Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Scaling archived social media data analysis using a hadoop cloud

Conejero, Javier, Burnap, Peter, Rana, Omer Farooq and Morgan, Jeffrey 2013. Scaling archived social media data analysis using a hadoop cloud. Presented at: IEEE 6th International Conference on Cloud Computing (CLOUD), Santa Clara, CA, USA, 27 June - 2 July 2013. IEEE,

[img]
Preview
PDF - Accepted Post-Print Version
Download (267kB) | Preview

Abstract

Over recent years, there has been an emerging interest in supporting social media analysis for marketing, opin- ion analysis and understanding community cohesion. Social media data conforms to many of the categorisations attributed to “big-data” – i.e. volume, velocity and variety. Generally analysis needs to be undertaken over large volumes of data in an efficient and timely manner. A variety of computational infrastructures have been reported to achieve this. We present the COSMOS platform supporting sentiment and tension analysis on Twitter data, and demonstrate how this platform can be scaled using the OpenNebula Cloud environment with Map/Reduce-based analysis using Hadoop. In particular, we describe the types of system configurations that would be most useful from a performance perspective – i.e. how virtual machines in the infrastructure should be distributed to reduce variability in the analysis performance. We demonstrate the approach using a data set consisting of several million Twitter messages, analysed over two types of Cloud infrastructure.

Item Type: Conference or Workshop Item (Paper)
Date Type: Completion
Status: Unpublished
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: IEEE
Funders: ESRC
Related URLs:
Last Modified: 17 Mar 2017 04:19
URI: http://orca.cf.ac.uk/id/eprint/47387

Citation Data

Cited 3 times in Google Scholar. View in Google Scholar

Cited 9 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Full Text Downloads from ORCA for this publication

Top Downloads of this item by Country

Monthly Full Text Downloads of this item

More statistics for this item...