Integroly: Automatic Knowledge Graph Population from Social Big Data in the Political Marketing Domain
Source abstract
Abstract
Social media sites have become platforms for conversation and channels to share experiences and opinions, promoting public discourse. In particular, their use has increased in political topics, such as citizen participation, proselytism, or political discussions. Political marketing involves collecting, monitoring, processing, and analyzing large amounts of voters’ data. However, the extraction, integration, processing, and storage of these torrents of relevant data in the political domain is a very challenging endeavor. In the recent years, the semantic technologies as ontologies and knowledge graphs (KGs) have proven effective in supporting knowledge extraction and management, providing solutions in heterogeneous data sources integration and the complexity of finding meaningful relationships. This work focuses on providing an automated solution for the population of a political marketing-related KG from Spanish texts through Natural Language Processing (NLP) techniques. The aim of the proposed framework is to gather significant data from semi-structured and unstructured digital media sources to feed a KG previously defined sustained by an ontological model in the political marketing domain. Twitter and political news sites were used to test the usefulness of the automatic KG population approach. The resulting KG was evaluated through 18 quality requirements, which ensure the optimal integration of political knowledge.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Semantic Web and Ontologies · Data Quality and Management · Biomedical Text Mining and Ontologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Escuela Internacional de Doctorado, University of Murcia, 30100 Murcia, Spain
Departamento de Informática y Sistemas, Faculty of Computer Science, University of Murcia, 30100 Murcia, Spain
Funding
European Union NextGenerationEU/PRTR · research project LaTe4PSP · Seneca Foundation—the Regional Agency for Science and Technology of Murcia (Spain)
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