Linked Data supported Content Analysis for Sociology
Buchtitel: Proceedings of the 15th Int. Conf. on Semantic Systems (SEMANTiCS 2019)
Organisation: SEMANTiCS 2019
Philology and hermeneutics as the analysis and interpreta-tion of natural language text in written historical sources are the prede-cessors of modern content analysis and date back already to antiquity. Inempirical social sciences, especially in sociology, content analysis providesvaluable insights to social structures and cultural norms of the presentand past. With the ever growing amount of text on the web to analyze,also numerous computer-assisted text analysis techniques and tools weredeveloped in sociological research. However, existing methods often gowithout sufficient standardization. As a consequence, sociological textanalysis is lacking transparency, reproducibility and data re-usability.The goal of this paper is to show, how Linked Data principles and En-tity Linking techniques can be used to structure, publish and analyzenatural language text for sociological research to tackle these shortcom-ings. This is achieved on the use case of constitutional text documents ofthe Netherlands from 1884 to 2016 which represent an important contri-bution to the European cultural heritage. Finally, the generated data ismade available and re-usable as Linked Data not only for sociologists, butalso for all other researchers in the digital humanities domain interestedin the development of constitutions in the Netherlands.