy Due Diligence to complement existing frameworks for safeguarding employee privacy in an era of Big Data surveillance.
      Citation: Big Data & Society
      PubDate: 2021-05-06T05:06:03Z
      DOI: 10.1177/20539517211013051
      Issue No: Vol. 8, No. 1 (2021)
       
  • Identifying and characterizing scientific authority-related misinformation
           discourse about hydroxychloroquine on twitter using unsupervised machine
           learning

    • Authors: Michael Robert Haupt, Jiawei Li, Tim K Mackey
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      This study investigates the types of misinformation spread on Twitter that evokes scientific authority or evidence when making false claims about the antimalarial drug hydroxychloroquine as a treatment for COVID-19. Specifically, we examined tweets generated after former U.S. President Donald Trump retweeted misinformation about the drug using an unsupervised machine learning approach called the biterm topic model that is used to cluster tweets into misinformation topics based on textual similarity. The top 10 tweets from each topic cluster were content coded for three types of misinformation categories related to scientific authority: medical endorsements of hydroxychloroquine, scientific information used to support hydroxychloroquine’s use, and a comparison group that included scientific evidence opposing hydroxychloroquine’s use. Results show a much higher volume of tweets featuring medical endorsements and use of supportive scientific information compared to accurate and updated scientific evidence, that misinformation-related tweets propagated for a longer time frame, and the majority of hydroxychloroquine Twitter discourse expressed positive views about the drug. Metadata from Twitter accounts found that prominent users within misinformation discourse were more likely to have media or political affiliation and explicitly expressed support for President Trump. Conversely, prominent accounts within the scientific opposition discourse primarily consisted of medical doctors or scientists but had far less influence in the Twitter discourse. Implications of these findings and connections to related social media research are discussed, as well as cognitive mechanisms for understanding susceptibility to misinformation and strategies to combat misinformation spread via online platforms.
      Citation: Big Data & Society
      PubDate: 2021-05-06T04:17:09Z
      DOI: 10.1177/20539517211013843
      Issue No: Vol. 8, No. 1 (2021)
       
  • From FAIR data to fair data use: Methodological data fairness in
           health-related social media research

    • Authors: Sabina Leonelli, Rebecca Lovell, Benedict W Wheeler, Lora Fleming, Hywel Williams
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      The paper problematises the reliability and ethics of using social media data, such as sourced from Twitter or Instagram, to carry out health-related research. As in many other domains, the opportunity to mine social media for information has been hailed as transformative for research on well-being and disease. Considerations around the fairness, responsibilities and accountabilities relating to using such data have often been set aside, on the understanding that as long as data were anonymised, no real ethical or scientific issue would arise. We first counter this perception by emphasising that the use of social media data in health research can yield problematic and unethical results. We then provide a conceptualisation of methodological data fairness that can complement data management principles such as FAIR by enhancing the actionability of social media data for future research. We highlight the forms that methodological data fairness can take at different stages of the research process and identify practical steps through which researchers can ensure that their practices and outcomes are scientifically sound as well as fair to society at large. We conclude that making research data fair as well as FAIR is inextricably linked to concerns around the adequacy of data practices. The failure to act on those concerns raises serious ethical, methodological and epistemic issues with the knowledge and evidence that are being produced.
      Citation: Big Data & Society
      PubDate: 2021-05-04T05:05:25Z
      DOI: 10.1177/20539517211010310
      Issue No: Vol. 8, No. 1 (2021)
       
  • One size does not fit all: Constructing complementary digital reskilling
           strategies using online labour market data

    • Authors: Fabian Stephany
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      Digital technologies are radically transforming our work environments and demand for skills, with certain jobs being automated away and others demanding mastery of new digital techniques. This global challenge of rapidly changing skill requirements due to task automation overwhelms workers. The digital skill gap widens further as technological and social transformation outpaces national education systems and precise skill requirements for mastering emerging technologies, such as Artificial Intelligence, remain opaque. Online labour platforms could help us to understand this grand challenge of reskilling en masse. Online labour platforms build a globally integrated market that mediates between millions of buyers and sellers of remotely deliverable cognitive work. This commentary argues that, over the last decade, online labour platforms have become the ‘laboratories’ of skill rebundling; the combination of skills from different occupational domains. Online labour platform data allows us to establish a new taxonomy on the individual complementarity of skills. For policy makers, education providers and recruiters, a continuous analysis of complementary reskilling trajectories enables automated, individual and far-sighted suggestions on the value of learning a new skill in a future of technological disruption.
      Citation: Big Data & Society
      PubDate: 2021-04-15T05:45:17Z
      DOI: 10.1177/20539517211003120
      Issue No: Vol. 8, No. 1 (2021)
       
  • The data archive as factory: Alienation and resistance of data processors

    • Authors: Jean-Christophe Plantin
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      Archival data processing consists of cleaning and formatting data between the moment a dataset is deposited and its publication on the archive’s website. In this article, I approach data processing by combining scholarship on invisible labor in knowledge infrastructures with a Marxian framework and show the relevance of considering data processing as factory labor. Using this perspective to analyze ethnographic data collected during a six-month participatory observation at a U.S. data archive, I generate a taxonomy of the forms of alienation that data processing generates, but also the types of resistance that processors develop, across four categories: routine, speed, skill, and meaning. This synthetic approach demonstrates, first, that data processing reproduces typical forms of factory worker’s alienation: processors are asked to work along a strict standardized pipeline, at a fast pace, without acquiring substantive skills or having a meaningful involvement in their work. It reveals, second, how data processors resist the alienating nature of this workflow by developing multiple tactics along the same four categories. Seen through this dual lens, data processors are therefore not only invisible workers, but also factory workers who follow and subvert a workflow organized as an assembly line. I conclude by proposing a four-step framework to better value the social contribution of data workers beyond the archive.
      Citation: Big Data & Society
      PubDate: 2021-04-07T06:54:04Z
      DOI: 10.1177/20539517211007510
      Issue No: Vol. 8, No. 1 (2021)
       
  • The value of mass-digitised cultural heritage content in creative contexts

    • Authors: Melissa Terras, Stephen Coleman, Steven Drost, Chris Elsden, Ingi Helgason, Susan Lechelt, Nicola Osborne, Inge Panneels, Briana Pegado, Burkhard Schafer, Michael Smyth, Pip Thornton, Chris Speed
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      How can digitised assets of Galleries, Libraries, Archives and Museums be reused to unlock new value' What are the implications of viewing large-scale cultural heritage data as an economic resource, to build new products and services upon' Drawing upon valuation studies, we reflect on both the theory and practicalities of using mass-digitised heritage content as an economic driver, stressing the need to consider the complexity of commercial-based outcomes within the context of cultural and creative industries. However, we also problematise the act of considering such heritage content as a resource to be exploited for economic growth, in order to inform how we consider, develop, deliver and value mass-digitisation. Our research will be of interest to those wishing to understand a rapidly changing research and innovation landscape, those considering how to engage memory institutions in data-driven activities and those critically evaluating years of mass-digitisation across the heritage sector.
      Citation: Big Data & Society
      PubDate: 2021-04-07T06:54:03Z
      DOI: 10.1177/20539517211006165
      Issue No: Vol. 8, No. 1 (2021)
       
  • Between surveillance and recognition: Rethinking digital identity in aid

    • Authors: Keren Weitzberg, Margie Cheesman, Aaron Martin, Emrys Schoemaker
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      Identification technologies like biometrics have long been associated with securitisation, coercion and surveillance but have also, in recent years, become constitutive of a politics of empowerment, particularly in contexts of international aid. Aid organisations tend to see digital identification technologies as tools of recognition and inclusion rather than oppressive forms of monitoring, tracking and top-down control. In addition, practices that many critical scholars describe as aiding surveillance are often experienced differently by humanitarian subjects. This commentary examines the fraught questions this raises for scholars of international aid, surveillance studies and critical data studies. We put forward a research agenda that tackles head-on how critical theories of data and society can better account for the ambivalent dynamics of ‘power over’ and ‘power to’ that digital aid interventions instantiate.
      Citation: Big Data & Society
      PubDate: 2021-04-02T03:59:20Z
      DOI: 10.1177/20539517211006744
      Issue No: Vol. 8, No. 1 (2021)
       
  • Data diaries: A situated approach to the study of data

    • Authors: Nathaniel Tkacz, Mário Henrique da Mata Martins, João Porto de Albuquerque, Flávio Horita, Giovanni Dolif Neto
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      This article adapts the ethnographic medium of the diary to develop a method for studying data and related data practices. The article focuses on the creation of one data diary, developed iteratively over three years in the context of a national centre for monitoring disasters and natural hazards in Brazil (Cemaden). We describe four points of focus involved in the creation of a data diary – spaces, interfaces, types and situations – before reflecting on the value of this method. We suggest data diaries (1) are able to capture the informal dimension of data-intensive organisations; (2) enable empirical analysis of the specific ways that data intervene in the unfolding of situations; and (3) as a document, data diaries can foster interdisciplinary and inter-expert dialogue by bridging different ways of knowing data.
      Citation: Big Data & Society
      PubDate: 2021-03-24T07:10:34Z
      DOI: 10.1177/2053951721996036
      Issue No: Vol. 8, No. 1 (2021)
       
  • Heritage-based tribalism in Big Data ecologies: Deploying origin myths for
           antagonistic othering

    • Authors: Chiara Bonacchi, Marta Krzyzanska
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      This article presents a conceptual and methodological framework to study heritage-based tribalism in Big Data ecologies by combining approaches from the humanities, social and computing sciences. We use such a framework to examine how ideas of human origin and ancestry are deployed on Twitter for purposes of antagonistic ‘othering’. Our goal is to equip researchers with theory and analytical tools for investigating divisive online uses of the past in today’s networked societies. In particular, we apply notions of heritage, othering and neo-tribalism, and both data-intensive and qualitative methods to the case of people’s engagements with the news of Cheddar Man’s DNA on Twitter. We show that heritage-based tribalism in Big Data ecologies is uniquely shaped as an assemblage by the coalescing of different forms of antagonistic othering. Those that co-occur most frequently are the ones that draw on ‘Views on Race’, ‘Trust in Experts’ and ‘Political Leaning’. The framings of the news that were most influential in triggering heritage-based tribalism were introduced by both right- and left-leaning newspaper outlets and by activist websites. We conclude that heritage-themed communications that rely on provocative narratives on social media tend to be labelled as political and not to be conducive to positive change in people’s attitudes towards issues such as racism.
      Citation: Big Data & Society
      PubDate: 2021-03-24T06:47:16Z
      DOI: 10.1177/20539517211003310
      Issue No: Vol. 8, No. 1 (2021)
       
  • Epistemologies of predictive policing: Mathematical social science, social
           physics and machine learning

    • Authors: Jens Hälterlein
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      Predictive policing has become a new panacea for crime prevention. However, we still know too little about the performance of computational methods in the context of predictive policing. The paper provides a detailed analysis of existing approaches to algorithmic crime forecasting. First, it is explained how predictive policing makes use of predictive models to generate crime forecasts. Afterwards, three epistemologies of predictive policing are distinguished: mathematical social science, social physics and machine learning. Finally, it is shown that these epistemologies have significant implications for the constitution of predictive knowledge in terms of its genesis, scope, intelligibility and accessibility. It is the different ways future crimes are rendered knowledgeable in order to act upon them that reaffirm or reconfigure the status of criminological knowledge within the criminal justice system, direct the attention of law enforcement agencies to particular types of crimes and criminals and blank out others, satisfy the claim for the meaningfulness of predictions or break with it and allow professionals to understand the algorithmic systems they shall rely on or turn them into a black box. By distinguishing epistemologies and analysing their implications, this analysis provides insight into the techno-scientific foundations of predictive policing and enables us to critically engage with the socio-technical practices of algorithmic crime forecasting.
      Citation: Big Data & Society
      PubDate: 2021-03-18T05:15:44Z
      DOI: 10.1177/20539517211003118
      Issue No: Vol. 8, No. 1 (2021)
       
  • Emotional artificial intelligence in children’s toys and devices:
           Ethics, governance and practical remedies

    • Authors: Andrew McStay, Gilad Rosner
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      This article examines the social acceptability and governance of emotional artificial intelligence (emotional AI) in children’s toys and other child-oriented devices. To explore this, it conducts interviews with stakeholders with a professional interest in emotional AI, toys, children and policy to consider implications of the usage of emotional AI in children’s toys and services. It also conducts a demographically representative UK national survey to ascertain parental perspectives on networked toys that utilise data about emotions. The article highlights disquiet about the evolution of generational unfairness, that encompasses injustices regarding the datafication of childhood, manipulation, parental vulnerability, synthetic personalities, child and parental media literacy, and need for improved governance. It concludes with practical recommendations for regulators and the toy industry.
      Citation: Big Data & Society
      PubDate: 2021-03-15T04:24:29Z
      DOI: 10.1177/2053951721994877
      Issue No: Vol. 8, No. 1 (2021)
       
  • “More like a support tool”: Ambivalences around digital health from
           medical developers’ perspective

    • Authors: Sarah Lenz
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      Against the background of the increasing importance of digitization in health care, the paper examines how medical practitioners who are involved in the development of digital health technologies legitimate and criticize the implementation and use of digital health technologies. Adopting an institutional logics perspective, the study is based on qualitative interviews with persons working at the interface of medicine and digital technologies development in Switzerland. The findings indicate that the developers believe that digital health technologies could harmonize current conflicts between an increasing economization of the health care system and professional–ethical demands. At the same time, however, they show that digital technologies can undermine the demand for medical autonomy, a central element of the medical ethos.
      Citation: Big Data & Society
      PubDate: 2021-03-12T10:54:36Z
      DOI: 10.1177/2053951721996733
      Issue No: Vol. 8, No. 1 (2021)
       
  • “Reach the right people”: The politics of “interests” in
           Facebook’s classification system for ad targeting

    • Authors: Kelley Cotter, Mel Medeiros, Chankyung Pak, Kjerstin Thorson
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      Political campaigns increasingly rely on Facebook for reaching their constituents, particularly through ad targeting. Facebook’s business model is premised on a promise to connect advertisers with the “right” users: those likely to click, download, engage, purchase. The company pursues this promise (in part) by algorithmically inferring users’ interests from their data and providing advertisers with a means of targeting users by their inferred interests. In this study, we explore for whom this interest classification system works in order to build on conversations in critical data studies about the ways such systems produce knowledge about the world rooted in power structures. We critically analyze the classification system from a variety of empirical vantage points—via user data; Facebook documentation, training, and patents; and Facebook’s tools for advertisers—and through theoretical concepts from a variety of domains. In this, we focus on the ways the classification system shapes possibilities for political representation and voice, particularly for people of color, women, and LGBTQ+ people. We argue that this “big data-driven” classification system should be read as political: it articulates a stance not only on what issues are or are not important in the U.S. public sphere, but also on who is considered a significant enough public to be adequately accounted for.
      Citation: Big Data & Society
      PubDate: 2021-03-10T11:56:42Z
      DOI: 10.1177/2053951721996046
      Issue No: Vol. 8, No. 1 (2021)
       
  • Blockchain imperialism in the Pacific

    • Authors: Olivier Jutel
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      The rise of blockchain as a techno-solution in the development sector underscores the critical imbalances of data power under ‘computational capitalism’ (Beller, 2018). This article will consider the political economy of techno-solutionist and blockchain discourses in the developing world, using as its object of study blockchain projects in Pacific Island nations. Backed by US State Department soft power initiatives such as Tech Camp, these projects inculcate tech-driven notions of economic and political development, or ICT4D, while opening up new terrains for data accumulation and platform control. Blockchain developers in search of proof of concept have found the development sector a fecund space for tech experimentation as they leverage a desire for tech-development and exploit regulatory weakness. The material implications of blockchain projects and discourse have been to create governance solutions which bypass the developing world state as a largely corrupting intermediary. In the Pacific, this has meant blockchain supply-chain management systems, proprietary financial innovation in humanitarian relief and an Asian Development Bank project to manage indigenous Fijian lands exclusively on the blockchain. In all these instances, discourses of solutionism, innovation and data empowerment have been deployed in aid of blockchain cartographies of control.
      Citation: Big Data & Society
      PubDate: 2021-02-19T06:55:00Z
      DOI: 10.1177/2053951720985249
      Issue No: Vol. 8, No. 1 (2021)
       
  • Encrypting human rights: The intertwining of resistant voices in the UK
           state surveillance debate

    • Authors: Amy Stevens, James Allen-Robertson
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      The Snowden revelations in 2013 redrew the lines of debate surrounding surveillance, exposing the extent of state surveillance across multiple nations and triggering legislative reform in many. In the UK, this was in the form of the Investigatory Powers Act (2016). As a contribution to understanding resistance to expanding state surveillance activities, this article reveals the intertwining of diverse interests and voices which speak in opposition to UK state surveillance. Through a computational topic modelling-based mixed methods analysis of the submissions made to the draft Investigatory Powers Bill consultation, the article demonstrates the diversity and intersection of discourses within different actor groups, including civil society and the technology industry. We demonstrate that encryption is a key issue for these groups, and is additionally conflated with a human rights discourse. This serves to unite seemingly disparate interests by imbuing encryption with a responsibility for the protection of human rights, but also threatens to legitimate corporate interests and distract from their own data-driven activities of surveillance capitalism.
      Citation: Big Data & Society
      PubDate: 2021-02-18T05:07:45Z
      DOI: 10.1177/2053951720985304
      Issue No: Vol. 8, No. 1 (2021)
       
  • Making sense of algorithms: Relational perception of contact tracing and
           risk assessment during COVID-19

    • Authors: Chuncheng Liu, Ross Graham
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      Governments and citizens of nearly every nation have been compelled to respond to COVID-19. Many measures have been adopted, including contact tracing and risk assessment algorithms, whereby citizen whereabouts are monitored to trace contact with other infectious individuals in order to generate a risk status via algorithmic evaluation. Based on 38 in-depth interviews, we investigate how people make sense of Health Code (jiankangma), the Chinese contact tracing and risk assessment algorithmic sociotechnical assemblage. We probe how people accept or resist Health Code by examining their ongoing, dynamic, and relational interactions with it. Participants display a rich variety of attitudes toward privacy and surveillance, ranging from fatalism to the possibility of privacy to trade-offs for surveillance in exchange for public health, which is mediated by the perceived effectiveness of Health Code and changing views on the intentions of institutions who deploy it. We show how perceived competency varies not just on how well the technology works, but on the social and cultural enforcement of various non-technical aspects like quarantine, citizen data inputs, and cell reception. Furthermore, we illustrate how perceptions of Health Code are nested in people’s broader interpretations of disease control at the national and global level, and unexpectedly strengthen the Chinese authority’s legitimacy. None of the Chinese public, Health Code, or people’s perceptions toward Health Code are predetermined, fixed, or categorically consistent, but are co-constitutive and dynamic over time. We conclude with a theorization of a relational perception and methodological reflections to study algorithmic sociotechnical assemblages beyond COVID-19.
      Citation: Big Data & Society
      PubDate: 2021-02-18T05:05:45Z
      DOI: 10.1177/2053951721995218
      Issue No: Vol. 8, No. 1 (2021)
       
  • Digital failure: Unbecoming the “good” data subject through entropic,
           fugitive, and queer data

    • Authors: Lauren E Bridges
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      This paper explores the political potential of digital failure as a refusal to work in service of today’s dataveillance society. Moving beyond criticisms of flawed digital systems, this paper traces the moments of digital failure that seek to break, rather than fix, existing systems. Instead, digital failure is characterized by pesky data that sneaks through the cracks of digital capitalism and dissipates into the unproductive; it supports run-away data prone to misidentifications by digital marketers, coders, and content moderators; and it celebrates data predisposed to “back-talk” with playful irreverence toward those that seek to bring order through normative categorization and moderation. I call these data entropic, fugitive, and queer and explore their mischievous practices through three case studies: the unaccountable data in identity resolution, public shaming of the ImageNet training data, and reading practices of sex worker and influencer, @Charlieshe. Together these case studies articulate the political potential of digital failure as a process of unbecoming the good data subject by pushing past the margins of legibility, knowability, and thinkability, to reveal what is made illegible, unknowable, and unthinkable to data’s seeing eye. As predictive analytics, automated decision-systems, and artificial intelligence take on increasingly central roles in public governance, digital failure reveals how data itself is a flawed concept prone to political abuse and social engineering to protect the interests of the powerful, while keeping those marginalized over-surveilled and underrepresented.
      Citation: Big Data & Society
      PubDate: 2021-02-12T05:25:56Z
      DOI: 10.1177/2053951720977882
      Issue No: Vol. 8, No. 1 (2021)
       
  • Big data for climate action or climate action for big data'

    • Authors: Maria I Espinoza, Melissa Aronczyk
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      Under the banner of “data for good,” companies in the technology, finance, and retail sectors supply their proprietary datasets to development agencies, NGOs, and intergovernmental organizations to help solve an array of social problems. We focus on the activities and implications of the Data for Climate Action campaign, a set of public–private collaborations that wield user data to design innovative responses to the global climate crisis. Drawing on in-depth interviews, first-hand observations at “data for good” events, intergovernmental and international organizational reports, and media publicity, we evaluate the logic driving Data for Climate Action initiatives, examining the implications of applying commercial datasets and expertise to environmental problems. Despite the increasing adoption of Data for Climate Action paradigms in government and public sector efforts to address climate change, we argue Data for Climate Action is better seen as a strategy to legitimate extractive, profit-oriented data practices by companies than a means to achieve global goals for environmental sustainability.
      Citation: Big Data & Society
      PubDate: 2021-02-11T09:31:32Z
      DOI: 10.1177/2053951720982032
      Issue No: Vol. 8, No. 1 (2021)
       
  • The cancer multiple: Producing and translating genomic big data into
           oncology care

    • Authors: Tiên-Dung Hà, Peter A. Chow-White
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      This article provides an ethnographic account of how Big Data biology is produced, interpreted, debated, and translated in a Big Data-driven cancer clinical trial, entitled “Personalized OncoGenomics,” in Vancouver, Canada. We delve into epistemological differences between clinical judgment, pathological assessment, and bioinformatic analysis of cancer. To unpack these epistemological differences, we analyze a set of gazes required to produce Big Data biology in cancer care: clinical gaze, molecular gaze, and informational gaze. We are concerned with the interactions of these bodily gazes and their interdependence on each other to produce Big Data biology and translate it into clinical knowledge. To that end, our central research questions ask: How do medical practitioners and data scientists interact, contest, and collaborate to produce and translate Big Data into clinical knowledge' What counts as actionable and reliable data in cancer decision-making' How does the explicability or translatability of genomic Big Data come to redefine or contradict medical practice' The article contributes to current debates on whether Big Data engenders new questions and approaches to biology, or Big Data biology is merely an extension of early modern natural history and biology. This ethnographic account will highlight how genomic Big Data, which underpins the mechanism of personalized medicine, allows oncologists to understand and diagnose cancer in a different light, but it does not revolutionize or disrupt medical oncology on an institutional level. Rather, personalized medicine is interdependent on different styles of (medical) thought, gaze, and practice to be produced and made intelligible.
      Citation: Big Data & Society
      PubDate: 2021-02-09T05:53:41Z
      DOI: 10.1177/2053951720978991
      Issue No: Vol. 8, No. 1 (2021)
       
  • Corrigendum to Editorial: The personalisation of insurance: Data,
           behaviour and innovation

    • Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.

      Citation: Big Data & Society
      PubDate: 2021-02-05T05:40:55Z
      DOI: 10.1177/2053951720988208
      Issue No: Vol. 8, No. 1 (2021)
       
  • ‘It depends on your threat model’: the anticipatory dimensions of
           resistance to data-driven surveillance

    • Authors: Becky Kazansky
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      While many forms of data-driven surveillance are now a ‘fact’ of contemporary life amidst datafication, obtaining concrete knowledge of how different institutions exploit data presents an ongoing challenge, requiring the expertise and power to untangle increasingly complex and opaque technological and institutional arrangements. The how and why of potential surveillance are thus wrapped in a form of continuously produced uncertainty. How then, do affected groups and individuals determine how to counter the threats and harms of surveillance' Responding to an interdisciplinary concern with agency amidst datafication, this article explores what I term ‘anticipatory data practices’ – future-oriented practices which provide a concrete anchor and a heuristic for action amidst the persistent uncertainties of life with data. This article traces how anticipatory data practices have emerged within civil society practices concerned with countering the harms of surveillance and data exploitation. The mixed-method empirical analysis of this article draws from 50 interviews with digital security educators and technology developers; participant observation at 12 civil society events between 2016 and 2019 and the textual analysis of 100 security manuals produced by NGOs and grassroots groups.
      Citation: Big Data & Society
      PubDate: 2021-01-29T08:09:52Z
      DOI: 10.1177/2053951720985557
      Issue No: Vol. 8, No. 1 (2021)
       
  • Archival strategies for contemporary collecting in a world of big data:
           Challenges and opportunities with curating the UK web archive

    • Authors: Nicola Jayne Bingham, Helena Byrne
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      In this contribution, we will discuss the opportunities and challenges arising from memory institutions' need to redefine their archival strategies for contemporary collecting in a world of big data. We will reflect on this topic by critically examining the case study of the UK Web Archive, which is made up of the six UK Legal Deposit Libraries: the British Library, National Library of Scotland, National Library of Wales, Bodleian Libraries Oxford, Cambridge University Library and Trinity College Dublin. The UK Web Archive aims to archive, preserve and give access to the UK web space. This is achieved through an annual domain crawl, first undertaken in 2013, in addition to more frequent crawls of key websites and specially curated collections which date back as far as 2005. These collections reflect important aspects of British culture and events that shape society. This commentary will explore a number of questions including: what heritage is captured and what heritage is instead neglected by the UK Web archive' What heritage is created in the form of new data and what are its properties' What are the ethical issues that memory institutions face when developing these web archiving practices' What transformations are required to overcome such challenges and what institutional futures can we envisage'
      Citation: Big Data & Society
      PubDate: 2021-01-29T08:08:52Z
      DOI: 10.1177/2053951721990409
      Issue No: Vol. 8, No. 1 (2021)
       
  • The algorithm audit: Scoring the algorithms that score us

    • Authors: Shea Brown, Jovana Davidovic, Ali Hasan
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals for ethical assessment of algorithms are either too high level to be put into practice without further guidance, or they focus on very specific and technical notions of fairness or transparency that do not consider multiple stakeholders or the broader social context. In this article, we present an auditing framework to guide the ethical assessment of an algorithm. The audit instrument itself is comprised of three elements: a list of possible interests of stakeholders affected by the algorithm, an assessment of metrics that describe key ethically salient features of the algorithm, and a relevancy matrix that connects the assessed metrics to stakeholder interests. The proposed audit instrument yields an ethical evaluation of an algorithm that could be used by regulators and others interested in doing due diligence, while paying careful attention to the complex societal context within which the algorithm is deployed.
      Citation: Big Data & Society
      PubDate: 2021-01-28T07:42:15Z
      DOI: 10.1177/2053951720983865
      Issue No: Vol. 8, No. 1 (2021)
       
  • Data sovereignty: A review

    • Authors: Patrik Hummel, Matthias Braun, Max Tretter, Peter Dabrock
      Abstract: Big Data & Society, Volume 8, Issue 1, January-Jun 2021.
      New data-driven technologies yield benefits and potentials, but also confront different agents and stakeholders with challenges in retaining control over their data. Our goal in this study is to arrive at a clear picture of what is meant by data sovereignty in such problem settings. To this end, we review 341 publications and analyze the frequency of different notions such as data sovereignty, digital sovereignty, and cyber sovereignty. We go on to map agents they concern, in which context they appear, and which values they allude to. While our sample reveals a considerable degree of divergence and an occasional lack of clarity about intended meanings of data sovereignty, we propose a conceptual grid to systematize different dimensions and connotations. Each of them relates in some way to meaningful control, ownership, and other claims to data articulated by a variety of agents ranging from individuals to countries. Data sovereignty alludes to a nuanced mixture of normative concepts such as inclusive deliberation and recognition of the fundamental rights of data subjects.
      Citation: Big Data & Society
      PubDate: 2021-01-22T06:22:15Z
      DOI: 10.1177/2053951720982012
      Issue No: Vol. 8, No. 1 (2021)
       
 
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