A paralleled big data algorithm with mapreduce framework for mining twitter data

Li Bing; Chun Chung Chan

doi:10.1109/BDCloud.2014.26

A paralleled big data algorithm with mapreduce framework for mining twitter data

Li Bing, Chun Chung Chan

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

2 Citations (Scopus)

Abstract

Some recent studies have suggested that public opinions expressed in social media may be correlated with various social issues. To find out what actually can be discovered in social media data, we need data mining. Data mining approaches that can handle massive amount of data have recently been referred to as big data algorithms. In this paper, we propose a big data algorithm to handling Twitter data mining. Furthermore, to ensure scalability, MapReduce framework is adopted to parallelize the proposed algorithm. Through the experiments, the potential of the proposed algorithm can be demonstrated. Computationally, the speed of execution can be shown to increase significantly despite increases in data set size. In fact, the acceleration ratio increases as the size of the dataset increases, and as the number of Data Nodes increases.

Original language	English
Title of host publication	Proceedings - 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 with the 7th IEEE International Conference on Social Computing and Networking, SocialCom 2014 and the 4th International Conference on Sustainable Computing and Communications, SustainCom 2014
Publisher	IEEE
Pages	121-128
Number of pages	8
ISBN (Electronic)	9781479967193
DOIs	https://doi.org/10.1109/BDCloud.2014.26
Publication status	Published - 1 Jan 2015
Event	4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 - Sydney, Australia Duration: 3 Dec 2014 → 5 Dec 2014

Conference

Conference	4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014
Country/Territory	Australia
City	Sydney
Period	3/12/14 → 5/12/14

Keywords

big data algorithm
data mining
MapReduce
social media
Twitter

ASJC Scopus subject areas

Software
Computer Networks and Communications

More information

10.1109/BDCloud.2014.26

Cite this

Bing, L., & Chan, C. C. (2015). A paralleled big data algorithm with mapreduce framework for mining twitter data. In Proceedings - 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 with the 7th IEEE International Conference on Social Computing and Networking, SocialCom 2014 and the 4th International Conference on Sustainable Computing and Communications, SustainCom 2014 (pp. 121-128). Article 7034776 IEEE. https://doi.org/10.1109/BDCloud.2014.26

Bing, Li ; Chan, Chun Chung. / A paralleled big data algorithm with mapreduce framework for mining twitter data. Proceedings - 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 with the 7th IEEE International Conference on Social Computing and Networking, SocialCom 2014 and the 4th International Conference on Sustainable Computing and Communications, SustainCom 2014. IEEE, 2015. pp. 121-128

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abstract = "Some recent studies have suggested that public opinions expressed in social media may be correlated with various social issues. To find out what actually can be discovered in social media data, we need data mining. Data mining approaches that can handle massive amount of data have recently been referred to as big data algorithms. In this paper, we propose a big data algorithm to handling Twitter data mining. Furthermore, to ensure scalability, MapReduce framework is adopted to parallelize the proposed algorithm. Through the experiments, the potential of the proposed algorithm can be demonstrated. Computationally, the speed of execution can be shown to increase significantly despite increases in data set size. In fact, the acceleration ratio increases as the size of the dataset increases, and as the number of Data Nodes increases.",

keywords = "big data algorithm, data mining, MapReduce, social media, Twitter",

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note = "4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 ; Conference date: 03-12-2014 Through 05-12-2014",

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Bing, L & Chan, CC 2015, A paralleled big data algorithm with mapreduce framework for mining twitter data. in Proceedings - 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 with the 7th IEEE International Conference on Social Computing and Networking, SocialCom 2014 and the 4th International Conference on Sustainable Computing and Communications, SustainCom 2014., 7034776, IEEE, pp. 121-128, 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014, Sydney, Australia, 3/12/14. https://doi.org/10.1109/BDCloud.2014.26

A paralleled big data algorithm with mapreduce framework for mining twitter data. / Bing, Li; Chan, Chun Chung.
Proceedings - 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 with the 7th IEEE International Conference on Social Computing and Networking, SocialCom 2014 and the 4th International Conference on Sustainable Computing and Communications, SustainCom 2014. IEEE, 2015. p. 121-128 7034776.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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Bing L, Chan CC. A paralleled big data algorithm with mapreduce framework for mining twitter data. In Proceedings - 4th IEEE International Conference on Big Data and Cloud Computing, BDCloud 2014 with the 7th IEEE International Conference on Social Computing and Networking, SocialCom 2014 and the 4th International Conference on Sustainable Computing and Communications, SustainCom 2014. IEEE. 2015. p. 121-128. 7034776 doi: 10.1109/BDCloud.2014.26

A paralleled big data algorithm with mapreduce framework for mining twitter data

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