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Advisor(s)
Abstract(s)
Advances in digital sensors and Information flow have created
an abundance of data generated by users under various emotional
states in different situations. Although this opens up a new facet in
spatial research, the large amount of data makes it difficult to analyze and obtain complete and comprehensive information leading
to an increase in the demand for sentiment analysis. In this study,
the Canadian National Research Council (NRC) of Sentiment and
Emotion Lexicon (EmoLex) was used, based on data from the
social network Twitter (now X), thus enabling the identification
of the places in Lisbon where both positive and negative sentiment
prevails. From the results obtained, the Portuguese are happy in
spaces associated with leisure and consumption, such as museums, event venues, gardens, shopping centres, stores, and restaurants. The high score of words associated with negative sentiment
have more bias, since the lexicon sometimes has difficulties to
identify the context in which the word appears, ending up giving
it a negative score (e.g., war, terminal).
Description
Keywords
Sentiment analysis Lexicon approach Twitter Emotion Lisbon
Pedagogical Context
Citation
Betco, I., Ribeiro, A. I., Vale, D. S., Encalada-Abarca, L., Viana, C. M. & Rocha, J. (2025). Sentiment analysis using a lexicon-based approach in Lisbon, Portugal. Geospatial Health, 20, 1344. https://doi.org/10.4081/gh.2025.1344
Publisher
Page Press Publications