nach oben

Artificial Intelligence Review

Erschienen in:

02.07.2016

A comparative empirical study on social media sentiment analysis over various genres and languages

verfasst von: Viktor Hangya, Richárd Farkas

Erschienen in: Artificial Intelligence Review | Ausgabe 4/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

People express their opinions about things like products, celebrities and services using social media channels. The analysis of these textual contents for sentiments is a gold mine for marketing experts as well as for research in humanities, thus automatic sentiment analysis is a popular area of applied artificial intelligence. The chief objective of this paper is to investigate automatic sentiment analysis on social media contents over various text sources and languages. The comparative findings of the investigation may give useful insights to artificial intelligence researchers who develop sentiment analyzers for a new textual source. To achieve this, we describe supervised machine learning based systems which perform sentiment analysis and we comparatively evaluate them on seven publicly available English and Hungarian databases, which contain text documents taken from Twitter and product review sites. We discuss the differences among these text genres and languages in terms of document- and target-level sentiment analysis.

Vorheriger Artikel Weighted-spectral clustering algorithm for detecting community structures in complex networks

Nächster Artikel A survey of decision making methods based on certain hybrid soft set models

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Jetzt informieren

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!

Jetzt informieren

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!

Jetzt informieren

www.internetslang.com.

http://www.arukereso.hu.

Amigó E, Carrillo de Albornoz J, Chugur I, Corujo A, Gonzalo J, Martín T, Meij E, de Rijke M, Spina D, Amigo E, de Albornoz JC, Martin T, de Rijke M (2013) Overview of replab 2013: evaluating online reputation monitoring systems. In: Information access evaluation. multilinguality, multimodality, and visualization, pp 333–352

Baccianella S, Esuli A, Sebastiani F (2010) SentiWordNet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining. In: Proceedings of the seventh international conference on language resources and evaluation (LREC’10)

Blei DM, Ng AY, Jordan MI (2003) Latent dirichlet allocation. J Mach Learn Res 3:993–1022MATH

Bohnet B (2010) Top accuracy and fast dependency parsing is not a contradiction. In: Proceedings of the 23rd international conference on computational linguistics (Coling 2010), Beijing, China, pp 89–97

Ceylan H, Mihalcea R (2011) An efficient indexer for large N-gram corpora. In: ACL (system demonstrations), pp 103–108

Cossu JV, Bigot B, Bonnefoy L, Morchid M, Bost X, Senay G, Dufour R, Bouvier V, Torres-Moreno JM, El-Beze M (2013) LIA@RepLab 2013. In: Working notes of CLEF 2013 evaluation labs and workshop

Farkas R, Bohnet B (2012) Stacking of dependency and phrase structure parsers. In: Proceedings of COLING 2012, the COLING 2012 Organizing Committee, Mumbai, pp 849–866

Feldman R (2013) Techniques and applications for sentiment analysis. Commun ACM 56(4):82. doi:10.1145/2436256.2436274 CrossRef

Foster J, Çetinoglu Ö, Wagner J, Le Roux J, Hogan S, Nivre J, Hogan D, Van Genabith J (2011) # hardtoparse: POS tagging and parsing the twitterverse. In: AAAI 2011 workshop on analyzing microtext, pp 20–25

Hangya V, Farkas R (2013) Filtering and polarity detection for reputation management on tweets. In: Working notes of CLEF 2013 evaluation labs and workshop

Hangya V, Berend G, Farkas R (2013) SZTE-NLP: sentiment detection on twitter messages. In: Second joint conference on lexical and computational semantics (*SEM), volume 2: proceedings of the seventh international workshop on semantic evaluation (SemEval 2013), pp 549–553

Hangya V, Berend G, Varga I, Farkas R (2014) SZTE-NLP: aspect level opinion mining exploiting syntactic cues. In: Proceedings of the 8th international workshop on semantic evaluation (SemEval 2014). Dublin, Ireland, pp 610–614

Jansen BJ, Zhang M, Sobel K, Chowdury A (2009) Twitter power: tweets as electronic word of mouth. J Am Soc Inf Sci Technol 60(11):2169–2188

Jiang L, Yu M, Zhou M, Liu X, Zhao T (2011) Target-dependent Twitter sentiment classification. In: Proceedings of the 49th annual meeting of the Association for Computational Linguistics, pp 151–160

Jindal N, Liu B, Street SM (2008) Opinion spam and analysis. In: Proceedings of the 2008 international conference on web search and data mining

Kessler JS, Eckert M, Clark L, Nicolov N (2010) The 2010 ICWSM JDPA sentiment corpus for the automotive domain. In: 4th international AAAI conference on weblogs and social media data workshop challenge (ICWSM-DWC 2010)

Kiritchenko S, Zhu X, Cherry C, Mohammad S (2014) NRC-Canada-2014: detecting aspects and sentiment in customer reviews. In: Proceedings of the 8th international workshop on semantic evaluation (SemEval 2014), SemEval, p 437

Klein D, Manning CD (2003) Accurate unlexicalized parsing. In: Proceedings of the 41st ACL, pp 423–430. doi:10.3115/1075096.1075150

Kong L, Schneider N, Swayamdipta S, Bhatia A, Dyer C, Smith NA (2014) A dependency parser for tweets. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). Association for Computational Linguistics, Doha, pp 1001–1012

Lazaridou A, Titov II, Sporleder CC (2013) A Bayesian model for joint unsupervised induction of sentiment, aspect and discourse representations. In: 51st annual meeting of the Association for Computational Linguistics, ACL 2013, pp 1630–1639

Li S, Zhou L, Li Y (2015) Improving aspect extraction by augmenting a frequency-based method with web-based similarity measures. Inf Process Manag 51(1):58–67. doi:10.1016/j.ipm.2014.08.005 CrossRef

Liu B (2012) Sentiment analysis and opinion mining. Synth Lect Hum Lang Technol 5(1):1–167CrossRef

Martínez-Cámara E, Martín-Valadivia MT, Urena-López LA, Montejo-Ráez AR (2012) Sentiment analysis in Twitter. Nat Lang Eng 20(01):1–28. doi:10.1017/S1351324912000332 CrossRef

McCallum AK (2002) MALLET: a machine learning for language toolkit. http://mallet.cs.umass.edu

Miháltz M (2013) OpinHuBank: szabadon hozzáférhető annotált korpusz magyar nyelvű véleményelemzéshez. In: IX. Magyar Számítógépes Nyelvészeti Konferencia, pp 343–345

Montejo-Ráez A, Martínez-Cámara E, Martín-Valdivia MT, Ureña-López LA (2014) A knowledge-based approach for polarity classification in Twitter. J Assoc Inf Sci Technol 65(2):414–425. doi:10.1002/asi.22984 CrossRef

O’Connor B, Balasubramanyan R (2010) From tweets to polls: linking text sentiment to public opinion time series. In: ICWSM

Pontiki M, Galanis D, Pavlopoulos J, Papageorgiou H, Androutsopoulos I, Manandhar S (2014) Semeval-2014 task 4: aspect based sentiment analysis. In: Proceedings of the 8th international workshop on semantic evaluation (SemEval 2014), SemEval ’14, pp 27–35

Poria S, Cambria E, Ku LW, Gui C, Gelbukh A (2014) A rule-based approach to aspect extraction from product reviews. In: Proceedings of the second workshop on natural language processing for social media (SocialNLP), Association for Computational Linguistics and Dublin City University, Dublin, pp 28–37

Ravi K, Ravi V (2015) A survey on opinion mining and sentiment analysis: tasks, approaches and applications. Knowl-Based Syst 89:14–46. doi:10.1016/j.knosys.2015.06.015 CrossRef

Reyes A, Rosso P (2013) On the difficulty of automatically detecting irony: beyond a simple case of negation. Knowl Inf Syst 40(3):595–614. doi:10.1007/s10115-013-0652-8 CrossRef

Rosenthal S, Nakov P, Ritter A, Stoyanov V (2014) Semeval-2014 task 9: Sentiment analysis in twitter. In: Proceedings of the 8th international workshop on semantic evaluation (SemEval 2014), SemEval, pp 73–80

Sang ETK, Bos J (2012) Predicting the 2011 Dutch Senate Election results with Twitter. In: Proceedings of the 13th conference of the European Chapter of the Association for Computational Linguistics, pp 53–60

Socher R, Perelygin A, Wu J, Chuang J, Manning CD, Ng AY, Potts C (2013) Recursive deep models for semantic compositionality over a sentiment treebank. In: Proceedings of the 2013 conference on empirical methods in natural language processing, pp 1631–1642

Szántó Zs, Farkas R (2014) Special techniques for constituent parsing of morphologically rich languages. In: Proceedings of the 14th conference of the European Chapter of the Association for Computational Linguistics, pp 135–144

Varga I, Sano M, Torisawa K, Hashimoto C, Ohtake K, Kawai T, Oh JH, De Saeger S (2013) Aid is out there: looking for help from tweets during a large scale disaster. In: Proceedings of the 51st annual meeting of the ACL, pp 1619–1629

Vilares D, Alonso MA, Gómez-Rodriguez C (2015a) A syntactic approach for opinion mining on Spanish reviews. Nat Lang Eng 21(01):139–163. doi:10.1017/S1351324913000181 CrossRef

Vilares D, Alonso MA, Gómez-Rodríguez C (2015b) On the usefulness of lexical and syntactic processing in polarity classification of Twitter messages. J Assoc Inf Sci Technol 66(9):1799–1816. doi:10.1002/asi.23284 CrossRef

Vinodhini G, Chandrasekaran RM (2012) Sentiment analysis and opinion mining: a survey. Int J Adv Res Comput Sci Softw Eng 2(6):282–292

Wagner J, Arora P, Cortes S (2014) DCU: aspect-based polarity classification for semeval task 4. In: Proceedings of the 8th international workshop on semantic evaluation (SemEval 2014), pp 223–229

Wiegand M, Balahur A, Roth B, Klakow D, Montoyo A (2010) A survey on the role of negation in sentiment analysis. In: Proceedings of the workshop on negation and speculation in natural language processing, pp 60–68

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

Wilson T, Kozareva Z, Nakov P, Rosenthal S, Stoyanov V, Ritter A (2013) SemEval-2013 Task 2: sentiment analysis in Twitter. In: Proceedings of the international workshop on semantic evaluation, SemEval‘3

Zhang C, Zeng D, Li J, Wang FY, Zuo W (2009) Sentiment analysis of Chinese documents: from sentence to document level. J Am Soc Inf Sci Technol 60(12):2474–2487. doi:10.1002/asi.21206 CrossRef

Zhu X, Kiritchenko S, Mohammad S (2014) NRC-Canada-2014: recent improvements in the sentiment analysis of tweets. In: Proceedings of the 8th international workshop on semantic evaluation (SemEval 2014), pp 443–447

Zsibrita J, Vincze V, Farkas R (2013) Magyarlanc: a toolkit for morphological and dependency parsing of Hungarian. In: Proceedings of RANLP, pp 763–771

Titel: A comparative empirical study on social media sentiment analysis over various genres and languages
verfasst von: Viktor Hangya
Richárd Farkas
Publikationsdatum: 02.07.2016
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 4/2017
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-016-9489-3

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 4/2017

Retraction Note to: Static hand gesture recognition using neural networks

Weighted-spectral clustering algorithm for detecting community structures in complex networks

Plant intelligence based metaheuristic optimization algorithms

Image descriptors in radiology images: a systematic review

A survey of decision making methods based on certain hybrid soft set models