Alexandria: Extensible Framework for Rapid Exploration of Social Media
July 23, 2015 Β· Declared Dead Β· π 2015 IEEE International Congress on Big Data
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Authors
Fenno F. Heath, Richard Hull, Elham Khabiri, Matthew Riemer, Noi Sukaviriya, Roman Vaculin
arXiv ID
1507.06667
Category
cs.IR: Information Retrieval
Cross-listed
cs.CY,
cs.HC,
cs.SI
Citations
10
Venue
2015 IEEE International Congress on Big Data
Last Checked
4 months ago
Abstract
The Alexandria system under development at IBM Research provides an extensible framework and platform for supporting a variety of big-data analytics and visualizations. The system is currently focused on enabling rapid exploration of text-based social media data. The system provides tools to help with constructing "domain models" (i.e., families of keywords and extractors to enable focus on tweets and other social media documents relevant to a project), to rapidly extract and segment the relevant social media and its authors, to apply further analytics (such as finding trends and anomalous terms), and visualizing the results. The system architecture is centered around a variety of REST-based service APIs to enable flexible orchestration of the system capabilities; these are especially useful to support knowledge-worker driven iterative exploration of social phenomena. The architecture also enables rapid integration of Alexandria capabilities with other social media analytics system, as has been demonstrated through an integration with IBM Research's SystemG. This paper describes a prototypical usage scenario for Alexandria, along with the architecture and key underlying analytics.
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