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Sentiment Analysis in Arabic

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Natural Language Processing and Information Systems (NLDB 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9612))

Abstract

The tasks that falls under the errands that takes after Natural Language Processing approaches includes Named Entity Recognition, Information Retrieval, Machine Translation, and so on. Wherein Sentiment Analysis utilizes Natural Language Processing as one of the way to locate the subjective content showing negative, positive or impartial (neutral) extremity (polarity). Due to the expanded utilization of online networking sites like Facebook, Instagram, Twitter, Sentiment Analysis has increased colossal statures. Examination of sentiments helps organizations, government and other association to extemporize their items and administration in view of the audits or remarks. This paper introduces an Innovative methodology that investigates the part of lexicalization for Arabic Sentiment examination. The system was put in place with two principles rules– “equivalent to” and “within the text” rules. The outcomes subsequently accomplished with these rules methodology gave 89.6 % accuracy when tried on baseline dataset, and 50.1 % exactness on OCA, the second dataset. A further examination shows 19.5 % in system1 increase in accuracy when compared with baseline dataset.

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References

  1. Abdulla, N.A., Ahmed, N.A., Shehab, M.A., Al-Ayyoub, M., Al-Kabi, M.N., Al-rifai, S.: Towards improving the lexicon-based approach for arabic sentiment analysis. Int. J. Inf. Technol. Web Eng. (IJITWE) 9(3), 55–71 (2014)

    Article  Google Scholar 

  2. Aldayel, H.K., Azmi, A.M.: Arabic tweets sentiment analysis – a hybrid scheme. J. Inf. Sci. 0165551515610513 (2015)

    Google Scholar 

  3. El-Halees, A.: Arabic opinion mining using combined classification approach (2011)

    Google Scholar 

  4. Feldman, R.: Techniques and applications for sentiment analysis. Commun. ACM 56(4), 82–89 (2013)

    Article  Google Scholar 

  5. Shaalan, K.: A survey of arabic named entity recognition and classification. Comput. Linguist. 40(2), 469–510 (2014). MIT Press, USA

    Article  Google Scholar 

  6. Shoukry, A., Rafea, A.: Preprocessing Egyptian dialect tweets for sentiment mining. In: 4th Workshop on Computational Approaches to Arabic Script-Based Languages, pp. 47–56 (2012)

    Google Scholar 

  7. Shoukry, A., Rafea, A.: Sentence-level Arabic sentiment analysis. In: 2012 International Conference on Collaboration Technologies and Systems (CTS), pp. 546–550. IEEE, May 2012

    Google Scholar 

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Author information

Authors and Affiliations

  1. British University in Dubai, Block 11, 1st and 2nd Floor, Dubai International Academic City, Dubai, UAE

    Sanjeera Siddiqui & Khaled Shaalan

  2. Faculty of Computer and Information Sciences, Ain Shams University, Abbassia, 11566, Cairo, Egypt

    Azza Abdel Monem

  3. School of Informatics, University of Edinburgh, Edinburgh, UK

    Khaled Shaalan

Authors
  1. Sanjeera Siddiqui
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  2. Azza Abdel Monem
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  3. Khaled Shaalan
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Corresponding author

Correspondence to Sanjeera Siddiqui .

Editor information

Editors and Affiliations

  1. ConservatoireNational desArts et Métiers, Paris, France

    Elisabeth Métais

  2. University of Salford, Salford, United Kingdom

    Farid Meziane

  3. University of Salford, Salford, United Kingdom

    Mohamad Saraee

  4. Oakland University, Rochester, Michigan, USA

    Vijayan Sugumaran

  5. University of Salford, Salford, United Kingdom

    Sunil Vadera

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© 2016 Springer International Publishing Switzerland

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Siddiqui, S., Monem, A.A., Shaalan, K. (2016). Sentiment Analysis in Arabic. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2016. Lecture Notes in Computer Science(), vol 9612. Springer, Cham. https://doi.org/10.1007/978-3-319-41754-7_41

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  • DOI: https://doi.org/10.1007/978-3-319-41754-7_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41753-0

  • Online ISBN: 978-3-319-41754-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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