Sentiment Analysis for the Humanities: the Case of Historical Texts

In this paper we investigate the possibility to adapt existing lexical resources and Natural Language Processing (NLP) methodologies related to Sentiment Analysis (SA) to the historical domain. The corpus used for our research is the complete corpus of writings of Alcide De Gasperi (1881-1954), one of the founders of the Italian Republic, made of about 3,000 documents and 3,000,000 words. Using this corpus as a case study, two experiments have been carried out and are described in this paper. The aim of these experiments were the evaluation of i) how existing lexical resources for SA perform in the historical domain and ii) the feasibility of a sentiment annotation task for historical texts either for expert annotators and for crowdsourcing workers