CONCEPTS – LOCATIONS – EMOTIONS: SEMANTIC ANALYSIS AND VISUALIZATION OF CLIMATE CHANGE TEXTS
Keywords: Information Extraction, Ontology, Term Extraction, Named Entity Recognition, Sentiment Analysis, Emotion Detection, Semantic Information Visualization, Climate Change, Visualization
Abstract. Research on knowledge discovery in the geospatial domain currently focuses on semi-structured, even on unstructured rather than fully structured content. The attention has been put on the plethora of resources on the Web, such as html pages, news articles, blogs, social media etc. Semantic information extraction in geospatial-oriented approaches is further used for semantic analysis, search, and retrieval. The aim of this paper is to extract, analyse and visualize geospatial semantic information and emotions from texts on climate change. A collection of articles on climate change is used to demonstrate the developed approach. These articles describe environmental and socio-economic dimensions of climate change across the Earth, and include a wealth of information related to environmental concepts and geographic locations affected by it. The results are analysed in order to understand which specific human emotions are associated with environmental concepts and/or locations, as well as which environmental terms are linked to locations. For the better understanding of the above-mentioned information, semantic networks are used as a powerful visualization tool of the links among concepts – locations – emotions.