Data Science and Social Research: Epistemology, Methods, Technology and Applications

In: Studies in Classification, Data Analysis, and Knowledge Organization Ser

Abstract

Intro -- Preface -- Contents -- 1 Introduction -- References -- Epistemology -- 2 On Data, Big Data and Social Research. Is It a Real Revolution? -- Abstract -- 1 Data-Bases Are not a Repository -- 2 Some Consequences for Building a Data Science for Social Research -- References -- 3 New Data Science: The Sociological Point of View -- Abstract -- 1 The Reframing of Social Sciences -- 2 Data as Signification Acts -- 3 Data Culture, Data Assemblage and Data Science -- 4 Sense Making, Small Decisions and Social Actors -- 5 Final Remarks -- References -- 4 Data Revolutions in Sociology -- Abstract -- References -- 5 Blurry Boundaries: Internet, Big-New Data, and Mixed-Method Approach -- Abstract -- 1 Introduction -- 2 New Contexts and New Data -- 3 The Study of the Online Textual Data -- 3.1 What Is New in Approaches and Analytics? -- 3.2 Concerns and Boundaries -- 4 Open Questions -- References -- 6 Social Media and the Challenge of Big Data/Deep Data Approach -- Abstract -- 1 The Field of Observation: The Nature of the Data and the Perspective of Collection -- 2 Computational Social Sciences and Big Data: New Research Questions -- 3 Big Data: Critical Issues -- 3.1 The Contingency of the UGC: The Dimension of Time Is Relevant -- 3.2 The Architecture of the Platforms Counts -- 3.3 Making Sense of Network -- 3.4 Deep Data and the Context of the Facts -- 4 Conclusions -- References -- 7 Governing by Data: Some Considerations on the Role of Learning Analytics in Education -- Abstract -- 1 Introduction -- 2 The Transformative Power of Data -- 3 System of Measurement -- 3.1 Description -- 3.2 Prediction/Prescription -- 3.3 Accountability -- 4 Culture of Evidence -- 4.1 Short Circuits -- 4.2 Collateral Risks -- 4.3 Methods -- 5 System of Influence -- 5.1 Hybrid Actors -- 5.2 Software Space -- 5.3 Transactional Pedagogies

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Buch(elektronisch)#12017

Data science and social research: epistemology, methods, technology and applications

In: Studies in classification, data analysis, and knowledge organization

Lauro, N. C; Amaturo, E; Grassia, Maria Gabriella; Aragona, B; Marino, Marina

Lauro, N. C; Amaturo, E; Grassia, Maria Gabriella; Aragona, B; Marino, Marina

Abstract

This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources. This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in statistical institutes and offices.--

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