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2010 IEEE 3rd International Conference on Cloud Computing
Mining Twitter in the Cloud: A Case Study
Miami, Florida
July 05-July 10
ISBN: 978-0-7695-4130-3
| ASCII Text | x | ||
| Pieter Noordhuis, Michiel Heijkoop, Alexander Lazovik, "Mining Twitter in the Cloud: A Case Study," 2012 IEEE Fifth International Conference on Cloud Computing, pp. 107-114, 2010 IEEE 3rd International Conference on Cloud Computing, 2010. | |||
| BibTex | x | ||
| @article{ 10.1109/CLOUD.2010.59, author = {Pieter Noordhuis and Michiel Heijkoop and Alexander Lazovik}, title = {Mining Twitter in the Cloud: A Case Study}, journal ={2012 IEEE Fifth International Conference on Cloud Computing}, volume = {0}, year = {2010}, isbn = {978-0-7695-4130-3}, pages = {107-114}, doi = {http://doi.ieeecomputersociety.org/10.1109/CLOUD.2010.59}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2012 IEEE Fifth International Conference on Cloud Computing TI - Mining Twitter in the Cloud: A Case Study SN - 978-0-7695-4130-3 SP107 EP114 A1 - Pieter Noordhuis, A1 - Michiel Heijkoop, A1 - Alexander Lazovik, PY - 2010 KW - twitter KW - pagerank KW - amazon KW - data mining KW - web crawl VL - 0 JA - 2012 IEEE Fifth International Conference on Cloud Computing ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CLOUD.2010.59
Mining and analyzing data from social networks can be difficult because of the large amounts of data involved. Such activities are usually very expensive, as they require a lot of computational resources. With the recent success of cloud computing, data analysis is going to be more accessible due to easier access to less expensive computational resources. In this work we propose to use cloud computing services as a possible solution for analysis of large amounts of data. As a source for a large data set, we propose to use Twitter, yielding a graph with 50 million nodes and 1.8 billion edges. In this paper, we use computation of PageRank on Twitter’s social graph to investigate whether or not cloud computing, and Amazon cloud services1 in particular, can make these tasks more feasible and, as a side effect, whether or not PageRank provides a good ranking of Twitter users.
Index Terms:
twitter, pagerank, amazon, data mining, web crawl
Citation:
Pieter Noordhuis, Michiel Heijkoop, Alexander Lazovik, "Mining Twitter in the Cloud: A Case Study," cloud, pp.107-114, 2010 IEEE 3rd International Conference on Cloud Computing, 2010
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