Data Science And Social Research: Epistemology, Methods, Technology And Applications (studies In Classification, Data Analysis, And Knowledge Organization)
by N. Carlo Lauro /
2017 / English / PDF
10.8 MB Download
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.
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.
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.
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.