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Historical Content Analysis

So far, Human Language Technologies have not contributed in a substantial way to the development of Humanities even if they have evolved to a point where they can provide Humanities with analytic tools that go beyond text indexing. Some of the relevant technologies are: Named Entities recognition (e.g. identification of names of persons and locations within texts); extraction of semantic relations between entities (e.g. motion relations between persons and locations); temporal processing (i.e. identification of temporal expressions and events and extraction of relations between them); geographical information processing, key-concept extraction; distributional semantic analysis (i.e. quantification and categorization of semantic similarities between linguistic elements), sentiment analysis (i.e. determine the attitude of a writer with respect to some topic, identify the general polarity – positive, negative, neutral - of a text or of a statement).

In this context, the aim of the Digital Humanities group at FBK is to exploit text processing technologies to support research activities that are traditionally qualified as Humanistic, with a special attention to the Historical domain. The choice of this domain is strategic given that FBK includes a renowned history research group (Istituto Storico Italo-Germanico, ISIG) whose main research topic is the study of major historical transitions.

Application cases: 

The close collaboration with ISIG historians led us to use, as first case study, the complete corpus of writings of Alcide De Gasperi, one of the founders of the Italian Republic.

Objectives: 
  • Domain adaptations of FBK existing tools for content analysis to History;
  • Development of new tools and methodologies to study major historical transitions based on different information sources
Research topics: