Discovering Mobility Patterns of Instagram Users through Process Mining Techniques

C. Diamantini, Laura Genga, F. Marozzo, D. Potena, Paolo Trunfio
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引用次数: 9

Abstract

Every day a huge amount of data is generated by users of social media platforms, like Facebook, Twitter and so on. Analyzing data posted by people interested in a given topic or event allows inferring patterns and trends about people behaviors on a very large scale. These posts are often geotagged, this way enabling mobility pattern analysis. In this work, we investigate the use of Process Mining techniques to support the discovery and the analysis of mobility patterns of social media users. We discuss the results obtained analyzing posts of Instagram users who visited EXPO 2015, the Universal Exposition hosted in Milan, Italy, from May to October 2015.
通过流程挖掘技术发现Instagram用户的移动模式
每天,Facebook、Twitter等社交媒体平台的用户都会产生大量的数据。分析对特定话题或事件感兴趣的人发布的数据,可以在很大程度上推断人们行为的模式和趋势。这些帖子通常带有地理标签,这样就可以进行移动模式分析。在这项工作中,我们研究了使用过程挖掘技术来支持发现和分析社交媒体用户的移动模式。我们讨论了2015年5月至10月在意大利米兰举办的世博会(EXPO 2015)的Instagram用户的帖子分析结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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