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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. (More)

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Paper citation in several formats:
Nikolaidou, A.; Lazaridis, M.; Semertzidis, T.; Axenopoulos, A. and Daras, P. (2019). Forensic Analysis of Heterogeneous Social Media Data. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KEOD; ISBN 978-989-758-382-7; ISSN 2184-3228, SciTePress, pages 343-350. DOI: 10.5220/0008347803430350

@conference{keod19,
author={Aikaterini Nikolaidou. and Michalis Lazaridis. and Theodoros Semertzidis. and Apostolos Axenopoulos. and Petros Daras.},
title={Forensic Analysis of Heterogeneous Social Media Data},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KEOD},
year={2019},
pages={343-350},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008347803430350},
isbn={978-989-758-382-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KEOD
TI - Forensic Analysis of Heterogeneous Social Media Data
SN - 978-989-758-382-7
IS - 2184-3228
AU - Nikolaidou, A.
AU - Lazaridis, M.
AU - Semertzidis, T.
AU - Axenopoulos, A.
AU - Daras, P.
PY - 2019
SP - 343
EP - 350
DO - 10.5220/0008347803430350
PB - SciTePress