Tracing and archiving ‘constructed’ data on Facebook pages and groups: reflections on fieldwork among young activists in Zimbabwe and South Africa

Mare, Admire

doi:10.1177/1468794117720973

Cited by 28 publications

(16 citation statements)

References 34 publications

(65 reference statements)

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“…This, of course, implies several ethical challenges that remain to be answered. In a study on student political activism in Zimbabwe and South Africa, Admire Mare mostly employed ethnographic data obtained through the Facebook groups and the pages of some relevant activist organizations (Mare 2017). In doing so, the author encountered several ethical issues, including those related to informed consent: beyond requesting the permission to conduct research from the administrators of the Facebook groups and pages, Mare also made his presence visible to all members in the collective profiles before following them as a friend and observing their interactions.…”

Section: Digital Methodsmentioning

confidence: 99%

Ethics in Political Science Research

Piccio

Mattoni

2019

Handbook of Research Ethics and Scientific Integrity

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Ethical dilemmas are much more common in political science than it is commonly envisaged. In this chapter we use the tripartite division between politics, polity, and policies and discuss the specific ethical concerns of these three core areas of research in political science. Additionally, we discuss some of the current and future challenges of research ethics in the field addressing ethics issues related to the use experiments, digital media, and the adoption of research designs that rest on action research. Overall, ethics considerations have becomeand will becomeincreasingly important also in political science.

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Section: Digital Methodsmentioning

confidence: 99%

Ethics in Political Science Research

Piccio

Mattoni

2019

Handbook of Research Ethics and Scientific Integrity

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“…Interpret the technology-centered categorization of data sources within a particular social scientific framework such as ethnographic methodology (Mare, 2017) or conversation analysis (Housley et al, 2017).…”

Section: Towards a Research Agenda For Big Social Datamentioning

confidence: 99%

Defining the big social data paradigm through a systematic literature review approach

Solazzo

Elia

Passiante

2021

JKM

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Purpose This study aims to investigate the Big Social Data (BSD) paradigm, which still lacks a clear and shared definition, and causes a lack of clarity and understanding about its beneficial opportunities for practitioners. In the knowledge management (KM) domain, a clear characterization of the BSD paradigm can lead to more effective and efficient KM strategies, processes and systems that leverage a huge amount of structured and unstructured data sources. Design/methodology/approach The study adopts a systematic literature review (SLR) methodology based on a mixed analysis approach (unsupervised machine learning and human-based) applied to 199 research articles on BSD topics extracted from Scopus and Web of Science. In particular, machine learning processing has been implemented by using topic extraction and hierarchical clustering techniques. Findings The paper provides a threefold contribution: a conceptualization and a consensual definition of the BSD paradigm through the identification of four key conceptual pillars (i.e. sources, properties, technology and value exploitation); a characterization of the taxonomy of BSD data type that extends previous works on this topic; a research agenda for future research studies on BSD and its applications along with a KM perspective. Research limitations/implications The main limits of the research rely on the list of articles considered for the literature review that could be enlarged by considering further sources (in addition to Scopus and Web of Science) and/or further languages (in addition to English) and/or further years (the review considers papers published until 2018). Research implications concern the development of a research agenda organized along with five thematic issues, which can feed future research to deepen the paradigm of BSD and explore linkages with the KM field. Practical implications Practical implications concern the usage of the proposed definition of BSD to purposefully design applications and services based on BSD in knowledge-intensive domains to generate value for citizens, individuals, companies and territories. Originality/value The original contribution concerns the definition of the big data social paradigm built through an SLR the combines machine learning processing and human-based processing. Moreover, the research agenda deriving from the study contributes to investigate the BSD paradigm in the wider domain of KM.

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“…Whilst such descriptive categories may be useful from the machine learning and information retrieval perspectives, they have no particular heuristic value from the perspective of social research and cannot be considered sufficient in many areas of practice. In order to obtain heuristic significance and explanatory value, the technology-centred categorisation of data sources needs to be interpreted within a particular social scientific framework such as ethnographic methodology (Mare, 2017), Conversation Analysis (CA) Housley et al, 2017b), and so on.…”

Section: Epistemological Revolution In Perspectivementioning

confidence: 99%

Conceptual frameworks for social and cultural Big Data analytics: Answering the epistemological challenge

Resnyansky

2019

Big Data & Society

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This paper aims to contribute to the development of tools to support an analysis of Big Data as manifestations of social processes and human behaviour. Such a task demands both an understanding of the epistemological challenge posed by the Big Data phenomenon and a critical assessment of the offers and promises coming from the area of Big Data analytics. This paper draws upon the critical social and data scientists' view on Big Data as an epistemological challenge that stems not only from the sheer volume of digital data but, predominantly, from the proliferation of the narrow-technological and the positivist views on data. Adoption of the social-scientific epistemological stance presupposes that digital data was conceptualised as manifestations of the social. In order to answer the epistemological challenge, social scientists need to extend the repertoire of social scientific theories and conceptual frameworks that may inform the analysis of the social in the age of Big Data. However, an 'epistemological revolution' discourse on Big Data may hinder the integration of the social scientific knowledge into the Big Data analytics.

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Tracing and archiving ‘constructed’ data on Facebook pages and groups: reflections on fieldwork among young activists in Zimbabwe and South Africa

Cited by 28 publications

References 34 publications

Ethics in Political Science Research

Ethics in Political Science Research

Defining the big social data paradigm through a systematic literature review approach

Conceptual frameworks for social and cultural Big Data analytics: Answering the epistemological challenge

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