Authors:
Aikaterini Nikolaidou
;
Michalis Lazaridis
;
Theodoros Semertzidis
;
Apostolos Axenopoulos
and
Petros Daras
Affiliation:
Information Technologies Institute, CERTH, Thessaloniki and Greece
Keyword(s):
Social Media Analytics Forensic Platform, Heterogeneous Social Media Data, Ontology, Labeled Property Graph.
Related
Ontology
Subjects/Areas/Topics:
Applications and Case-studies
;
Artificial Intelligence
;
Domain Analysis and Modeling
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontology Matching and Alignment
;
Symbolic Systems
Abstract:
It is a challenge to aggregate and analyze data from heterogeneous social media sources not only for businesses and organizations but also for Law Enforcement Agencies. The latter’s core objectives are to monitor criminal and terrorist related activities and to identify the ”key players” in various networks. In this paper, a framework for homogenizing and exploiting data from multiple sources is presented. Moreover, as part of the framework, an ontology that reflects today’s social media perceptions is introduced. Data from multiple sources is transformed into a labeled property graph and stored in a graph database in a homogenized way based on the proposed ontology. The result is a cross-source analysis system where end-users can explore different scenarios and draw conclusions through a library of predefined query placeholders that focus on forensic investigation. The framework is evaluated on the Stormfront dataset, a radical right, web community. Finally, the benefits of applying
the proposed framework to discover and visualize the relationships between the Stormfront profiles are presented.
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