A Multidomain and Multilingual Conceptual Data Model for Online Reviews Representation

Marcirio Silveira Chaves, Winnie Picoto

Abstract

User-Generated Content (UGC) such as online reviews are freely available in the web. This kind of data has been used to support clients’ and managerial decision making in several industries, e.g. books, tourism or hospitality. However, the challenge is how to represent this information in a structured way in order to leverage on the information provided by the use of Web 2.0 applications. To deal with this challenge, models and metamodels have been used to support a set of concrete applications in several sub-domains into Computer Science and Information Systems body of knowledge (Karagiannis and Höfferer, 2006). This paper focuses on the model-driven engineering and introduces a new multidomain and multilingual conceptual data model to represent UGC. This model is based on a characterization of online reviews and aims to capture all the facets of these reviews. The characterization of the reviews’ sentences extends previous models (such as Martin and White, 2007; Ding et al., 2008; Liu, 2010). Applications build on the model proposed in this paper may allow in-depth analysis of the fine-grained and disperse knowledge existent in the UGC. Furthermore, as this model is domain-independent it can be used to represent multiple types of reviews.

References

  1. Attensity, 2012. Available at http://www.attensity.com. Last access: January 6, 2012.
  2. Bai, X., 2011. Predicting Consumer Sentiments from Online Reviews. Decision Support Systems 50(4), March, Elsevier Science, p. 732-742.
  3. Carvalho, E.; Chaves, M. S., 2012. Exploring User Generated Data Visualization in the Accommodation Sector. Proceedings of the 16th International Conference Information Visualisation, IEEE, Montpellier, France, 10-13 July.
  4. Casey W., Navendu G., and Shlomo A., 2005. Using Appraisal Groups for Sentiment Analysis. In Proceedings of the 14th ACM International Conference on Information and Knowledge management (CIKM 7805). ACM, New York, NY, USA, 625-631.
  5. Chaves, M. S.; Gomes, R. and Pedron, C., 2012. Decision making based on Web 2.0 Data: The Small and Medium Hotel Management. Proceedings of the 20th European Conference on Information Systems, Barcelona, Spain, 10-13 June.
  6. Chaves, M. S.; Freitas, L. A.; Souza, M. and Vieira, R., 2012. PIRPO: An Algorithm to deal with Polarity in Portuguese Online Reviews from the Accommodation Sector. Proceedings of the 17th International Conference on Applications of Natural Language Processing to Information Systems (NLDB), Groningen, The Netherlands, 26-28 June.
  7. Chaves, M. S.; Rodrigues, C. and Silva, M. J., 2007. Data Model for Geographic Ontologies Generation. XATA2007 - XML: Aplicações e Tecnologias Associadas. Ramalho, José Carlos; Lopes, João Correia and Carriço, Luís (Eds.). 15-16 February, Lisbon, Portugal.
  8. Chaves, M. S.; Trojahn, Cássia and Pedron, Cristiane Drebes, 2012. A Framework for Customer Knowledge Management based on Social Semantic Web: A Hotel Sector Approach. In: Customer Relationship Management and the Social and Semantic Web: Enabling Cliens Conexus. Colomo-Palacios, Ricardo; Varajão, João and Soto-Acosta, Pedro (Eds.). p. 141- 157, Hershey, PA: IGI Global. ISBN: 978-161-35- 0044-6
  9. Chesley, P.; Vincent, B.; Xu, L. and Srihari R., 2006. Using Verbs and Adjectives to Automatically Classify Blog Sentiment. in AAAI Symposium on Computational Approaches to Analysing Weblogs (AAAI-CAAW), 27-29.
  10. Clarabridge, 2012. Sentiment and Text Analytics Software - Clarabridge. Available at http://clarabridge.com. Last access: January 6, 2012.
  11. Consoli, D.; Diamantini, C. and Potena, D., 2009. Affective Algorithm to Polarize Customer Opinions. Proceedings of the 11th International Conference on Enterprise Information Systems, Volume HCI, ICEIS (5), Milan, Italy, May 6-10, 157-160.
  12. Ding, X., Liu, B., and Yu, P. S., 2008. A Holistic Lexiconbased Approach to Opinion Mining. Proceedings of the Conference on Web Search and Web Data Mining (WSDM) - ACM, Palo Alto, California, USA, p. 231- 240.
  13. EC, (2012). European Comission: Enterprise and Industry. Small and Medium-sized Enterprises (SMEs) Fact and Figures about the EÝs Small and Medium Enterprise. Available at http://ec.europa.eu/enterprise/policies/sme /facts-figures-analysis/index_en.htm. Last access: January 8, 2012.
  14. Hu, M.; Liu, B., 2004. Mining and Summarizing Customer Reviews. Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'04), August 22-25, Seatle, WA, USA, p. 168-177.
  15. Karagiannis, D.; Höfferer, P., 2006. Metamodels in Action: An overview. Proceedings of the First International Conference on Software Paradigm Trends (ICSOFT), INSTICC Press, Setúbal Portugal, September 11-14. ISBN: 972-8865-69-4
  16. Khan, K., Baharudin, B. B., Khan, A. and Fazal_e_Malik, 2010. Automatic Extraction of Features and OpinionOriented Sentences from Customer Reviews. World Academy of Science, Engeneering and Technology, Issue 62, February. ISSN:1307-6892.
  17. Liu, B., 2010. Sentiment Analysis and Subjectivity. In Handbook of Natural Language Processing, Second Edition, Eds: N. Indurkhya and F. J. Damerau), CRC Press, Taylor and Francis Group, Boca Raton, FL. Chapter 28.
  18. Martin, J. R. and White, P. R. R., 2007, The Language of Evaluation, Appraisal in English. Palgrave Macmillan, First edition, London & New York, 256 pages.
  19. OMG, 1999. Unified Modeling Language Specification version 1.3. Technical Report, Object Management Group.
  20. Schmidt, D. C., 2006. Model-driven Engineering. IEEE Computer 39(2), February, p. 25-31.
  21. Synthesio, 2012. Synthesio. Available at http://synthesio. com. Last access: April 30, 2012.
  22. SocialMetricx, 2012. Socialmetrix - Social Media Analytics for serious decision making. Available at http://www.socialmetrix.com. Last access: January 6, 2012.
  23. Tromp, E., 2011. Multilingual Sentiment Analysis on Social Media. Master's Theisis. Department of Mathematics and Computer Science, Eindhoven University of Technology.
  24. Turney, P., 2002. Thumbs Up or Thumbs Downs? Semantic Orientation Applied tio Unsupervised Classification of Reviews. Proceedings of the 40th Annual Meeting of the ACL, Philadelphia, July, p. 417- 424.
  25. van Gigch, J. P., 1991. System Design Modeling and Metamodeling. Plenum, First edition. July, 453 pages. ISBN: 0306437406.
  26. Whitelaw, C.; Garg, N. e Argamon, S., 2005. Using Appraisal Groups for Sentiment Analysis. In Proceedings of the 14th ACM International Conference on Information and Knowledge Management (CIKM 7805). ACM, New York, NY, USA, p. 625?631.
  27. Wilson, T., 2008. Fine-Grained Subjectivity Analysis. PhD Dissertation, Intelligent Systems Program, University of Pittsburgh.
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Paper Citation


in Harvard Style

Silveira Chaves M. and Picoto W. (2012). A Multidomain and Multilingual Conceptual Data Model for Online Reviews Representation . In Proceedings of the 7th International Conference on Software Paradigm Trends - Volume 1: ICSOFT, ISBN 978-989-8565-19-8, pages 14-23. DOI: 10.5220/0004021800140023


in Bibtex Style

@conference{icsoft12,
author={Marcirio Silveira Chaves and Winnie Picoto},
title={A Multidomain and Multilingual Conceptual Data Model for Online Reviews Representation},
booktitle={Proceedings of the 7th International Conference on Software Paradigm Trends - Volume 1: ICSOFT,},
year={2012},
pages={14-23},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004021800140023},
isbn={978-989-8565-19-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Software Paradigm Trends - Volume 1: ICSOFT,
TI - A Multidomain and Multilingual Conceptual Data Model for Online Reviews Representation
SN - 978-989-8565-19-8
AU - Silveira Chaves M.
AU - Picoto W.
PY - 2012
SP - 14
EP - 23
DO - 10.5220/0004021800140023