Social data science is an interdisciplinary field that addresses social science problems by applying or designing computational and digital methods. As the name implies, Social Data Science is located primarily within the social science, but it relies on technical advances in fields like data science, network science, and computer science. The data in Social Data Science is always about human beings and derives from social phenomena, and it could be structured data (e.g. surveys) or unstructured data (e.g. digital footprints). The goal of Social Data Science is to yield new knowledge about social networks, human behavior, cultural ideas and political ideologies.
A social data scientist combines domain knowledge and specialized theories from the social sciences with programming, statistical and other data analysis skills.
Methods
Social data science employs a wide range of quantitative – both established methods in social science as well as new methods developed in computer science and interdisciplinary data science fields such as natural language processing (NLP) and network science.
Social Data Science is closely related to
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Source: Wikipedia
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