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. 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.
