Thick Big Data - Doing Digital Social Sciences

Thick Big Data presents the available arsenal of new methods and tools for studying society both quantitatively and qualitatively, opening ground for the social sciences to take the lead in analysing digital behaviour. These tools are critical for students and researchers in the social sciences to successfully build mixed-methods approaches.

Sommario

• Preface


• 1: Introduction


• 2: Online Revolution


• 3: Methods of Researching Online Communities


• 4: Research Ethics


• Final Remarks

Info autore

Dariusz Jemielniak is Full Professor of Management at Kozminski University in Poland, where he heads the MINDS (Management in Networked and Digital Societies) department. He is also Associate Faculty at Berkman-Klein Center for Internet and Society at Harvard University and a member of The Wikimedia Foundation Board of Trustees. He is the author of Common Knowledge?: An Ethnography of Wikipedia (2014, Stanford University Press), winner of the Dorothy Lee Award for Outstanding Scholarship in the Ecology of Culture in 2015 and the Chair of the Polish Academy of Sciences academia award in 2016. His research focuses on open collaboration, peer production, and sharing economy.

Riassunto

Thick Big Data presents the available arsenal of new methods and tools for studying society both quantitatively and qualitatively, opening ground for the social sciences to take the lead in analysing digital behaviour. These tools are critical for students and researchers in the social sciences to successfully build mixed-methods approaches.

Dettagli sul prodotto

• Autori: Dariusz Jemielniak, Dariusz (Full Professor of Management Jemielniak, Jemielniak Dariusz
• Editore: Oxford University Press
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 25.03.2020
• EAN: 9780198839712
• ISBN: 978-0-19-883971-2
• Pagine: 208
• Categorie: Scienze sociali, diritto, economia > Economia > Tematiche generali, enciclopedie; Business and Management, SOCIAL SCIENCE / Research, BUSINESS & ECONOMICS / Management, BUSINESS & ECONOMICS / Research & Development, Business & management, Data analysis: general, Data science and analysis: general, Research methods: general, Data capture and analysis, Data Capture & Analysis