A Novel Query Language for Data Extraction from Social Networks

Francesco Buccafurri, Gianluca Lax, Lorenzo Musarella, Roberto Nardone

Abstract

Online Social Networks (OSNs) represent an important source of information since they manage a huge amount of data that can be used in many different contexts. Moreover, many people create and manage more than one social profile in the different available OSNs. The combination and the extraction of the set of data from contained in OSNs can produce a huge amount of additional information regarding both a single person and the overall society. Consequently, the data extraction from multiple social networks is a topic of growing interest. There are many techniques and technologies for data extraction from a single OSN, but there is a lack of simple query languages which can be used by programmers to retrieve data, correlate resources and integrate results from multiple OSNs. This work describes a novel query language for data extraction from multiple OSNs and the related supporting tool to edit and validate queries. With respect to existing languages, the designed language is general enough to include the variety of resources managed by the different OSNs. Moreover, thanks to the support of the editing environment, the language syntax can be customised by programmers to express searching criteria that are specific for a social network.

Download


Paper Citation