Big Data sources and methods for social and economic analyses

The Data Big Bang that the development of the ICTs has raised is providing us with a stream of fresh and digitized data related to how people, companies and other organizations interact. To turn these data into knowledge about the underlying behavior of the social and economic agents, organizations...

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Bibliographic Details
Published in:Technological forecasting & social change 2018-05, Vol.130, p.99-113
Main Authors: Blazquez, Desamparados, Domenech, Josep
Format: Article
Language:English
Subjects:
Behavior modification
Big Data
Big Data architecture
Data analysis
Data lifecycle
Data management
Data sources
Digitization
Economic analysis
Economic development
Economic forecasting
Forecasting
Governance
Information sources
Information technology
Life cycle analysis
Non-traditional analysis methods
Non-traditional data sources
Nowcasting
Organizations
Socio-economic data
Socioeconomic factors
Unstructured data
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Summary:The Data Big Bang that the development of the ICTs has raised is providing us with a stream of fresh and digitized data related to how people, companies and other organizations interact. To turn these data into knowledge about the underlying behavior of the social and economic agents, organizations and researchers must deal with such amount of unstructured and heterogeneous data. Succeeding in this task requires to carefully plan and organize the whole process of data analysis taking into account the particularities of the social and economic analyses, which include the wide variety of heterogeneous sources of information and a strict governance policy. Grounded on the data lifecycle approach, this paper develops a Big Data architecture that properly integrates most of the non-traditional information sources and data analysis methods in order to provide a specifically designed system for forecasting social and economic behaviors, trends and changes. •A taxonomy of non-traditional data sources according to the purpose of the agent generating the data is proposed.•A taxonomy of non-traditional analysis methods within a Big Data paradigm is proposed.•The existing data lifecycles are reviewed and extended into a complete and integrative proposal.•A Big Data architecture designed to forecast social and economic change is proposed.
ISSN:0040-1625
1873-5509
DOI:10.1016/j.techfore.2017.07.027