Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
DE
EN
Books
Journals
Events
Topic Page
Marketing
Log in
Learn more about individual access
Request company access
13th International Engine Congress 2026 | 24 + 25 February 2026

Meeting Place for the Powertrain and Sustainable Fuels Community

Take part as a speaker in the 13th International Engine Congress 2026, the Meeting Place for the Powertrain, and Sustainable Fuels Community for the exchange of experience. Submit a subject proposal online about our main subject areas: Passenger car engine technology, Commercial vehicle engine technology and Sustainable Fuels & Energy!
EXTENDED SEARCH
Log in
Top
Social Network Analysis and Mining
Published in:

01-12-2016 | Review Article

Sentiment/subjectivity analysis survey for languages other than English

Authors: Mohammed Korayem, Khalifeh Aljadda, David Crandall

Published in: Social Network Analysis and Mining | Issue 1/2016

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Subjective and sentiment analysis have gained considerable attention recently. Most of the resources and systems built so far are done for English. The need for designing systems for other languages is increasing. This paper surveys different ways used for building systems for subjective and sentiment analysis for languages other than English. There are three different types of systems used for building these systems. The first (and the best) one is the language-specific systems. The second type of systems involves reusing or transferring sentiment resources from English to the target language. The third type of methods is based on using language-independent methods. The paper presents a separate section devoted to Arabic sentiment analysis.
previous article Behavioral analysis and classification of spammers distributing pornographic content in social media
next article Toward understanding online sentiment expression: an interdisciplinary approach with subgroup comparison and visualization

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
Literature
Abbasi A, Chen H, Salem A (2008) Sentiment analysis in multiple languages: feature selection for opinion classification in web forums. ACM Trans Inf Syst 26:121–1234
AbdelRahman S, Elarnaoty M, Magdy M, Fahmy A (2010) Integrated machine learning techniques for Arabic named entity recognition. IJCSI 7:27–36
Abdul-Mageed M, Diab M (2011) Subjectivity and sentiment annotation of modern standard Arabic newswire. In: ACL HLT 2011, p. 110
Abdul-Mageed M, Diab M (2012) Awatif: a multi-genre corpus for modern standard Arabic subjectivity and sentiment analysis. In: The 8th international conference on language resources and evaluation (LREC2012)
Abdul-Mageed M, Diab M, Korayem M (2011) Subjectivity and sentiment analysis of modern standard Arabic. In: Proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies: short papers, vol 2. Association for Computational Linguistics, pp 587–591
Abdul-Mageed M, Korayem M (2010) Automatic identification of subjectivity in morphologically rich languages: the case of Arabic. In: Computational approaches to subjectivity and sentiment analysis, p 2
Abdul-Mageed M, übler SK, Diab M (2012) Samar: a system for subjectivity and sentiment analysis of Arabic social media. In: 3rd workshop on computational approaches to subjectivity and sentiment analysis (WASSA)
Agić Ž, Ljubešić N, Tadić M (2010) Towards sentiment analysis of financial texts in croatian. Bull Market 143(45):69
Ahmad K, Cheng D, Almas Y (2006) Multi-lingual sentiment analysis of financial news streams. In: Proceedings of the 1st international conference on grid in finance
Almas Y, Ahmad K (2007) A note on extracting sentiments in financial news in English, Arabic & Urdu. In: Proceedings of Workshop on Computational Approaches to Arabic Script-based Languages. Linguistic society of America, Stanford University, Stanford, California, pp 1–12
Banea C, Mihalcea R, Wiebe J (2010) Multilingual subjectivity: are more languages better? In: Proceedings of the 23rd international conference on computational Linguistics. Association for Computational Linguistics, pp 28–36
Banea C, Mihalcea R, Wiebe J, Hassan S (2008) Multilingual subjectivity analysis using machine translation. In: Proceedings of the conference on empirical methods in natural language processing. Association for Computational Linguistics, pp 127–135
Bollen J, Mao H, Zeng X (2011) Twitter mood predicts the stock market. J Comput Sci 2:1–8CrossRef
Brooke J, Tofiloski M, Taboada M (2009) Cross-linguistic sentiment analysis: from English to Spanish. In: Proceedings of the 7th international conference on recent advances in natural language processing, Borovets, Bulgaria, pp 50–54
Das A, Bandyopadhyay S (2009) Subjectivity detection in English and Bengali: a CRF-based approach. In: Proceeding of ICON
Denecke K (2008) Using Sentiwordnet for multilingual sentiment analysis. In: IEEE 24th international conference on data engineering workshop, 2008. ICDEW 2008. IEEE, pp 507–512
El-Halees A (2011) Arabic opinion mining using combined classification approach. In: 2011 international Arab conference on information technology ACIT2011
Elarnaoty M, AbdelRahman S, Fahmy A (2012) A machine learning approach for opinion holder extraction in Arabic language. Int J Artif Intell Appl 3(2):45–63
Elhawary M, Elfeky M (2010) Mining Arabic business reviews. In: 2010 IEEE international conference on data mining workshops (ICDMW). IEEE, pp 1108–1113
Esuli A, Sebastiani F (2006) Sentiwordnet: a publicly available lexical resource for opinion mining. In: Proceedings of LREC, vol 6, Citeseer, pp 417–422
Farra N, Challita E, Assi R, Hajj H (2010) Sentence-level and document-level sentiment mining for Arabic texts. In: 2010 IEEE international conference on data mining workshops (ICDMW). IEEE, pp 1114–1119
Ghorbel H, Jacot D (2011) Sentiment analysis of French movie reviews. In: Pallotta V, Soro A, Vargiu E (eds) Advances in distributed agent-based retrieval tools. Springer, Berlin, Heidelberg, pp 97–108. doi:10.​1007/​978-3-642-21384-7_​7. ISBN 978-3-642-21384-7
Habash N (2010) Introduction to Arabic natural language processing. Synth Lect Hum Lang Technol 3(1):1–187CrossRef
Habash N, Rambow O, Roth R (2009) MADA + TOKAN: a toolkit for Arabic tokenization, diacritization, morphological disambiguation, pos tagging, stemming and lemmatization. In: Proceedings of the 2nd international conference on Arabic language resources and tools (MEDAR), Cairo, Egypt
Kim J, Jung H, LEE Y, LEE J (2009) Conveying subjectivity of a lexicon of one language into another using a bilingual dictionary and a link analysis algorithm. Int J Comput Process Orient Lang 22(2):205CrossRef
Li J, Sun M (2007) Experimental study on sentiment classification of Chinese review using machine learning techniques. In: International conference on natural language processing and knowledge engineering, 2007. NLP-KE 2007, 30 Sept 2007, pp 393–400
Lin Z, Tan S, Cheng X (2011) Language-independent sentiment classification using three common words. In: Proceedings of the 20th ACM international conference on information and knowledge management. ACM, pp 1041–1046
Liu B (2010) Sentiment analysis and subjectivity. In: Indurkhya N, Damerau FJ (eds) Handbook of natural language processing. CRC Press, Taylor and Francis Group, Boca Raton, FL, pp 627–666. ISBN 978-1420085921
Mihalcea R, Banea C, Wiebe J (2007) Learning multilingual subjective language via cross-lingual projections. In: Annual meeting-association for computational linguistics, vol 45, p 976
Mullen T, Collier N (2004) Sentiment analysis using support vector machines with diverse information sources. In: Proceedings of conference on empirical methods in natural language processing
Pang B, Lee L (2004) A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts. In: Proceedings of the ACL, pp 271–278
Pang B, Lee L (2008) Opinion mining and sentiment analysis. Found Trends Inf Retr 2(1–2):1–135CrossRef
Pang B, Lee L, Vaithyanathan S (2002) Thumbs up? Sentiment classification using machine learning techniques. In: Proceedings of the ACL-02 conference on empirical methods in natural language processing, vol 10. EMNLP’02, Stroudsburg, PA, USA, Association for Computational Linguistics, pp 79–86
Pennebaker JW, Francis ME, Booth RJ (2001) Linguistic inquiry and word count: Liwc 2001. Mahway: Lawrence Erlbaum Associates, vol 71, p 2001
Raychev V, Nakov P (2009) Language-independent sentiment analysis using subjectivity and positional information. In: Proceedings of the international conference RANLP, pp 360–364
Remus, R, Quasthoff U, Heyer G (2010) Sentiws-a publicly available german-language resource for sentiment analysis. In: Proceedings of the 7th language resources and evaluation conference
Rushdi-Saleh M, Martín-Valdivia M, Ureña-López L, Perea-Ortega J (2011a) Bilingual experiments with an arabic-english corpus for opinion mining, pp 740–745
Rushdi-Saleh M, Martín-Valdivia M, Ureña-López L, Perea-Ortega J (2011b) OCA: Opinion corpus for Arabic. J Am Soc Inf Sci Technol 62(10):2045–2054CrossRef
Scheible C (2010) Sentiment translation through lexicon induction. In: Proceedings of the ACL 2010 student research workshop. Association for Computational Linguistics, pp 25–30
Scheible C, Laws F, Michelbacher L, Schütze H (2010) Sentiment translation through multi-edge graphs. In: Proceedings of the 23rd international conference on computational Linguistics: posters. Association for Computational Linguistics, pp 1104–1112
Steinberger J, Lenkova P, Ebrahim M, Ehrmann M, Hurriyetoglu A, Kabadjov M, Steinberger R, Tanev H, Zavarella V, Vázquez S (2011) Creating sentiment dictionaries via triangulation. In: Proceedings of the 2nd workshop on computational approaches to subjectivity and sentiment analysis. Association for Computational Linguistics, pp 28–36
Steinberger J, Lenkova P, Kabadjov M, Steinberger R, van der Goot E (2011) Multilingual entity-centered sentiment analysis evaluated by parallel corpora. In Proceedings of Recent Advances in Natural Language Processing, Hissar, Bulgaria, pp 770–775
Stone P, Dunphy D, Smith M, Ogilvie DM (1968) The general inquirer: a computer approach to content analysis. J Reg Sci 8(1):113–116CrossRef
Syed A, Aslam M, Martinez-Enriquez A (2010) Lexicon based sentiment analysis of Urdu text using Sentiunits. In: Advances in artificial intelligence, pp 32–43
Versteegh K, Versteegh C (1997) The Arabic language. Columbia University Press, New York City
Vilares D, Thelwall M, Alonso MA (2015) The megaphone of the people? Spanish sentistrength for real-time analysis of political tweets. J Inf Sci 41(6):799–813CrossRef
Wan X (2008) Using bilingual knowledge and ensemble techniques for unsupervised Chinese sentiment analysis. In: Proceedings of the conference on empirical methods in natural language processing. Association for Computational Linguistics, pp 553–561
Wan X (2009) Co-training for cross-lingual sentiment classification. In: Proceedings of the joint conference of the 47th annual meeting of the ACL and the 4th international joint conference on natural language processing of the AFNLP, vol 1. Association for Computational Linguistics, pp 235–243
Wei B, Pal C (2010) Cross lingual adaptation: an experiment on sentiment classifications. In: Proceedings of the ACL 2010 conference short papers. Association for Computational Linguistics, pp 258–262
Whitelaw C, Garg N, Argamon S (2005) Using appraisal groups for sentiment analysis. In: Proceedings of the 14th ACM international conference on information and knowledge management. CIKM’05. ACM, New York, NY, USA, pp 625–631
Wiebe J, Riloff E (2005) Creating subjective and objective sentence classifiers from unannotated texts. In: Computational linguistics and intelligent text processing, pp 486–497
Wilson T, Wiebe J, Hoffmann P (2005) Recognizing contextual polarity in phrase-level sentiment analysis. In: Proceedings of the conference on human language technology and empirical methods in natural language processing. Association for Computational Linguistics, pp 347–354
Zhai Z, Xu H, Li J, Jia P (2010) Feature subsumption for sentiment classification in multiple languages. In: Zaki M, Yu J, Ravindran B, Pudi V (eds) Advances in knowledge discovery and data mining, vol 6119. Lecture notes in computer science. Springer, Berlin, pp 261–271
Zhang C, Zeng D, Li J, Wang F, Zuo W (2009) Sentiment analysis of Chinese documents: from sentence to document level. J Am Soc Inf Sci Technol 60(12):2474–2487CrossRef
Zhang C, Zuo W, Peng T, He F (2008) Sentiment classification for chinese reviews using machine learning methods based on string kernel. In: Third international conference on convergence and hybrid information technology, 2008. ICCIT’08, vol 2. IEEE, pp 909–914
Metadata
Title
Sentiment/subjectivity analysis survey for languages other than English
Authors
Mohammed Korayem
Khalifeh Aljadda
David Crandall
Publication date
01-12-2016
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2016
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-016-0381-6

Other articles of this Issue 1/2016

An algebraic approach to temporal network analysis based on temporal quantities

  • Original Article

A penalty box approach for approximation betweenness and closeness centrality algorithms

  • Original Article

Structure and causality in the world system

  • Original Article

Behavioral analysis and classification of spammers distributing pornographic content in social media

  • Original Article

Applying the Clique Percolation Method to analyzing cross-market branch banking network structure: the case of Illinois

  • Original Article

Comparison of sentiment lexicon development techniques for event prediction

  • Original Article

Premium Partner

    Image Credits