Social media have become an invaluable source of data for a wide variety of tasks. Unfortunately, this data is hard to gather and process due to low amount of machine readable attributes, API limitations and noisiness. In this paper we propose a system that aligns knowledge base entries of people and organisations to the corresponding social media profiles. The motivation is twofold:(i) on the one hand, we facilitate processing of social media data by allowing the import of rich entity descriptions from knowledge bases;(ii) on the other hand, we are enabling an automatic enrichment of a knowledge base with additional data from the social media. We used this system to create a resource of 893,446 alignments between DBpedia entities and Twitter profiles. This resource allows, effectively, to connect Twitter to the Linked Open Data cloud.
Linking knowledge bases to social media profiles
Yaroslav Nechaev
;Francesco Corcoglioniti;Claudio Giuliano
2017-01-01
Abstract
Social media have become an invaluable source of data for a wide variety of tasks. Unfortunately, this data is hard to gather and process due to low amount of machine readable attributes, API limitations and noisiness. In this paper we propose a system that aligns knowledge base entries of people and organisations to the corresponding social media profiles. The motivation is twofold:(i) on the one hand, we facilitate processing of social media data by allowing the import of rich entity descriptions from knowledge bases;(ii) on the other hand, we are enabling an automatic enrichment of a knowledge base with additional data from the social media. We used this system to create a resource of 893,446 alignments between DBpedia entities and Twitter profiles. This resource allows, effectively, to connect Twitter to the Linked Open Data cloud.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.