Social Media Analysis for Crisis Informatics in the Cloud
Gerard Casas Saez

TL;DR
This paper proposes a cloud-based infrastructure for analyzing social media data during crises, focusing on fast, reliable, and scalable data processing and Twitter stream collection, with comparisons to existing systems.
Contribution
Introduces a novel cloud infrastructure for crisis social media analysis that improves reliability, scalability, and ease of maintenance over existing solutions.
Findings
Enhanced reliability of Twitter data collection using container orchestration
Improved query performance with cloud-based infrastructure
Better scalability and extensibility compared to traditional systems
Abstract
Social media analysis of disaster events is a critical task in crisis informatics research. It involves analyzing social media data generated during natural disasters, crisis events, or other mass convergence events. Due to the large data sets generated during these events, large scale software infrastructures need to be designed to analyze the data in a timely manner. Creating such infrastructures bring the need to maintain them and this becomes more difficult as these infrastructures grow larger and older. Maintenance costs are high since there is a need for queries to be handled quickly which require large amounts of computational resources to be available on demand 24 hours a day, seven days a week. In this thesis, I describe an alternative approach to designing a software infrastructure for analyzing unstructured data on the cloud while providing fast queries and with the…
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Taxonomy
TopicsPublic Relations and Crisis Communication · Complex Network Analysis Techniques · Data Visualization and Analytics
