{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T07:26:50Z","timestamp":1767166010068,"version":"3.48.0"},"publisher-location":"Singapore","reference-count":41,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819958368"},{"type":"electronic","value":"9789819958375"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-99-5837-5_5","type":"book-chapter","created":{"date-parts":[[2023,9,4]],"date-time":"2023-09-04T01:01:29Z","timestamp":1693789289000},"page":"52-62","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Survey of\u00a0Explainable Artificial Intelligence Approaches for\u00a0Sentiment Analysis"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6370-2913","authenticated-orcid":false,"given":"Bernadetta","family":"Maleszka","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,5]]},"reference":[{"key":"5_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105801","volume":"119","author":"HF Alsaif","year":"2023","unstructured":"Alsaif, H.F., Aldosssari, H.D.: Review of stance detection for rumor verification in social media. Eng. Appl. Artif. Intell. 119, 105801 (2023)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"5_CR2","doi-asserted-by":"crossref","unstructured":"Arras, L., Montavon, G., Muller, K.R., Samek, W.: Explaining recurrent neural network predictions in sentiment analysis. In: Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pp. 159\u2013168 (2017)","DOI":"10.18653\/v1\/W17-5221"},{"issue":"2020","key":"5_CR3","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.inffus.2019.12.012","volume":"58","author":"AB Arrieta","year":"2020","unstructured":"Arrieta, A.B., et al.: Explainable Artificial Intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI. Inf. Fusion 58(2020), 82\u2013115 (2020)","journal-title":"Inf. Fusion"},{"key":"5_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.106087","volume":"122","author":"AB Athira","year":"2023","unstructured":"Athira, A.B., Kumar, S.D.M., Chacko, A.M.: A systematic survey on explainable AI applied to fake news detection. Eng. Appl. Artif. Intell. 122, 106087 (2023)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"2021","key":"5_CR5","first-page":"107","volume":"226","author":"M Birjali","year":"2021","unstructured":"Birjali, M., Kasri, M., Beni-Hssane, A.: A comprehensive survey on sentiment analysis: approaches, challenges and trends. Knowl.-Based Syst. 226(2021), 107\u2013134 (2021)","journal-title":"Knowl.-Based Syst."},{"issue":"2019","key":"5_CR6","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1016\/j.patrec.2019.04.024","volume":"125","author":"I Chaturvedi","year":"2019","unstructured":"Chaturvedi, I., Satapathy, R., Cavallari, S., Cambria, E.: Fuzzy commonsense reasoning for multimodal sentiment analysis. Pattern Recogn. Lett. 125(2019), 264\u2013270 (2019)","journal-title":"Pattern Recogn. Lett."},{"key":"5_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2021.103525","volume":"299","author":"R Dazeley","year":"2021","unstructured":"Dazeley, R., Vamplew, P., Foale, C., Young, Ch., Aryal, S., Cruz, F.: Levels of explainable artificial intelligence for human-aligned conversational explanations. Artif. Intell. 299, 103525 (2021)","journal-title":"Artif. Intell."},{"issue":"2022","key":"5_CR8","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1016\/j.ins.2022.10.013","volume":"615","author":"W Ding","year":"2022","unstructured":"Ding, W., Abdel-Basset, M., Hawash, H., Ali, A.M.: Explainability of artificial intelligence methods, applications and challenges: a comprehensive survey. Inf. Sci. 615(2022), 238\u2013292 (2022)","journal-title":"Inf. Sci."},{"key":"5_CR9","doi-asserted-by":"publisher","unstructured":"Dwivedi, Y.K., Kshetri, N., et al.: \u201cSo what if ChatGPT wrote it?\" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. Int. J. Inf. Manage. 71, 102642 (2023). https:\/\/doi.org\/10.1016\/j.ijinfomgt.2023.102642. ISSN 0268\u20134012","DOI":"10.1016\/j.ijinfomgt.2023.102642"},{"key":"5_CR10","unstructured":"Esuli, A., Sebastiani, F.: SentiWordNet - a publicly available lexical resource for opinion mining. In: Proceedings of the 5th Conference on Language Resources and Evaluation (LREC 2006), pp. 417\u2013422 (2006)"},{"key":"5_CR11","unstructured":"Fernandez, C., Provost, F., Han, X.: Explaining data-driven decisions made by AI systems: the counterfactual approach (2020). arXiv:2001.07417v1. Accessed 5 Mar 2023"},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Fiok, K., Karwowski, W., Gutierrez, E., Wilamowski, M.: Twitter account: comparison of model performance and explainability of predictions. Expert Syst. Appl. 186, 115771 (2021)","DOI":"10.1016\/j.eswa.2021.115771"},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Fuhrman, J.D., Gorre, N., Hu, Q., Li, H., El Naqa, I., Giger, M.L.: A review of explainable and interpretable AI with applications in COVID-19 imaging. Med. Phys. 49(1), 1\u201314 (2022). https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/mp.15359","DOI":"10.1002\/mp.15359"},{"key":"5_CR14","unstructured":"Gilpin, L.H., Bau, D., Yuan, B.Z., Bajwa, A., Specter, M., Kagal, L.: Explaining explanations: an overview of interpretability of machine learning (2019). arXiv:1806.00069v3. Accessed 18 Mar 2023"},{"key":"5_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107390","volume":"108","author":"K Gutierrez-Batista","year":"2021","unstructured":"Gutierrez-Batista, K., Vila, M.-A., Martin-Bautista, M.J.: Building a fuzzy sentiment dimension for multidimensional analysis in social networks. Appl. Soft Comput. 108, 107390 (2021)","journal-title":"Appl. Soft Comput."},{"issue":"11","key":"5_CR16","doi-asserted-by":"publisher","first-page":"21241","DOI":"10.1109\/TITS.2022.3172442","volume":"23","author":"S Hacohen","year":"2022","unstructured":"Hacohen, S., Medina, O., Shoval, S.: Autonomous driving: a survey of technological gaps using google scholar and web of science trend analysis. IEEE Trans. Intell. Transp. Syst. 23(11), 21241\u201321258 (2022)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"30","key":"5_CR17","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1016\/j.jksues.2016.04.002","volume":"2018","author":"DMEDM Hussein","year":"2018","unstructured":"Hussein, D.M.E.D.M.: A survey on sentiment analysis challenges. J. King Saud Univ. Eng. Sci. 2018(30), 330\u2013338 (2018)","journal-title":"J. King Saud Univ. Eng. Sci."},{"key":"5_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107455","volume":"231","author":"M L\u00f3pez","year":"2021","unstructured":"L\u00f3pez, M., Mart\u00ednez-C\u00e1mara, E., Luz\u00f3n, V., Herrera, F.: ADOPS: Aspect Discovery OPinion Summarisation Methodology based on deep learning and subgroup discovery for generating explainable opinion summaries. Knowl.-Based Syst. 231, 107455 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"5_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107525","volume":"233","author":"C Liu","year":"2021","unstructured":"Liu, C., Xu, X.: AMFF: a new attention-based multi-feature fusion method for intention recognition. Knowl.-Based Syst. 233, 107525 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"5_CR20","unstructured":"Lundberg, S.M., Lee, S.-I.: A unified approach to interpreting model predictions. In: NIPS 2017: Proceedings of the 31st International Conference on Neural Information Processing Systems, pp. 4768\u20134777 (2017)"},{"key":"5_CR21","doi-asserted-by":"publisher","unstructured":"L\u00f6tsch, J., Ultsch, A.: Enhancing explainable machine learning by reconsidering initially unselected items in feature selection for classification. Biomedinformatics 2, 701\u2013714 (2022). https:\/\/doi.org\/10.3390\/biomedinformatics2040047","DOI":"10.3390\/biomedinformatics2040047"},{"key":"5_CR22","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.1016\/j.asej.2014.04.011","volume":"5","author":"W Medhat","year":"2014","unstructured":"Medhat, W., Hassan, A., Korashy, H.: Sentiment analysis algorithms and applications: a survey. Ain Shams Eng. J. 5, 1093\u20131113 (2014)","journal-title":"Ain Shams Eng. J."},{"key":"5_CR23","unstructured":"Montavon, G., Samek, W., Muller, K.R.: Methods for interpreting and understanding deep neural networks (2017). https:\/\/arxiv.org\/pdf\/1706.07979.pdf. Accessed 21 Mar 2023"},{"key":"5_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113941","volume":"165","author":"M Moradi","year":"2021","unstructured":"Moradi, M., Samwald, M.: Post-hoc explanation of black-box classifiers using confident itemsets. Expert Syst. Appl. 165, 113941 (2021)","journal-title":"Expert Syst. Appl."},{"key":"5_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113596","volume":"159","author":"AH Nabizadeh","year":"2020","unstructured":"Nabizadeh, A.H., Leal, J.P., Rafsanjani, H.N., Shah, R.R.: Learning path personalization and recommendation methods: a survey of the state-of-the-art. Expert Syst. Appl. 159, 113596 (2020)","journal-title":"Expert Syst. Appl."},{"key":"5_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107162","volume":"226","author":"T-S Nguyen","year":"2021","unstructured":"Nguyen, T.-S., Wu, Z., Ong, D.C.: Attention uncovers task-relevant semantics in emotional narrative understanding. Knowl.-Based Syst. 226, 107162 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"5_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107332","volume":"229","author":"I Perikos","year":"2021","unstructured":"Perikos, I., Kardakis, S., Hatzilygeroudis, I.: Sentiment analysis using novel and interpretable architectures of Hidden Markov Models. Knowl.-Based Syst. 229, 107332 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"5_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110235","volume":"139","author":"HT Phan","year":"2023","unstructured":"Phan, H.T., Nguyen, N.T., Hwang, D.: Fake news detection: a survey of graph neural network methods. Appl. Soft Comput. 139, 110235 (2023)","journal-title":"Appl. Soft Comput."},{"issue":"4","key":"5_CR29","doi-asserted-by":"publisher","first-page":"403","DOI":"10.15625\/1813-9663\/37\/4\/15892","volume":"37","author":"HT Phan","year":"2021","unstructured":"Phan, H.T., Nguyen, N.T., Hwang, D.: Sentiment analysis for opinions on social media: a survey. J. Comput. Sci. Cybern. 37(4), 403\u2013428 (2021)","journal-title":"J. Comput. Sci. Cybern."},{"key":"5_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2022.103058","volume":"59","author":"M Polignano","year":"2022","unstructured":"Polignano, M., Basile, V., Basile, P., Gabrieli, G., Vassallo, M., Bosco, C.: A hybrid lexicon-based and neural approach for explainable polarity detection. Inf. Process. Manage. 59, 103058 (2022)","journal-title":"Inf. Process. Manage."},{"key":"5_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107018","volume":"222","author":"J Serrano-Guerrero","year":"2021","unstructured":"Serrano-Guerrero, J., Romero, F.P., Olivias, J.A.: Fuzzy logic applied to opinion mining: a review. Knowl.-Based Syst. 222, 107018 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"5_CR32","unstructured":"da Silva, M.P.: Feature Selection using SHAP: an Explainable AI approach. University of Brasilia. Doctoral thesis (2021)"},{"key":"5_CR33","doi-asserted-by":"crossref","unstructured":"So, Ch.: Understanding the prediction mechanism of sentiments by XAI visualization. In: 4th International Conference on Natural Language Processing and Information Retrieval, Sejong, South Korea, 18\u201320 December 2020. ACM (2020)","DOI":"10.1145\/3443279.3443284"},{"key":"5_CR34","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1007\/978-3-030-50334-5_28","volume-title":"Artificial Intelligence in HCI","author":"C So","year":"2020","unstructured":"So, C.: What emotions make one or five stars? Understanding ratings of online product reviews by sentiment analysis and XAI. In: Degen, H., Reinerman-Jones, L. (eds.) HCII 2020. LNCS, vol. 12217, pp. 412\u2013421. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-50334-5_28"},{"key":"5_CR35","doi-asserted-by":"publisher","unstructured":"Song, M.H.: A study on explainable artificial intelligence-based sentimental analysis system model. Int. J. Internet Broadcast. Commun. 14(1), 142\u2013151 (2022). https:\/\/doi.org\/10.7236\/IJIBC.2022.1.142","DOI":"10.7236\/IJIBC.2022.1.142"},{"key":"5_CR36","doi-asserted-by":"crossref","unstructured":"de Souza Jr., L.A., et al.: Convolutional Neural Networks for the evaluation of cancer in Barrett\u2019s esophagus: explainable AI to lighten up the black-box. Comput. Biol. Med. 135, 104578 (2021)","DOI":"10.1016\/j.compbiomed.2021.104578"},{"key":"5_CR37","unstructured":"Ventura, F., Greco, S., Apiletti, D., Cerquitelli, T.: Explaining the Deep Natural Language Processing by Mining Textual Interpretable Features (2021). https:\/\/arxiv.org\/abs\/2106.06697. Accessed 31 Mar 2023"},{"key":"5_CR38","doi-asserted-by":"publisher","unstructured":"Zacharias, J., von Zahn, M., Chen, J., Hinz, O.: Designing a feature selection method based on explainable artificial intelligence. Electron. Mark. 32, 2159\u20132184 (2022). https:\/\/doi.org\/10.1007\/s12525-022-00608-1","DOI":"10.1007\/s12525-022-00608-1"},{"key":"5_CR39","doi-asserted-by":"publisher","unstructured":"Zhang, L., Wang, S., Liu, B.: Deep learning for sentiment analysis: a survey (2018). https:\/\/doi.org\/10.1002\/widm.1253. Accessed 11 Mar 2023","DOI":"10.1002\/widm.1253"},{"key":"5_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107220","volume":"227","author":"A Zhao","year":"2021","unstructured":"Zhao, A., Yu, Y.: Knowledge-enabled BERT for aspect-based sentiment analysis. Knowl.-Based Syst. 227, 107220 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"5_CR41","unstructured":"https:\/\/elula.ai\/feature-importances-are-not-good-enough\/. Accessed 10 Mar 2023"}],"container-title":["Lecture Notes in Computer Science","Intelligent Information and Database Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-5837-5_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T07:22:37Z","timestamp":1767165757000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-5837-5_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819958368","9789819958375"],"references-count":41,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-5837-5_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"5 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACIIDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Intelligent Information and Database Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Phuket","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Thailand","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 July 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aciids2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aciids.pwr.edu.pl\/2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}