Paper by William Aboucaya, Sonia Guehis and Rafael Angarita: “Online consultation platforms have improved the possibilities for citizens to have an input on public decision making. However, and especially at large scale, identification of the topics discussed and entities evoked has been identified as difficult for both citizens and platform administrators. In this paper, we leverage topic modeling, Named Entity Recognition and Linking and Semantic Textual Similarity to build a knowledge graph representing the different contributions to the République Numérique online citizen consultation in French language. The generated graph links the different proposals to topics identified in the consultation and to relevant DBpedia resources. The model proposed for representation of citizen consultations as knowledge graphs simplifies the retrieval of proposals focused on specific topics or mentioning a given entity. It also allows us to improve contextualization of important words in proposals by linking them to short definitions extracted from Wikipedia…(More)”.
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