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SWQL: A new domain-specific language for mining the social Web
Science of Computer Programming ( IF 1.5 ) Pub Date : 2021-03-16 , DOI: 10.1016/j.scico.2021.102642
Xiomarah Guzmán-Guzmán , Edward Rolando Núñez-Valdez , Raysa Vásquez-Reynoso , Angel Asencio , Vicente García-Díaz

Social media generate a massive amount of information each day. This information is usually generated by people and may be used for many studies. Social media mining is a growing discipline inside data mining, and the results have proven to be quite revealing. Getting the data to work with might seem to be the easiest task in the process, but it can be very challenging for people without programming knowledge.

Thus, there are numerous ways to extract information from social media, such as to use the network API, a Web scraper or specialized libraries. Using a straightforward and a cross social media query language we can hide the complexity of those mechanisms and gather information in a more efficient and easier way. This is because many social media share common elements, so we can create and unify queries to search, find and extract information from those platforms.

In this paper, we propose a domain-specific query language, specially designed to allow developers or domain experts to extract data from different social media. With this language we unify and simplify the mechanisms of data extraction from social networks such as Twitter and Facebook.



中文翻译:

SWQL:一种用于挖掘社交网络的特定于领域的新语言

社交媒体每天都会产生大量信息。此信息通常由人们生成,可用于许多研究。社交媒体挖掘是数据挖掘中越来越多的学科,并且事实证明,这一结果非常具有启发性。处理数据似乎是该过程中最简单的任务,但对没有编程知识的人来说可能是非常困难的。

因此,有很多方法可以从社交媒体中提取信息,例如使用网络API,Web抓取工具或专用库。使用直接的跨社会媒体查询语言,我们可以隐藏这些机制的复杂性,并以更有效,更轻松的方式收集信息。这是因为许多社交媒体共享共同的元素,因此我们可以创建和统一查询以从这些平台中搜索,查找和提取信息。

在本文中,我们提出了一种特定于领域的查询语言,该语言专门设计用于允许开发人员或领域专家从不同的社交媒体提取数据。使用这种语言,我们统一并简化了从Twitter和Facebook等社交网络提取数据的机制。

更新日期:2021-03-18
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