engleski

Generation and Semantic Expansion of Impacts in Arts and Culture

The paper aims to offer a solution for the identification and annotation of impacts in the domain of arts and culture. We explore available (ex post) narratives of impactful interventions in society, such as those contained in the body of scientific papers dealing with related topics to arts and culture, and try to disentangle some meaningful descriptions of impact generation mechanisms, using NLP (Natural Language Processing) techniques based on semantic similarity principles. The typology of texts analysed so far are academic papers from peer reviewed journals being focused on the societal impacts of cultural policies and practices. However, the method easily lends itself to being extended to pilot studies and policy documents. Three main categories of societal impact - borrowed from the New European Agenda for Culture - have been considered: impacts on personal well- being, on social cohesion and on urban renovation. Based on prior literature findings, a collection of possible societal impacts was gathered in the form of 100 phrases of two up to eight words. Then we expanded the semantic neighbourhood of each impact utilising continuous space word representations by cosine similarity measures. We show that impacts can be clustered into well separated and defined groups of related concepts. This can be interpreted in two ways: first, the European Agenda points at three, largely independent, impact areas for cultural interventions, with little overlaps to one another ; second, little is left out of these categories, which could still be considered as a separate impact area. Finally, we show that proposed procedure can be successfully applied to the task of automatic annotation of documents in the domain of arts and culture.

Impacts of arts and culture ; Semantic similarity ; Word2vec embeddings ; Clustering

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