Semantifying Twitter: the influenceTracker ontology
This work addresses the need for semantic analytics in social media for researchers and analysts, but it is incremental as it builds on existing ontology and semantic web techniques.
The authors tackled the problem of analyzing Twitter influence by proposing an ontology schema for semantic representation, resulting in a publicly available service that measures account influence through social activity and interaction metrics, with a SPARQL endpoint for advanced queries over RDFized Twitter entities.
In this paper, we propose an ontology schema towards semantification provision of Twitter social analytics. The ontology is deployed over a publicly available service that measures how influential a Twitter account is, by combining its social activity and interaction over Twittersphere. Apart from influential quantity and quality measures, the service provides a SPARQL endpoint where users can perform advance semantic queries through the RDFized Twitter entities (mentions, replies, hashtags, photos, URLs) over the semantic graph.