{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T18:39:46Z","timestamp":1768415986489,"version":"3.49.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2017,9,5]],"date-time":"2017-09-05T00:00:00Z","timestamp":1504569600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cogn Comput"],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1007\/s12559-017-9503-3","type":"journal-article","created":{"date-parts":[[2017,9,5]],"date-time":"2017-09-05T00:37:54Z","timestamp":1504571874000},"page":"868-894","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":54,"title":["Sentence-Level Emotion Detection Framework Using Rule-Based Classification"],"prefix":"10.1007","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3320-2074","authenticated-orcid":false,"given":"Muhammad Zubair","family":"Asghar","sequence":"first","affiliation":[]},{"given":"Aurangzeb","family":"Khan","sequence":"additional","affiliation":[]},{"given":"Afsana","family":"Bibi","sequence":"additional","affiliation":[]},{"given":"Fazal Masud","family":"Kundi","sequence":"additional","affiliation":[]},{"given":"Hussain","family":"Ahmad","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,5]]},"reference":[{"issue":"2","key":"9503_CR1","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1007\/s12559-012-9183-y","volume":"5","author":"QF Wang","year":"2013","unstructured":"Wang QF, Cambria E, Liu CL, Hussain A. Common sense knowledge for handwritten Chinese recognition. Cogn Comput. 2013;5(2):234\u201342.","journal-title":"Cogn Comput"},{"issue":"4","key":"9503_CR2","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1007\/s12559-015-9380-6","volume":"8","author":"L Yang","year":"2016","unstructured":"Yang L, Lin H, Lin Y, Liu S. Detection and extraction of hot topics on Chinese microblogs. Cogn Comput. 2016;8(4):577\u201386.","journal-title":"Cogn Comput"},{"issue":"4","key":"9503_CR3","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1007\/s12559-014-9316-6","volume":"7","author":"B Agarwal","year":"2015","unstructured":"Agarwal B, Poria S, Mittal N, Gelbukh A, Hussain A. Concept-level sentiment analysis with dependency-based semantic parsing: a novel approach. Cogn Comput. 2015;7(4):487\u201399.","journal-title":"Cogn Comput"},{"issue":"1","key":"9503_CR4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12559-015-9374-4","volume":"8","author":"R Sun","year":"2016","unstructured":"Sun R, Wilson N, Lynch M. Emotion: a unified mechanistic interpretation from a cognitive architecture. Cogn Comput. 2016;8(1):1\u201314.","journal-title":"Cogn Comput"},{"issue":"2","key":"9503_CR5","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/coin.12024","volume":"31","author":"SM Mohammad","year":"2015","unstructured":"Mohammad SM, Kiritchenko S. Using hashtags to capture fine emotion categories from tweets. Comput Intell. 2015;31(2):301\u201326.","journal-title":"Comput Intell"},{"issue":"4","key":"9503_CR6","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1007\/s12559-012-9173-0","volume":"4","author":"D Das","year":"2012","unstructured":"Das D, Bandyopadhyay S. Sentence-level emotion and valence tagging. Cogn Comput. 2012;4(4):420\u201335.","journal-title":"Cogn Comput"},{"key":"9503_CR7","first-page":"1","volume":"49","author":"SA Crossley","year":"2016","unstructured":"Crossley SA, Kyle K, McNamara DS. Sentiment Analysis and Social Cognition Engine (SEANCE): an automatic tool for sentiment, social cognition, and social-order analysis. Behav Res Methods. 2016;49:1\u201319.","journal-title":"Behav Res Methods"},{"issue":"2","key":"9503_CR8","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1007\/s11042-011-0815-0","volume":"59","author":"E Cambria","year":"2012","unstructured":"Cambria E, Grassi M, Hussain A, Havasi C. Sentic computing for social media marketing. Multimed Tools Appl. 2012;59(2):557\u201377.","journal-title":"Multimed Tools Appl"},{"key":"9503_CR9","doi-asserted-by":"crossref","unstructured":"Cambria E, Hussain A, Havasi C, Eckl C. Common sense computing: from the society of mind to digital intuition and beyond. In: LNCS, 5707. Berlin:Springer; 2009. p. 252\u2013259.","DOI":"10.1007\/978-3-642-04391-8_33"},{"key":"9503_CR10","doi-asserted-by":"crossref","unstructured":"Shaila SG, Vadivel A. Cognitive based sentence level emotion estimation through emotional expressions. In: Progress in systems engineering. Springer International Publishing; 2015. p. 707\u2013713.","DOI":"10.1007\/978-3-319-08422-0_100"},{"issue":"2","key":"9503_CR11","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1109\/MIS.2016.31","volume":"31","author":"E Cambria","year":"2016","unstructured":"Cambria E. Affective computing and sentiment analysis. IEEE Intell Syst. 2016;31(2):102\u20137.","journal-title":"IEEE Intell Syst"},{"issue":"1","key":"9503_CR12","first-page":"105","volume":"2","author":"C Quan","year":"2010","unstructured":"Quan C, Ren F. Sentence emotion analysis and recognition based on emotion words using Ren-CECps. Int J Adv Intel. 2010;2(1):105\u201317.","journal-title":"Int J Adv Intel"},{"key":"9503_CR13","doi-asserted-by":"crossref","unstructured":"Li J, Ren F. Creating a Chinese emotion lexicon based on corpus Ren-CECps. In Cloud Computing and Intelligence Systems (CCIS), 2011 I.E. International Conference on 2011 Sep 15 IEEE; p. 80-84.","DOI":"10.1109\/CCIS.2011.6045036"},{"key":"9503_CR14","doi-asserted-by":"crossref","unstructured":"Socher R, Perelygin A, Wu JY, Chuang J, Manning CD, Ng AY, Potts C. Recursive deep models for semantic compositionality over a sentiment treebank. In: Proceedings of the conference on empirical methods in natural language processing (EMNLP) 2013 Oct 18 Vol. 1631. p. 1642.","DOI":"10.18653\/v1\/D13-1170"},{"key":"9503_CR15","doi-asserted-by":"publisher","unstructured":"Poria S, Chaturvedi I, Cambria E, Hussain A. Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis,\" 2016 IEEE 16th International Conference on Data Mining (ICDM), Barcelona pp. 439-448. doi: 10.1109\/ICDM.2016.0055 .","DOI":"10.1109\/ICDM.2016.0055"},{"key":"9503_CR16","doi-asserted-by":"crossref","unstructured":"Severyn A, Moschitti A. Twitter sentiment analysis with deep convolutional neural networks. In: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval 2015. ACM; p. 959-962.","DOI":"10.1145\/2766462.2767830"},{"key":"9503_CR17","doi-asserted-by":"publisher","unstructured":"Aminu M, Nirmalie W, Robert L. Contextual sentiment analysis for social media genres. Knowl-Based Syst. 2016; doi: 10.1016\/j.knosys.2016.05.032 .","DOI":"10.1016\/j.knosys.2016.05.032"},{"issue":"3","key":"9503_CR18","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/MCI.2016.2572518","volume":"11","author":"RG Pensa","year":"2016","unstructured":"Pensa RG, Sapino ML, Schifanella C, Vignaroli L. Leveraging cross-domain social media analytics to understand TV topics popularity. IEEE Comput Intell Mag. 2016;11(3):10\u201321.","journal-title":"IEEE Comput Intell Mag"},{"key":"9503_CR19","doi-asserted-by":"crossref","unstructured":"Chaumartin FR. UPAR7: a knowledge-based system for headline sentiment tagging, Proceedings of the 4th International Workshop on Semantic Evaluations. Association for Computational Linguistics, 2007.","DOI":"10.3115\/1621474.1621568"},{"key":"9503_CR20","unstructured":"WordNet Domains available at: http:\/\/wndomains.fbk.eu\/index.html , last accessed on April 12, 2016."},{"key":"9503_CR21","unstructured":"Wordnet-Affect available at : http:\/\/wndomains.fbk.eu\/index.html , last accessed on May 20, 2016."},{"key":"9503_CR22","unstructured":"SentiWordNet (SentiWordNet available at: http:\/\/sentwordnet.isti.cnr.it \/, last accessed on August 5, 2016."},{"key":"9503_CR23","doi-asserted-by":"crossref","unstructured":"A. Agrawal, A. An. Unsupervised emotion detection from text using semantic and syntactic relations, In: Web Intelligence and Intelligent Agent Technology (WI-IAT), IEEE\/WIC\/ACM International Conferences on Vol. 1. 2012. 346\u2013353.","DOI":"10.1109\/WI-IAT.2012.170"},{"key":"9503_CR24","doi-asserted-by":"crossref","unstructured":"Gievska S, Koroveshovski K, Chavdarova T A hybrid approach for emotion detection in support of affective interaction. In: 2014 I.E. International Conference on Data Mining Workshop. IEEE; 2014. p. 352-359.","DOI":"10.1109\/ICDMW.2014.130"},{"key":"9503_CR25","unstructured":"Cambria E, Olsher D, Rajagopal D. SenticNet 3: a common and common-sense knowledge base for cognition-driven sentiment analysis. In: Twenty-eighth AAAI conference on artificial intelligence, 2014."},{"key":"9503_CR26","doi-asserted-by":"publisher","unstructured":"Boratto L, Carta S, Fenu G, Saia R. Using neural word embeddings to model user behavior and detect user segments. Knowl-Based Syst. 2016; doi: 10.1016\/j.knosys.2016.05.002 .","DOI":"10.1016\/j.knosys.2016.05.002"},{"key":"9503_CR27","unstructured":"Ekman\u2019s basic emotions, available at: https:\/\/www.paulekman.com\/wp-content\/uploads\/2013\/07\/Basic-Emotions.pdf , last accessed on September 24, 2016."},{"key":"9503_CR28","unstructured":"NRC emotion lexicon, available at: http:\/\/saifmohammad.com\/WebDocs\/NRC-Emotion-Lexicon-v0.92-InManyLanguages-web.xlsx , last accessed on November 10, 2016."},{"key":"9503_CR29","doi-asserted-by":"crossref","unstructured":"Douglas-Cowie E, Cowie R, Sneddon I, Cox C, Lowry O, Mcrorie M, Martin JC, Devillers L, Abrilian S, Batliner A, Amir N. The HUMAINE database: addressing the collection and annotation of naturalistic and induced emotional data. In: International Conference on Affective Computing and Intelligent Interaction 2007 Sep 12 Springer Berlin Heidelberg. p. 488-500).","DOI":"10.1007\/978-3-540-74889-2_43"},{"key":"9503_CR30","unstructured":"Cambria E, Poria S, Bajpai R, Schuller B. SenticNet 4: a semantic resource for sentiment analysis based on conceptual primitives. In: COLING, 2016. 2666\u20132677."},{"issue":"2","key":"9503_CR31","doi-asserted-by":"publisher","first-page":"e0171649","DOI":"10.1371\/journal.pone.0171649","volume":"12","author":"MZ Asghar","year":"2017","unstructured":"Asghar MZ, Khan A, Ahmad S, Qasim M, Khan IA. Lexicon-enhanced sentiment analysis framework using rule-based classification scheme. PLoS One. 2017;12(2):e0171649. doi: 10.1371\/journal.pone.0171649 .","journal-title":"PLoS One"},{"issue":"4","key":"9503_CR32","first-page":"103","volume":"4","author":"M Romanyshyn","year":"2013","unstructured":"Romanyshyn M. Rule-based sentiment analysis of Ukrainian reviews. Int J Artif Intell Appl. 2013;4(4):103.","journal-title":"Int J Artif Intell Appl"},{"issue":"9","key":"9503_CR33","first-page":"66","volume":"11","author":"F Kundi","year":"2014","unstructured":"Kundi F, Ahmad S, Khan A, Asghar. Detection and scoring of internet slangs for sentiment analysis using SentiWordNet. Life Sci J. 2014;11(9):66\u201372.","journal-title":"Life Sci J"},{"key":"9503_CR34","doi-asserted-by":"crossref","unstructured":"Pang, Lee L. Seeing stars: exploiting class relationships for sentiment categorization with respect to rating scales. In: ACL; 2005. p. 115\u2013124, .","DOI":"10.3115\/1219840.1219855"},{"issue":"10","key":"9503_CR35","doi-asserted-by":"crossref","first-page":"e0140204","DOI":"10.1371\/journal.pone.0140204","volume":"10","author":"MZ Asghar","year":"2015","unstructured":"Asghar MZ, et al. A unified framework for creating domain dependent polarity lexicons from user generated reviews. PLoS One. 2015;10(10):e0140204.","journal-title":"PLoS One"},{"issue":"1","key":"9503_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40064-016-2809-x","volume":"5","author":"MZ Asghar","year":"2016","unstructured":"Asghar MZ, Ahmad S, Qasim M, Zahra R, Kundi FM. SentiHealth: creating health-related sentiment lexicon using hybrid approach. SpringerPlus. 2016;5(1):1\u201323. doi: 10.1186\/s40064-016-2809-x .","journal-title":"SpringerPlus"}],"container-title":["Cognitive Computation"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s12559-017-9503-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-017-9503-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12559-017-9503-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T15:22:24Z","timestamp":1750864944000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s12559-017-9503-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,9,5]]},"references-count":36,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2017,12]]}},"alternative-id":["9503"],"URL":"https:\/\/doi.org\/10.1007\/s12559-017-9503-3","relation":{},"ISSN":["1866-9956","1866-9964"],"issn-type":[{"value":"1866-9956","type":"print"},{"value":"1866-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,9,5]]}}}