Skip to main content
Springer Nature Link
Log in

Sentiment Analysis of Arabic Tweets: Opinion Target Extraction

  • Conference paper
  • First Online:
Modelling and Implementation of Complex Systems (MISC 2018)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 64))

Abstract

Due to the increased volume of Arabic opinionated posts on different social media, Arabic sentiment analysis is viewed as an important research field. Identifying the target on which opinion has been expressed is the aim of this work. Opinion target extraction is a problem that was generally very little treated in Arabic text. In this paper, an opinion target extraction method from Arabic tweets is proposed. First, as a preprocessing phase, several feature forms from tweets are extracted to be examined. The aim of these forms is to evaluate their impacts on accuracy. Then, two classifiers, SVM and Naïve Bayes are trained. The experiment results show that, with 500 tweets collected and manually tagged, SVM gives the highest precision and recall (86%).

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    https://tags.hawksey.info/.

  2. 2.

    http://nlp.stanford.edu/software/tagger.shtml.

  3. 3.

    http://www.cs.waikato.ac.nz/ml/weka.

References

  1. Liu, B., Zhang, L.: A survey of opinion mining and sentiment analysis. Mining Text Data, pp. 415–463. Springer, Boston (2012)

    Chapter  Google Scholar 

  2. Liu, B.: Sentiment analysis and opinion mining. Synth. Lect. Hum. Lang. Technol. 1–167 (2012)

    Google Scholar 

  3. Elarnaoty, M.: A machine learning approach for opinion holder extraction in Arabic language. Int. J. Artif. Intell. Appl. 3(2), 45–63 (2012)

    Google Scholar 

  4. Alkadri, A.M., ElKorany, A.M.: Semantic feature based Arabic opinion mining using ontology. Int. J. Adv. Comput. Sci. Appl. 7(5), 577–583 (2016)

    Google Scholar 

  5. Ismail, S., Alsammak, A., Elshishtawy, T.: A generic approach for extracting aspects and opinions of Arabic reviews. In: Proceedings of the 10th International Conference on Informatics and Systems, pp 173–179. ACM (2016)

    Google Scholar 

  6. Farra, N., McKeown, K., Habash, N.: Annotating targets of opinions in Arabic using crowd sourcing. In: 2015 Proceedings of the Second Workshop on Arabic Natural Language Processing, pp. 89–98 (2015)

    Google Scholar 

  7. Ibrahim, M.A., Salim, N.: Aspect oriented sentiment analysis model of Arabic tweets. Int. J. Comput. Sci. Trends Technol. 4(4), 342–353 (2016)

    Google Scholar 

  8. Khoja, S., Garside, R.: Stemming Arabic Text, Lancaster, UK, Computing Department, Lancaster University (1999). http://www.comp.lancs.ac.uk/computing/users/khoja/stemmer.ps

  9. Behdenna, S., Barigou, F., Belalem, G.: Sentiment analysis at document level. In: International Conference on Smart Trends for Information Technology and Computer Communications, pp 159–168. Springer, Singapore (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science Department, Faculty of Sciences, University of Oran 1, Ahmed Ben Bella, PB 1524 El M’Naouer, Oran, Algeria

    Behdenna Salima, Barigou Fatiha & Belalem Ghalem

Authors
  1. Behdenna Salima
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Barigou Fatiha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Belalem Ghalem
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Behdenna Salima .

Editor information

Editors and Affiliations

  1. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Salim Chikhi

  2. Faculty of Technology, GeCoDe Laboratory, University of Saida, Saida, Algeria

    Abdelmalek Amine

  3. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Allaoua Chaoui

  4. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Djamel Eddine Saidouni

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Salima, B., Fatiha, B., Ghalem, B. (2019). Sentiment Analysis of Arabic Tweets: Opinion Target Extraction. In: Chikhi, S., Amine, A., Chaoui, A., Saidouni, D.E. (eds) Modelling and Implementation of Complex Systems. MISC 2018. Lecture Notes in Networks and Systems, vol 64. Springer, Cham. https://doi.org/10.1007/978-3-030-05481-6_12

Download citation

Publish with us

Policies and ethics