ESWC’14 Challenge on Concept-Level Sentiment Analysis

  • Diego Reforgiato RecuperoEmail author
  • Erik Cambria
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 475)


With the introduction of social networks, blogs, wikis, etc., the users’ behavior and their interaction in the Web have changed. As a consequence, people express their opinions and sentiments in a totally different way with respect to the past. All this information hinders potential business opportunities, especially within the advertising world, and key stakeholders need to catch up with the latest technology if they want to be at the forefront in the market. In practical terms, the automatic analysis of online opinions involves a deep understanding of natural language text, and it has been proved that the use of semantics improves the accuracy of existing sentiment analysis systems based on classical machine learning or statistical approaches. To this end, the Concept Level Sentiment Analysis challenge aims to provide a push in this direction offering the researchers an event where they can learn new approaches for the employment of Semantic Web features within their systems of sentiment analysis bringing to better performance and higher accuracy. The challenge aims to go beyond a mere word-level analysis of text and provides novel methods to process opinion data from unstructured textual information to structured machine-processable data.


Sentiment Analysis Opinion Word Polarity Detection Advance Task Annotate Dataset 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.CNRCataniaItaly
  2. 2.School of Computer EngineeringNanyang Technological UniversitySingaporeSingapore

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