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Semantic Web Evaluation Challenges

SemWebEval 2015: Semantic Web Evaluation Challenges pp 244–250Cite as

Detecting Sentiment Polarities with Sentilo

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 548))

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

  1. 1.

    http://wit.istc.cnr.it/stlab-tools/sentilo.

  2. 2.

    http://wit.istc.cnr.it/stlab-tools/sentilo/service.

  3. 3.

    Dolce Ultra Lite Ontology. http://ontologydesignpatterns.org/ont/dul/DUL.owl.

  4. 4.

    http://www.cs.jhu.edu/~mdredze/datasets/sentiment/.

  5. 5.

    https://github.com/diegoref/ESWC-CLSA/blob/master/task1Challenge_testGold.zip.

  6. 6.

    http://wit.istc.cnr.it/stlab-tools/sentilo.

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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”.

Author information

Authors and Affiliations

  1. Semantic Technology Lab, ISTC-CNR, Rome, Catania, Italy

    Andrea Giovanni Nuzzolese & Misael Mongiovì

Authors
  1. Andrea Giovanni Nuzzolese
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  2. Misael Mongiovì
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Corresponding author

Correspondence to Andrea Giovanni Nuzzolese .

Editor information

Editors and Affiliations

  1. Inria, Sophia Antipolis, France

    Fabien Gandon

  2. INRIA Sophia-Antipolis Méditerranée, Sophia Antipolis, France

    Elena Cabrio

  3. Université Paris-Sorbonne, Paris, France

    Milan Stankovic

  4. École des Mines de Saint-Étienne, Saint-Étienne, France

    Antoine Zimmermann

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© 2015 Springer International Publishing Switzerland

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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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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25517-0

  • Online ISBN: 978-3-319-25518-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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