Semantifying Twitter: the influenceTracker ontology

TL;DR

This paper introduces an ontology schema for semantifying Twitter data, enabling advanced semantic queries on social influence metrics and Twitter entities through a publicly accessible service.

Contribution

It presents a novel ontology schema and a semantic service for Twitter analytics, integrating influence measures with semantic querying capabilities.

Findings

Ontology schema for Twitter data

Semantic querying via SPARQL endpoint

Enhanced analysis of Twitter influence

Abstract

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.