Abstract
We present the tool used for the Concept-Level Sentiment Analysis Challenge ESWC-CLSA 2015 Task #1, concerning binary polarity detection of the sentiment of a sentence. Our tool is a little modification of Sentilo [7], an unsupervised, domain-independent system, previously developed by our group, that performs sentiment analysis by hybridizing natural language processing techniques with semantic web technologies. Sentilo is able to recognize the opinion holder and measure the sentiment expressed on topics and sub-topics. The knowledge extracted from the text is represented by means of an RDF graph. Holders and topics are linked to external knowledge. Sentilo is available as a REST service as well as a user-friendly demo.
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Notes
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Dolce Ultra Lite Ontology. http://ontologydesignpatterns.org/ont/dul/DUL.owl.
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Acknowledgement
The research leading to these results has received funding from the European Union Horizons 2020 – the Framework Programme for Research and Innovation (2014–2020) under grant agreement 643808 Project MARIO “Managing active and healthy aging with use of caring service robots”.
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Nuzzolese, A.G., Mongiovì, M. (2015). Detecting Sentiment Polarities with Sentilo. In: Gandon, F., Cabrio, E., Stankovic, M., Zimmermann, A. (eds) Semantic Web Evaluation Challenges. SemWebEval 2015. Communications in Computer and Information Science, vol 548. Springer, Cham. https://doi.org/10.1007/978-3-319-25518-7_21
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DOI: https://doi.org/10.1007/978-3-319-25518-7_21
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