摘 要：为了在社交媒体数据中找出相应内容，可以通过大数据挖掘的算法对社交媒体数据进行处理。文章提出了一种处理 Twitter 数据挖掘的大数据算法，为保证可扩展性，基于 MapReduce 框架提出并行数据挖掘的大数据算法。通过实验证明了该算法是高效的，在计算上，尽管数据集大小增加，执行速度仍然可以显著增加，并且加速比随着数据集大小的增加和数据节点数量的增加而增大。
关键词：社会媒体；数据挖掘；大数据算法；推特数据；MapReduce
DOI:10.19850/j.cnki.2096-4706.2021.18.009
中图分类号：TP311 文献标识码：A 文章编号：2096-4706（2021）18-0031-04
Research on a Parallel Big Data Algorithm Based on MapReduce Framework
FENG Zhanwei
(Heilongjiang International University, Haerbin 150025, China)
Abstract: In order to find out the corresponding content in the social media data, the social media data can be processed through the algorithm of big data mining. This paper proposes a big data algorithm for Twitter data mining. In order to ensure the scalability, we propose a parallel big data algorithm based on MapReduce framework. Experimental results show that the algorithm is efficient. Although the size of the data set increases, the execution speed can still significantly increase, and the speedup ratio increases with the increase of the size of the data set and the number of data nodes.
Keywords: social media; data mining; big data algorithm; twitter data; MapReduce
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作者简介：冯占伟（1981—），男，汉族，黑龙江巴彦人，讲师，硕士，研究方向：软件工程。