Towards a General Architecture for Social Media Data Capture from a Multi-Domain Perspective

A. Bechini, Davide Gazzè, Andrea Marchetti, M. Tesconi
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引用次数: 5

Abstract

Online Social Media (OSM) platforms, such as Facebook or Twitter, are part of everyday life as powerful communication tools. They let users communicate anywhere anytime, and improve their own public image. For this reason, OSM are becoming more and more popular. Social Media data may play a crucial role in various decision-making processes. In this setting, research topics connected to monitoring of Social Media data are becoming increasingly important. The presented work is grounded on direct extensive experiences in data collection from different Social Media sources, and on the different methodologies applied in different reference domains (namely Online Reputation, Social Media Intelligence, and Opinion Mining in tourism). The crawlers developed for these domains provide valuable suggestions to elicit diverse requirements. After lessons learned in such fields, a general architecture for data capture from Social Media sources has been devised, and the interfaces of the composing modules have been defined. The resulting API can be exploited for an orderly re-engineering of crawling tools in the reference domains, thus implementing specific versions of the generic architecture.
多领域视角下的社交媒体数据捕获通用架构
在线社交媒体(OSM)平台,如Facebook或Twitter,是日常生活的一部分,是强大的沟通工具。他们让用户随时随地交流,提高自己的公众形象。由于这个原因,OSM正变得越来越流行。社交媒体数据可能在各种决策过程中发挥关键作用。在这种情况下,与社交媒体数据监控相关的研究课题变得越来越重要。所介绍的工作基于从不同社交媒体来源收集数据的直接广泛经验,以及在不同参考领域(即在线声誉,社交媒体情报和旅游业的意见挖掘)应用的不同方法。为这些领域开发的爬虫提供了有价值的建议,以引出不同的需求。在吸取了这些领域的经验教训之后,设计了一个用于从Social Media源获取数据的通用体系结构,并定义了组合模块的接口。生成的API可以用于参考域中爬行工具的有序重新工程,从而实现通用体系结构的特定版本。
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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