Abstract
Emotion classification is used in many commercial applications and research applications. The semantic classification models (or sentiment classification methods) are based on the vocabulary of the emotion dictionary being studied and being used very much to this day. In this study, a Vietnamese sentiment dictionary includes Vietnamese terms (Vietnamese nouns, Vietnamese verbs, Vietnamese adjectives, etc.) which the valences (and polarities) are calculated by using Ochiai measure through Google search engine and many Vietnamese adjective phrases which the valences (and polarities) are identified based on Vietnamese language characteristics. The Vietnamese adjectives often bear emotion which values (or semantic scores) are not fixed and are changed when they appear in different contexts of these phrases. Therefore, if the Vietnamese adjectives bring sentiment and their semantic values (or their sentiment scores) are not changed in any context, then the results of the emotion classification are not high accuracy. We propose many rules based on Vietnamese language characteristics to determine the emotional values of the Vietnamese adjective phrases bearing sentiment in specific contexts. Our Vietnamese sentiment adjective dictionary is widely used in applications and researches of the Vietnamese semantic classification.
Similar content being viewed by others
References
Abreu R, Zoeteweij P, van Gemund AJC (2006) An evaluation of similarity coefficients for software fault localization. In: 12th Pacific Rim international symposium on dependable computing (PRDC’06), pp 39–46
Agarwal B, Mittal N (2016a) Machine learning approach for sentiment analysis. In: Prominent feature extraction for sentiment analysis, pp 21–45. doi: 10.1007/978-3-319-25343-5_3. Print ISBN 978-3-319-25341-1
Agarwal B, Mittal N (2016b) Semantic orientation-based approach for sentiment analysis. In: Prominent feature extraction for sentiment analysis, pp 77–88. doi: 10.1007/978-3-319-25343-5_6. Print ISBN 978-3-319-25341-1
Ahmed S, Danti A (2016) Effective sentimental analysis and opinion mining of web reviews using rule based classifiers. In: Computational intelligence in data mining, vol 1, pp 171–179, doi:10.1007/978-81-322-2734-2_18. Print ISBN 978-81-322-2732-8
An NTT, Hagiwara M (2014) Adjective-based estimation of short sentence’s impression. In: International conference on Kansei engineering and emotion research, Keer2014, Linköping
Andreevskaia A, Bergler S (2006) Mining WordNet for fuzzy sentiment: sentiment tag extraction from WordNet glosses. In: 11th conference of the European chapter of the association for computational linguistics, pp 209–216
Assiri FY, Bieman JM (2016) Fault localization for automated program repair: effectiveness and performance. Softw Qual J 1–29. doi:10.1007/s11219-016-9312-z
Bach NX, Van PD, Tai ND, Phuong TM (2015) Mining Vietnamese comparative sentences for sentiment analysis. In: 2015 Seventh international conference on knowledge and systems engineering (KSE), pp 162–167
Ban DQ (2005) Vietnamese grammar. Education Publisher, Vietnam
Ban DQ (2013) Vietnam grammar. Education Publisher, Vietnam
Bang TS, Haruechaiyasak C, Sornlertlamvanich V (2015), Vietnamese sentiment analysis based on term feature selection approach. In: Proceedings of the tenth international conference on knowledge, information and creativity support systems (KICSS2015), Phuket
Bouchon-Meunier B, Coletti G, Rifqi M, Lesot M-J (2009) Towards a conscious choice of a similarity measure: a qualitative point of view. In: 10th European conference on symbolic and quantitative approaches to reasoning with uncertainty (ECSQARU 2009), Verona
Brooke J, Tofiloski M, Taboada M (2009) Cross-linguistic sentiment analysis: from English to Spanish. In: Proceedings of international conference recent advances in natural language processing’2009
Cambria E, Olsher D, Rajagopal D (2014) SenticNet 3: a common and common-sense knowledge base for cognition-driven sentiment analysis, In: AAAI, Quebec City, pp 1515–1521
Cambria E, Poria S, Bajpai R, Schuller B (2016) SenticNet 4: a semantic resource for sentiment analysis based on conceptual primitives. In: COLING, Osaka
Can NT (1998) Vietnamese Grammar. Vietnam National University Publisher, Vietnam
Canuto S, Gonçalves MA, Benevenuto F (2016) Exploiting new sentiment-based meta-level features for effective sentiment analysis. In: Proceedings of the ninth ACM international conference on web search and data mining (WSDM ‘16), New York, pp 53–62
Chen L-S, Chiu H-J (2009) Developing a neural network based index for sentiment classification. In: Proceedings of the international multiconference of engineers and computer scientists, Hong Kong
Choi Y, Cardie C (2008) Learning with compositional semantics as structural inference for subsentential sentiment analysis. In: Proceedings of the 2008 conference on empirical methods in natural language processing, Honolulu, pp 793–801
Choi Y, Cardie C, Riloff E, Patwardhan S (2005) Identifying sources of opinions with conditional random fields and extraction patterns. In: Proceedings of human language technology conference and conference on empirical methods in natural language processing (HLT/EMNLP), Vancouver, pp 355–362
Choi S-S, Cha S-H, Tappert CC (2010) A survey of binary similarity and distance measures. Syst Cybern Inf 8(1):43–48
Cimiano P, Wenderoth J (2007) Automatic acquisition of ranked qualia structures from the web. In: Proceedings of the 45th annual meeting of the association of computational linguistics, Prague, pp 888–895
Dang Yan, Zhang Yulei, Chen HsinChun (2010) A lexicon-enhanced method for sentiment classification: an experiment on online product reviews. IEEE Intell Syst 25(4):46–53
Dat H, Doi TT, Lan DT (1998) Vietnamese establishments. Educational Publisher, Vietnam
De Caceres M, Legendre P, He F (2013) Dissimilarity measurements and the size structure of ecological communities. Methods Ecol Evol 4(12):1167–117
Duyen NT, Bach NX, Phuong TM (2014) An empirical study on sentiment analysis for Vietnamese. In: 2014 International conference on advanced technologies for communications (ATC), pp 309–314
Efron M (2004) Cultural orientation: classifying subjective documents by cociation analysis. In: Proceedings of the AAAI Fall symposium on style and meaning in language, art, music, and design, pp 41–48
El Alami YEM, Nfaoui EH, Beqqali OE (2015) An adjustment similarity measure for improving prediction in collaborative filtering. Glob J Eng Sci Res 5–9. ISSN 2348-8034
Feldman R, Rosenfeld B, Bar-Haimand R, Fresko M (2011) The stock sonar—sentiment analysis of stocks based on a hybrid approach. In: Proceedings of the twenty-third innovative applications of artificial intelligence conference
Feng S, Zhang L, Li B, Wang D, Yu G, Wong K-F (2013), Is Twitter a better corpus for measuring sentiment similarity? In: Proceedings of the 2013 conference on empirical methods in natural language processing, Seattle, pp 897–902
Godbole N, Srinivasaiah M, Skiena S (2007) Large-scale sentiment analysis for news and blogs. In: ICWSM’2007 Boulder
Ha Q-T, Vu T-T, Pham H-T, Luu C-T (2011) An upgrading feature-based opinion mining model on vietnamese product reviews. In: Proceedings of the 7th international conference on Active media technology (AMT 11), pp 173–185
Hao CX (1991) Vietnamese: draft, grammatical function. Social Science Publisher, Vietnam
Hughes RM, Rexstad E, Bond CE (1987) The relationship of aquatic ecoregions, river basins and physiographic provinces to the ichthyogeographic regions of Oregon. American Society of Ichthyologists and Herpetologists (ASIH), pp 423–432
Kieu BT, Pham SB (2010) Sentiment analysis for Vietnamese. In: 2010 second international conference on knowledge and systems engineering (KSE), pp 152–157
Kundi FM, Khan A, Asghar MZ, Ahamd S (2015) Context-aware spelling corrector for sentiment analysis. MAGNT Res Rep 2(6):1–11
LACVIET dictionary software, http://www.lacviet.vn/san-pham/tudienlacviet
Le HS, Le TV, Pham TV (2015) Aspect analysis for opinion mining of Vietnamese text. In: 2015 international conference on advanced computing and applications (ACOMP)
Le H-S, Lee J-H, Lee H-K (2015) Applying machine learning to classify sentiment text for Vietnamese language on social network data. The Korea Society of Management Information Systems, pp 709–714
LINGOES dictionary software, http://www.lingoes.net/
Lu G, Huang P, He L, Cu C, Li X (2010) A new semantic similarity measuring method based on web search engines. J WSEAS Trans Comput 9(1):1–10
Lu Y, Castellanos M, Dayal U, Zhai CX (2011) Automatic construction of a context-aware sentiment lexicon: an optimization approach. In: WWW ‘11 proceedings of the 20th international conference on World wide web, New York, pp 347–356
Manek AS, Shenoy PD, Mohan MC, Venugopal KR (2016) Aspect term extraction for sentiment analysis in large movie reviews using Gini Index feature selection method and SVM classifier. World Wide Web, pp 1–20. doi:10.1007/s11280-015-0381-x. Print ISSN1386-145X
Mann WC, Thompson SA (1988) Rhetorical structure theory: toward a functional theory of text organization. Text 8(3):243–281
Mao H, Gao P, Wang Y, Bollen J (2014) Automatic construction of financial semantic orientation lexicon from large-scale Chinese news corpus. In: The 7th financial risks international forum
Molinero MA, Sagot B, Nicolas L (2009) A morphological and syntactic wide-coverage lexicon for Spanish: the Leffe. In: Proceedings of international conference recent advances in natural language processing’2009, Bulgaria
Nadaf M, Lahane S, Deshpande A, Tirth S (2015) Using business intelligence for mining online reviews for predicting sales performance. Int J Eng Comput Sci 4(5):11718–11717. ISSN:2319-7242
Nasukawa T, Yi J (2003) Sentiment analysis: capturing favorability using natural language processing. In: K-CAP ‘03 proceedings of the 2nd international conference on knowledge capture, New York, pp 70–77
Nguyen NY, Van Khang N, Hao VQ, Thanh PX (2010) Great dictionary of Vietnamese. Ho Chi Minh City National University Publisher, vietnam
Nguyen DQ, Nguyen DQ, Vu T, Pham SB (2014a) Sentiment classification on polarity reviews: an empirical study using rating-based features. In: Proceedings of the 5th workshop on computational approaches to subjectivity, sentiment and social media analysis, pp 128–135
Nguyen HN, Van Le T, Le HS, Pham TV (2014b) Domain specific sentiment dictionary for opinion mining of Vietnamese text. In: Multi-disciplinary trends in artificial intelligence, pp 136–148
Niakšu O (2013) Calculating distance measure for clustering in multi-relational settings. In: Slovenian KDD conference on data mining and data warehouses (SiKDD)
Omhover J-F, Detyniecki M, Rifqi M, Bouchon-Memier B (2004) Ranking invariance between fuzzy similarity measures applied to image retrieval, Hungary
Peinado M, Díaz G, Ocaña-Peinado FM, Aguirre JL, Macías MÁ, Delgadillo J, Aparicio A (2013) Statistical measures of fidelity applied to diagnostic species in plant sociology. Mod Appl Sci 7(6):106–120
Phan D-H, Cao T-D (2014) Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews. In: Proceedings of the fifth symposium on information and communication technology (SoICT 14), New York, pp 232–239
Phe H, Linh HTT, Luong VX (2015) Vietnamese Dictionary 2015. Da Nang Publisher, Vietnam
Phu VN, Tuoi PT (2014) Sentiment classification using enhanced contextual valence shifters. In: International conference on Asian language processing (IALP), pp 224–229
Phu VN, Dat ND, Tran VTN, Chau VTN, Nguyen TA (2016) Fuzzy C-means for English sentiment classification in a distributed system. In: Applied intelligence (APIN), pp 1–22
Polguère A (2000) Towards a theoretically-motivated general public dictionary of semantic derivations and collocations for French. In: Proceedings of EURALEX 2000
Poria S, Gelbukh A, Cambria E, Hussain A, Huang G-B (2014) EmoSenticSpace: a novel framework for affective common-sense reasoning. Knowl Based Syst 69:108–123
Qiu G, Liu B, Bu J, Chen C (2009) Expanding domain sentiment Lexicon through double propagation. In: IJCAI’09 proceedings of the 21st international joint conference on artificial intelligence, pp 1199–1204
Remus R, Quasthoff U, Heyer G (2010) SentiWS—a publicly available German-language resource for sentiment analysis. In: Proceedings of the 7th international language resources and evaluation (LREC’10), pp 1168–1171
Rothfels J, Tibshirani J (2010) Unsupervised sentiment classification of English movie reviews using automatic selection of positive and negative sentiment items, CS224N-Final Project
Song J, He Y, Fu G (2015) Polarity classification of short product reviews via multiple cluster-based SVM classifiers. In: 29th Pacific Asia conference on language, information and computation: posters, Shanghai, pp 267–274
Steinberger J, Ebrahim M, Ehrmann M, Hurriyetoglu A, Kabadjov M, Lenkova P, Steinberger R, Tanev H, Vázquez S, Zavarella V (2012) Creating sentimen dictionaries via triangulation. Decis Support Syst 53(4):689–694
Taboada M, Anthony C, Voll K (2006) Methods for creating semantic orientation dictionaries. In: Proceedings of fifth international conference on language resources and evaluation (LREC 2006), Genoa, pp 427–432
Taboada M, Brooke J, Tofiloski M, Voll K, Stede M (2011) Lexicon-based methods for sentiment analysis. Comput Linguist 37(2):267–307
Tan S, Wang Y, Cheng X (2008) Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples. In: SIGIR ‘08 proceedings of the 31st annual international ACM SIGIR conference on research and development in information retrieval, New York, pp 743–744
TLNET Vietnamese Dictionary, http://www.tlnet.com.vn/tu-dien-tieng-viet/
Tran VTN, Phu VN, Tuoi PT (2014) Learning More Chi square feature selection to improve the fastest and most accurate sentiment classification. In: The third Asian conference on information systems, ACIS
Trinh S, Nguyen L, Vo M, Do P (2016) Lexicon-based sentiment analysis of Facebook comments in Vietnamese language. In: Recent developments in intelligent information and database systems, pp 263–276
Turney P (2002) Thumbs up or thumbs down? In: Semantic orientation applied to unsupervised classification of reviews, proceedings of 40th ACL, pp 417–424
Turney PD, Littman ML (2003) Measuring praise and criticism: inference of semantic orientation from association. ACM Trans Inf Syst (TOIS) 21(4):315–346
Van Anh TT, Dau HX (2014) A crossed-domain sentiment analysis system for the discovery of current careers from social networks. In: Proceedings of the fifth symposium on information and communication technology (SoICT 14), New York, pp 226–231
van Eck NJ, Waltman L (2009) How to normalize co-occurrence data? An analysis of some well-known similarity measures. J Am Soc Inf Sci Technol 60(8):1635–1651
VDict Vietnamese Dictionary, http://vdict.com/
Vietnam Social Science Commission (1993) Vietnamese Grammar. Social Science Publisher, Ha Noi
Voll K, Taboada M (2007) Not all words are created equal: extracting semantic orientation as a function of adjective relevance. In: Proceedings of the 20th Australian joint conference on artificial intelligence, Gold Coast, pp 337–346
Vu X-S, Park S-B (2014) Construction of Vietnamese SentiWordNet by using Vietnamese dictionary. In: The 40th conference of the Korea Information Processing Society, South Korea, pp 745–748
Wang G, Araki K (2007) Modifying SO-PMI for Japanese weblog opinion mining by using a balancing factor and detecting neutral expressions. In: Proceedings of NAACL HLT 2007, Companion Volume, pp 189–192
Yuen RWM, Chan TYW, Lai TBY, Kwong OY, T’sou BKY (2004) Morpheme-based derivation of bipolar semantic orientation of Chinese words. In: Proceedings of the 20th international conference on computational linguistics, Stroudsburg
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Phu, V.N., Chau, V.T.N., Tran, V.T.N. et al. A Vietnamese adjective emotion dictionary based on exploitation of Vietnamese language characteristics. Artif Intell Rev 50, 93–159 (2018). https://doi.org/10.1007/s10462-017-9538-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10462-017-9538-6