Buch, Englisch, 214 Seiten, Format (B × H): 129 mm x 198 mm
Reihe: The Basics
The Basics
Buch, Englisch, 214 Seiten, Format (B × H): 129 mm x 198 mm
Reihe: The Basics
ISBN: 978-1-041-08559-1
Verlag: Taylor & Francis Ltd
The emergence of big data has cut across research disciplines and applications - from architecture to urban planning; art history to economics. More and more fields that traditionally worked with qualitative (non-numeric) data now have access to relevant and robust big datasets, with big research potential.
This book introduces researchers to big data sources, concepts and applications, showing best practices in use and what we can and cannot do with it. It starts by defining the key distinctions between “data” and “big data”, practical considerations in moving to real world applications, and considers the methods and ways in which big data is used. It is not a technical book (of which there are many) but an introduction to a new research method, and includes case studies and applications from across disciplines (in the social sciences, arts and humanities). Readers are signposted to more detailed resources they can explore (e.g. software, datasets, tutorials) and how these have been used in research practice with various different formats of big data.
The authors take a non-technical approach to introducing big, novel and often complex data for applied research in the social sciences - targeted at those with primarily no background in using big data. It will be essential resource for students, researcher and practitioners.
Zielgruppe
Academic and Undergraduate Core
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken
- Sozialwissenschaften Soziologie | Soziale Arbeit Spezielle Soziologie Wissenssoziologie, Wissenschaftssoziologie, Techniksoziologie
- Geowissenschaften Geographie | Raumplanung Humangeographie
- Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
Weitere Infos & Material
'Section 1. Big Data for Research and Analysis. 1. What is Big Data? Properties, Characteristics and Structure. 2. Sources of Big Data. 3. Big Data for the Social Sciences. Section 2. From the Textbook to the Research Arena. 4. Critical Perspectives of Big Data Analysis. 5. The Right Data, the Right Methods, and the Right Application. 6. Practicalities for Big Data Analysis in the Social Sciences. Section 3. What to Do with Our Big Data. 7. Exploratory Big Data Analysis. 8. Visualising Big Data Graphically. 9. Inferential Statistics and Modelling (Causal Modelling). 10. Machine Learning and Pattern Detection (Predictive Modelling). Section 4. Big Data for Research Futures. 11. Artificial Intelligence. 12. Frontier Big Data Collection and Use. 13. Next Steps and Future Skills for the Big Data Researcher. End Matter. Book Summary.
