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Big Data Science for Criminology and the Social Sciences: From Case Studies to Theory


Reseña del editor There is an increasing prevalence of large and complex datasets within the social sciences, and notably criminology in recent years. This data explosion has led to the development of specialized techniques for extracting information from such data. This book presents an introduction to "Big Data Science" for criminology and the social sciences, taking a case study-based approach to explaining the concepts. The theory is introduced as needed to answer scientific questions based on real data problems in the application areas. Some R and Python code is included to give support with implementation of the methods.

Big Data Science for Criminology and the Social Sciences: From Case Studies to Theory: Amazon.es: Marcello Trovati, Fionn Murtagh, Richard Hill, Philip Hodgson, Philip Burton-Cartledge, Michael Teague, Charlotte Hargreaves: Libros en idiomas extranjeros
Big Data Science for Criminology and the Social Sciences: From Case Studies to Theory: Amazon.es: Marcello Trovati, Fionn Murtagh, Richard Hill, Philip Hodgson, Philip Burton-Cartledge, Michael Teague, Charlotte Hargreaves: Libros en idiomas extranjeros
Marcello Trovati, Fionn Murtagh, Richard Hill, Philip Hodgson, Philip Burton-Cartledge, Michael Teague, Charlotte Hargreaves,Big Data Science for Criminology and the Social Sciences: From Case Studies to Theory,Chapman and Hall/CRC,1498788653,LAW / Criminal Law / General,MATHEMATICS / Probability & Statistics / General,Mathematics/Probability & Statistics - General,Crime & criminology,Probability & statistics,Psychological methodology,ANF: Mathematics,Law,Non-Fiction,TEXT,data science,data science; knowledge discovery; networks; sampling; text mining; visualization,knowledge discovery,networks,sampling,text mining,visualization


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