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E-raamat: Digital Social Research

  • Formaat: EPUB+DRM
  • Ilmumisaeg: 25-Oct-2019
  • Kirjastus: Polity Press
  • Keel: eng
  • ISBN-13: 9781509529339
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  • Formaat: EPUB+DRM
  • Ilmumisaeg: 25-Oct-2019
  • Kirjastus: Polity Press
  • Keel: eng
  • ISBN-13: 9781509529339
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To analyse social and behavioural phenomena in our digitalized world, it is necessary to understand the main research opportunities and challenges specific to online and digital data. This book presents an overview of the many techniques that are part of the fundamental toolbox of the digital social scientist. 

Placing online methods within the wider tradition of social research, Giuseppe Veltri discusses the principles and frameworks that underlie each technique of digital research. This practical guide covers methodological issues such as dealing with different types of digital data, construct validity, representativeness and big data sampling. It looks at different forms of unobtrusive data collection methods (such as web scraping and social media mining) as well as obtrusive methods (including qualitative methods, web surveys and experiments). Special extended attention is given to computational approaches to statistical analysis, text mining and network analysis.

Digital Social Research will be a welcome resource for students and researchers across the social sciences and humanities carrying out digital research (or interested in the future of social research).

Arvustused

We need more books like this. With his far-reaching and accessible overview of the field, Giuseppe A. Veltri makes a very welcome contribution. Axel Bruns, Queensland University of Technology, and President of the Association of Internet Researchers 

Giuseppe A. Veltris innovative approach locates digital methods within the established canon of social research methodology, without the hyperbole that often surrounds such discussion. Students will learn about the essential principles of social scientific research and where new methods sit in relation to traditional methods. Nick Allum, Professor of Research Methodology, University of Essex

This is a timely and important book. Its real strength is that it moves beyond the how to to explain the why. This is achieved with clear language that makes the book of value to advanced undergraduates and postgraduates alike. Scott Wright, Associate Professor of Digital Media and Political Communication, University of Melbourne

Tables and Figures
x
Abbreviations xiii
Introduction 1(7)
1 Social Research Using Digital Data and Methods
8(28)
Self-Reported and Behavioural Data
8(5)
Big Data
13(5)
The Construct Validity Problem
18(6)
Representativeness and Access
24(4)
`Native' or Complex Digital Methods
28(2)
Digital Structured, Unstructured and Semi-structured Data
30(6)
2 Unobtrusive vs Obtrusive Methods
36(25)
Web Scraping and News Sources
39(5)
Social Media Data
44(4)
Collecting Data from APIs
48(3)
Understanding Social Media Data
51(7)
Tools and Instruments
58(3)
3 Online Obtrusive Data Collection Methods
61(63)
Online Qualitative Research Methods
61(19)
Online interviewing
65(4)
Online focus groups
69(4)
Asynchronous forms of group discussion
73(2)
Further approaches to digital qualitative data
75(5)
Further readings
80(1)
Web Surveys
80(21)
Visual design
85(6)
Data, paradata and metadata
91(3)
Sources of errors and potential problems
94(6)
New frontiers
100(1)
Further readings
101(1)
Experiments
101(15)
Random assignment
103(3)
Validity
106(1)
Internal validity
107(3)
External validity
110(1)
Ecological validity
111(1)
Main threats to validity
112(2)
Trade-offs between different forms of validity
114(2)
Randomized controlled trials
116(1)
Types of design
117(2)
Between-subject vs within-subject designs
118(1)
Online experiments
119(4)
Online experiments as field experiments
122(1)
Further readings
123(1)
4 Quantitative Data Analysis Reloaded
124(15)
Quantitative Analysis and Digital Data
124(4)
Conventional and Computational Approaches
128(2)
Further Differences
130(4)
Model-based Recursive Partitioning
134(4)
Further Readings
138(1)
5 Networks and Data
139(27)
Networks
139(2)
Key Concepts
141(10)
Basic Network Metrics
151(2)
Network-level Metrics
153(1)
Types of Networks
154(4)
Property of Networks
158(4)
Longitudinal Network Analysis
162(1)
Tools
163(2)
Further Readings
165(1)
6 Text Mining
166(27)
From Content Analysis to Text Mining
166(4)
Text Mining
170(3)
Text-mining Pre-processing Basic Concepts
173(3)
Parts of Speech Tagging
176(1)
Sentiment Analysis
176(6)
Topic Models
182(5)
Latent Dirichlet allocation
182(3)
Correlated topic model
185(1)
Latent semantic analysis
186(1)
Semantic Networks
187(2)
Tools
189(3)
Further Readings
192(1)
7 Final Remarks
193(6)
On Digital Social Research
193(6)
Notes 199(6)
References 205(17)
Index 222
Giuseppe A. Veltri, PhD, is Professor of Sociology at the University of Trento, Italy.