{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T16:02:01Z","timestamp":1781366521210,"version":"3.54.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2015,6,20]],"date-time":"2015-06-20T00:00:00Z","timestamp":1434758400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Lang Resources &amp; Evaluation"],"published-print":{"date-parts":[[2016,9]]},"DOI":"10.1007\/s10579-015-9307-6","type":"journal-article","created":{"date-parts":[[2015,6,19]],"date-time":"2015-06-19T05:51:51Z","timestamp":1434693111000},"page":"667-685","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":80,"title":["SentiTurkNet: a Turkish polarity lexicon for sentiment analysis"],"prefix":"10.1007","volume":"50","author":[{"given":"Rahim","family":"Dehkharghani","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yucel","family":"Saygin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Berrin","family":"Yanikoglu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kemal","family":"Oflazer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2015,6,20]]},"reference":[{"key":"9307_CR1","unstructured":"Agarwal, A., Xie, B., Vovsha, I., Rambow, O., & Passonneau, R. (2011). Sentiment analysis of Twitter data. In: Proceedings of the workshop on languages in social media (pp. 30\u201338). Association for Computational Linguistics."},{"key":"9307_CR2","unstructured":"Ak\u0131n, A. A., & Ak\u0131n, M. D. (2007). Zemberek, an open source NLP framework for Turkic languages. Structure, 10, 1\u20135."},{"issue":"3","key":"9307_CR3","first-page":"179","volume":"3","author":"C Aytekin","year":"2013","unstructured":"Aytekin, C. (2013). An opinion mining task in Turkish language: A model for assigning opinions in Turkish blogs to the polarities. Journalism and Mass Communication, 3(3), 179\u2013198.","journal-title":"Journalism and Mass Communication"},{"key":"9307_CR4","first-page":"2200","volume":"10","author":"S Baccianella","year":"2010","unstructured":"Baccianella, S., Esuli, A., & Sebastiani, F. (2010). SentiWordNet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining. LREC, 10, 2200\u20132204.","journal-title":"LREC"},{"issue":"1\u20132","key":"9307_CR5","first-page":"163","volume":"7","author":"O Bilgin","year":"2004","unstructured":"Bilgin, O., \u00c7etino\u011flu, \u00d6., & Oflazer, K. (2004). Building a wordnet for Turkish. Romanian Journal of Information Science and Technology, 7(1\u20132), 163\u2013172.","journal-title":"Romanian Journal of Information Science and Technology"},{"key":"9307_CR6","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1109\/MIS.2013.28","volume":"2","author":"C Bosco","year":"2013","unstructured":"Bosco, C., Patti, V., & Bolioli, A. (2013). Developing corpora for sentiment analysis: The case of irony and senti-tut. IEEE Intelligent Systems, 2, 55\u201363.","journal-title":"IEEE Intelligent Systems"},{"issue":"2","key":"9307_CR7","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1023\/A:1009715923555","volume":"2","author":"CJ Burges","year":"1998","unstructured":"Burges, C. J. (1998). A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2(2), 121\u2013167.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"9307_CR8","doi-asserted-by":"crossref","unstructured":"Cambria, E., Hussain, A., Durrani, T., & Zhang, J. (2012). Towards a chinese common and common sense knowledge base for sentiment analysis. In H. Jiang, W. Ding, M. Ali, X. Wu (Eds.), Advanced research in applied artificial intelligence (pp. 437\u2013446). Berlin, Springer.","DOI":"10.1007\/978-3-642-31087-4_46"},{"key":"9307_CR9","unstructured":"Cambria, E., Olsher, D., & Rajagopal, D. (2014). SenticNet 3: A common and common-sense knowledge base for cognition-driven sentiment analysis. In: Twenty-eighth AAAI conference on artificial intelligence (pp. 1515\u20131521)."},{"key":"9307_CR10","doi-asserted-by":"crossref","unstructured":"Choi, Y., & Cardie, C. (2009). Adapting a polarity lexicon using integer linear programming for domain-specific sentiment classification. In: Proceedings of the 2009 conference on empirical methods in natural language processing: Volume 2-Volume 2 (pp. 590\u2013598). Association for Computational Linguistics.","DOI":"10.3115\/1699571.1699590"},{"key":"9307_CR11","first-page":"56","volume-title":"SentiWordNet for Indian languages","author":"A Das","year":"2010","unstructured":"Das, A., & Bandyopadhyay, S. (2010). SentiWordNet for Indian languages (pp. 56\u201363). China: Asian Federation for Natural Language Processing."},{"key":"9307_CR12","doi-asserted-by":"crossref","unstructured":"Demir\u00f6z, G., Yanikoglu, B., Tapucu, D., & Saygin, Y. (2012). Learning domain-specific polarity lexicons. In: 2012 IEEE 12th international conference on data mining workshops (ICDMW) (pp. 674\u2013679). IEEE.","DOI":"10.1109\/ICDMW.2012.120"},{"key":"9307_CR13","unstructured":"Ero\u011ful, U. (2009). Sentiment analysis in Turkish. MSc thesis, Middle East University, Turkey."},{"key":"9307_CR14","unstructured":"Gezici, G., Yanikoglu, B., Tapucu, D., & Sayg\u0131n, Y. (2012). New features for sentiment analysis: Do sentences matter? In: SDAD 2012 The 1st international workshop on sentiment discovery from affective data (p. 5)."},{"key":"9307_CR15","unstructured":"Hatzivassiloglou, V., & Mckeown, K. R. (1997). Predicting the semantic orientation of adjectives. In: Proceedings of ACL-97, 35th annual meeting (pp. 174\u2013181). Association for Computational Linguistics."},{"key":"9307_CR16","doi-asserted-by":"crossref","unstructured":"Havasi, C., Cambria, E., Schuller, B., Liu, B., & Wang, H. (2013). Knowledge-based approaches to concept-level sentiment analysis. IEEE Intelligent Systems, 28(2), 12\u201314.","DOI":"10.1109\/MIS.2013.45"},{"key":"9307_CR17","unstructured":"Havasi, C., Speer, R., & Alonso, J. (2007). ConceptNet 3: A flexible, multilingual semantic network for common sense knowledge. In N. Nicolov, G. Angelova and R. Mitkov (Eds.), Recent advances in natural language processing (RANLP) (pp. 27\u201329). Borovets."},{"key":"9307_CR18","volume-title":"Neural networks: A comprehensive foundation","author":"S Haykin","year":"1994","unstructured":"Haykin, S. (1994). Neural networks: A comprehensive foundation. Upper Saddle River, NJ: Prentice Hall."},{"key":"9307_CR19","doi-asserted-by":"crossref","unstructured":"Holmes, G., Donkin, A., & Witten, I. H. (1994). Weka: A machine learning workbench. In: Proceedings of the 1994 second Australian and New Zealand conference on intelligent information systems, 1994 (pp. 357\u2013361). IEEE.","DOI":"10.1109\/ANZIIS.1994.396988"},{"key":"9307_CR20","volume-title":"Applied logistic regression","author":"DW Hosmer Jr","year":"2004","unstructured":"Hosmer, D. W, Jr, & Lemeshow, S. (2004). Applied logistic regression. New Jersey: Wiley."},{"key":"9307_CR21","doi-asserted-by":"crossref","unstructured":"Hu, M., & Liu, B. (2004). Mining and summarizing customer reviews. In: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 168\u2013177). ACM.","DOI":"10.1145\/1014052.1014073"},{"issue":"2","key":"9307_CR22","doi-asserted-by":"crossref","first-page":"0047","DOI":"10.1109\/MIS.2013.1","volume":"28","author":"C Hung","year":"2013","unstructured":"Hung, C., & Lin, H.-K. (2013). Using objective words in SentiWordNet to improve word-of-mouth sentiment classification. IEEE Intelligent Systems, 28(2), 0047\u201354.","journal-title":"IEEE Intelligent Systems"},{"key":"9307_CR23","doi-asserted-by":"crossref","unstructured":"Kaya, M., Fidan, G., & Toroslu, I. H. (2012). Sentiment analysis of Turkish political news. In: Proceedings of the the 2012 IEEE\/WIC\/ACM international joint conferences on web intelligence and intelligent agent technology-Volume 01 (pp. 174\u2013180). IEEE Computer Society.","DOI":"10.1109\/WI-IAT.2012.115"},{"key":"9307_CR24","unstructured":"Lenat, D. B., & Guha, R. V. (1989). Building large knowledge-based systems; Representation and inference in the Cyc project. Menlo Park: Addison-Wesley Longman Publishing Co., Inc."},{"key":"9307_CR25","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-02145-9","volume-title":"Sentiment analysis and opinion mining","author":"B Liu","year":"2012","unstructured":"Liu, B. (2012). Sentiment analysis and opinion mining. USA: Morgan and Claypool Publishers."},{"issue":"11","key":"9307_CR26","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1145\/219717.219748","volume":"38","author":"GA Miller","year":"1995","unstructured":"Miller, G. A. (1995). Wordnet: A lexical database for English. Communications of the ACM, 38(11), 39\u201341.","journal-title":"Communications of the ACM"},{"key":"9307_CR27","unstructured":"Mitchell, T. M. (1997). Machine learning., McGraw-Hill series in computer science New York: McGraw Hill."},{"issue":"3","key":"9307_CR28","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1111\/j.1467-8640.2012.00460.x","volume":"29","author":"SM Mohammad","year":"2013","unstructured":"Mohammad, S. M., & Turney, P. D. (2013). Crowdsourcing a word-emotion association lexicon. Computational Intelligence, 29(3), 436\u2013465.","journal-title":"Computational Intelligence"},{"key":"9307_CR29","unstructured":"Oflazer, K., & Boz\u015fahin, H. C. (1994). Turkish natural language processing initiative. In: Proceedings of the third Turkish symposium on artificial intelligence and artificial neural networks, Ankara, Turkey."},{"key":"9307_CR30","unstructured":"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-Volume 10 (pp. 79\u201386). Association for Computational Linguistics."},{"issue":"2","key":"9307_CR31","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1109\/MIS.2013.4","volume":"28","author":"S Poria","year":"2013","unstructured":"Poria, S., Gelbukh, A., Hussain, A., Howard, N., Das, D., & Bandyopadhyay, S. (2013). Enhanced SenticNet with affective labels for concept-based opinion mining. IEEE Intelligent Systems, 28(2), 31\u201338.","journal-title":"IEEE Intelligent Systems"},{"key":"9307_CR32","first-page":"1083","volume":"4","author":"C Strapparava","year":"2004","unstructured":"Strapparava, C., Valitutti, A., et al. (2004). Wordnet affect: An affective extension of wordnet. LREC, 4, 1083\u20131086.","journal-title":"LREC"},{"key":"9307_CR33","doi-asserted-by":"crossref","unstructured":"Sureka, A., Goyal, V., Correa, D., & Mondal, A. (2009). Polarity classification of subjective words using common-sense knowledge-base. In H. Sakai, M. Chakraborty, A.-E. Hassanien, D. Slezak, W. Zhu (Eds.), Rough sets, fuzzy sets, data mining and granular computing (pp. 486\u2013493). Berlin: Springer.","DOI":"10.1007\/978-3-642-10646-0_59"},{"issue":"1","key":"9307_CR34","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1002\/asi.21662","volume":"63","author":"M Thelwall","year":"2012","unstructured":"Thelwall, M., Buckley, K., & Paltoglou, G. (2012). Sentiment strength detection for the social web. Journal of the American Society for Information Science and Technology, 63(1), 163\u2013173.","journal-title":"Journal of the American Society for Information Science and Technology"},{"issue":"2","key":"9307_CR35","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MIS.2013.25","volume":"28","author":"AC-R Tsai","year":"2013","unstructured":"Tsai, A. C.-R., Wu, C.-E., Tsai, R. T.-H., Hsu, J. Y.-J., et al. (2013). Building a concept-level sentiment dictionary based on commonsense knowledge. IEEE Intelligent Systems, 28(2), 22\u201330.","journal-title":"IEEE Intelligent Systems"},{"key":"9307_CR36","unstructured":"Turney, P. D. (2002). Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th annual meeting on association for computational linguistics (pp. 417\u2013424). Association for Computational Linguistics."},{"key":"9307_CR37","unstructured":"Vural, A. G., Cambazo\u011flu, B. B., \u015eenkul, P., & Tokg\u00f6z, Z. \u00d6. (2012). A framework for sentiment analysis in Turkish: Application to polarity detection of movie reviews in Turkish. In: E. Gelenbe, & R. Lent (Eds.), ISCIS (pp. 437\u2013445). London: Springer."},{"issue":"2","key":"9307_CR38","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1007\/s12559-012-9183-y","volume":"5","author":"Q-F Wang","year":"2013","unstructured":"Wang, Q.-F., Cambria, E., Liu, C.-L., & Hussain, A. (2013). Common sense knowledge for handwritten chinese text recognition. Cognitive Computation, 5(2), 234\u2013242.","journal-title":"Cognitive Computation"},{"key":"9307_CR39","doi-asserted-by":"crossref","unstructured":"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 (pp. 347\u2013354). Association for Computational Linguistics.","DOI":"10.3115\/1220575.1220619"},{"issue":"3","key":"9307_CR40","doi-asserted-by":"crossref","first-page":"6527","DOI":"10.1016\/j.eswa.2008.07.035","volume":"36","author":"Q Ye","year":"2009","unstructured":"Ye, Q., Zhang, Z., & Law, R. (2009). Sentiment classification of online reviews to travel destinations by supervised machine learning approaches. Expert Systems with Applications, 36(3), 6527\u20136535.","journal-title":"Expert Systems with Applications"}],"container-title":["Language Resources and Evaluation"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10579-015-9307-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10579-015-9307-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10579-015-9307-6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T16:13:15Z","timestamp":1691770395000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10579-015-9307-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,6,20]]},"references-count":40,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2016,9]]}},"alternative-id":["9307"],"URL":"https:\/\/doi.org\/10.1007\/s10579-015-9307-6","relation":{},"ISSN":["1574-020X","1574-0218"],"issn-type":[{"value":"1574-020X","type":"print"},{"value":"1574-0218","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,6,20]]}}}