We Feel Fine : Big Data Observations of Citizen Sentiment about State Institutions and Social Inclusion
Motivated by the significant decline in citizen’s trust in governments over the past decades, this paper explores how policy decision makers and researchers can use social media analytics to investigate trust, specifically the relationship among tr...
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| Format: | Brief |
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2015
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| Online Access: | http://documents.worldbank.org/curated/en/2015/09/25022358/feel-fine-big-data-observations-citizen-sentiment-state-institutions-social-inclusion http://hdl.handle.net/10986/22778 |
| Summary: | Motivated by the significant decline in
citizen’s trust in governments over the past decades, this
paper explores how policy decision makers and researchers
can use social media analytics to investigate trust,
specifically the relationship among trust in government,
trust in state institutions, and citizens’ collective
behavior. Analysis of these complex socio-political issues
using online social data requires a human in the inference
loop while also benefiting from computational methods to
handle large amounts of unstructured data and the inference
of relevant data features. To highlight the power of a
mixed-initiative visual analytics-data science approach,
this technical note describes the exploratory analysis work
undertaken for analysis of collections of Tweets from
Brazil, and describes further work that conceives data
science methods to assist the analysis process by supporting
definition of constructs of concepts of interest using
social media data, and assisting the evaluation of evidence
for hypotheses evaluation in an interactive-machine learning
fashion. The outcomes of this project aim to support social
sciences inquiry using observational social media data and
World Bank operations. |
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