Climate Change, Disaster, and Sentiment Analysis over Social Media Mining

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Presented at the AGU Fall Meeting 2012

Abstract:

Accelerated climate change causes disasters and disrupts people living all over the globe. Disruptive climate events are often reflected in expressed sentiments of the people affected. Monitoring changes in these sentiments during and after disasters can reveal relationships between climate change and mental health. We developed a semantic web tool that uses linked data principles and semantic web technologies to integrate data from multiple sources and analyze them together. We are converting statistical data on climate change and disaster records obtained from the World Bank data catalog and the International Disaster Database into a Resource Description Framework (RDF) representation that was annotated with the RDF Data Cube vocabulary. We compare these data with a dataset of tweets that mention terms from the Emotion Ontology to get a sense of how disasters can impact the affected populations. This dataset is being gathered using an infrastructure we developed that extracts term uses in Twitter with controlled vocabularies. This data was also converted to RDF structure so that statistical data on the climate change and disasters is analyzed together with sentiment data. To visualize and explore relationship of the multiple data across the dimensions of time and location, we use the qb.js framework. We are using this approach to investigate the social and emotional impact of climate change. We hope that this will demonstrate the use of social media data as a valuable source of understanding on global climate change.

History

DateCreated ByLink
December 5, 2012
10:35:05
James McCuskerDownload

Related Projects:

Health on the Web
Principal Investigator: Deborah L. McGuinness and Joanne S. Luciano
Description: The Tetherless World Constellation's Health on the Web's primary goal is to explore the next generation web technology needed to improve health.

Related Research Areas:

Social Web
Lead Professor: Jim Hendler
Description: Social Web
Concepts: