Skip to main content
SpringerLink
Log in
Book cover

International Conference on Business Information Systems

BIS 2016: Business Information Systems Workshops pp 245–251Cite as

Performance Evaluation of Sentiment Analysis Methods for Brazilian Portuguese

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 263))

Abstract

Daily, a big data of media, thoughts and opinions can be noticed on Online Social Networks (OSN), resulting from their user’s interaction and sharing of information. In Brazil, this is strongly observed, as Brazilians are often active on the Internet. The business and academic communities around the world are aware of these events, due their possibilities to improve social customer relationship management. Therefore, this work aims to show a performance comparison between algorithms for Sentiment Analysis (SA), in their Portuguese and English versions, with datasets composed of Brazilian Portuguese comments from OSN, and their translations. The results highlight the need for proposals in specific language and Social Media context, given the performance presented by Portuguese version methods.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Lai, L.S., Turban, E.: Groups formation and operations in the Web 2.0 environment and social networks. Group Decis. Negot. 17(5), 387–402 (2008)

    Article  Google Scholar 

  2. Zephoria. https://zephoria.com/top-15-valuable-facebookstatistics/

  3. Internet Live Stats. http://www.internetlivestats.com/twitter-statistics/

  4. Mostafa, M.M.: More than words: social networks’ text mining for consumer brand sentiments. Expert Syst. Appl. 40(10), 4241–4251 (2013)

    Article  Google Scholar 

  5. Heller Baird, C., Gautam, P.: From social media to social customer relationship management. Strategy Leadersh. 39(5), 30–37 (2011)

    Article  Google Scholar 

  6. Garrigos, F., Gil, I., Narangajavana, Y.: The impact of social networks in the competitiveness of the firms. In: Beckford, A.M., Larsen, J.P. (eds.) Competitiveness: Psychology, Production, Impact and Global Trends. Nova Science Publishers, Hauppauge (2011)

    Google Scholar 

  7. Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found. Trends Inf. Retrieval 2(1–2), 1–35 (2008)

    Article  Google Scholar 

  8. Hearst, M.A.: Direction-based text interpretation as an information access refinement. In: Text-based Intelligent Systems: Current Research and Practice in Information Extraction and Retrieval, pp. 257–274 (1992)

    Google Scholar 

  9. We Are Social. http://wearesocial.com/sg/special-reports/digital-2016

  10. Silva, Mário, J., Carvalho, P., Sarmento, L.: Building a sentiment lexicon for social judgement mining. In: Caseli, H., Villavicencio, A., Teixeira, A., Perdigão, F. (eds.) PROPOR 2012. LNCS, vol. 7243, pp. 218–228. Springer, Heidelberg (2012). doi:10.1007/978-3-642-28885-2_25

    Chapter  Google Scholar 

  11. Cambria, E., Speer, R., Havasi, C., Hussain, A.: SenticNet: a publicly available semantic resource for opinion mining. In: AAAI Fall Symposium: Common Sense Knowledge, vol. 10 (2010)

    Google Scholar 

  12. Ribeiro, F.N., Araújo, M., Gonçalves, P., Benevenuto, F., Gonçalves, M.A.: A benchmark comparison of state-of-the-practice sentiment analysis methods. arXiv preprint arXiv:1512.01818 (2015)

  13. Balage, P.P.F., Pardo, T.A., Aluısio, S.M.: An evaluation of the Brazilian Portuguese LIWC dictionary for sentiment analysis. In: Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology (STIL), pp. 215–219 (2013)

    Google Scholar 

  14. Pennebaker, J.W., Francis, M.E., Booth, R.J.: Linguistic inquiry and word count: LIWC 2001, vol. 71. Lawrence Erlbaum Associates, Mahway (2001)

    Google Scholar 

  15. Hu, M., Liu, B.: Mining opinion features in customer reviews. AAAI 4(4), 755–760 (2004)

    Google Scholar 

  16. Taboada, M., Brooke, J., Tofiloski, M., Voll, K., Stede, M.: Lexicon-based methods for sentiment analysis. Comput. Linguist. 37(2), 267–307 (2011)

    Article  Google Scholar 

  17. Thelwall, M.: Heart and soul: sentiment strength detection in the social web with sentistrength. In: Proceedings of the CyberEmotions, pp. 1–14 (2013)

    Google Scholar 

  18. Hutto, C.J., Gilbert, E.: Vader: a parsimonious rule-based model for sentiment analysis of social media text. In: 8th International AAAI Conference on Weblogs and Social Media (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Electrical and Computer Engineering Department, ITEC, Federal University of Pará, Belém, 66075110, Brazil

    Douglas Cirqueira, Adamo Lima de Santana & Márcia Pinheiro

  2. Technological Sciences Center, State University of Maranhão, São Luís, 65950000, Brazil

    Antonio Jacob Jr.

  3. Federal University of Western Pará, Santarém, 68035110, Brazil

    Fábio Lobato

Authors
  1. Douglas Cirqueira
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antonio Jacob Jr.
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fábio Lobato
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Adamo Lima de Santana
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Márcia Pinheiro
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Antonio Jacob Jr. .

Editor information

Editors and Affiliations

  1. Poznań University of Economics and Business, Poznan, Poland

    Witold Abramowicz

  2. Leipzig University, Leipzig, Germany

    Rainer Alt

  3. Leipzig University, Leipzig, Germany

    Bogdan Franczyk

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Cirqueira, D., Jacob, A., Lobato, F., de Santana, A.L., Pinheiro, M. (2017). Performance Evaluation of Sentiment Analysis Methods for Brazilian Portuguese. In: Abramowicz, W., Alt, R., Franczyk, B. (eds) Business Information Systems Workshops. BIS 2016. Lecture Notes in Business Information Processing, vol 263. Springer, Cham. https://doi.org/10.1007/978-3-319-52464-1_22

Download citation

Publish with us

Policies and ethics

Search

Navigation