{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T08:38:11Z","timestamp":1765960691210,"version":"3.48.0"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soc. Netw. Anal. Min."],"DOI":"10.1007\/s13278-025-01489-w","type":"journal-article","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T07:50:10Z","timestamp":1753343410000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Fuzzy HCN-Net: fuzzy based hierarchical convolutional neural network for sentiment analysis using text reviews"],"prefix":"10.1007","volume":"15","author":[{"given":"Rashmi","family":"Thakur","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harshali","family":"Patil","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anil","family":"Vasoya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Omprakash","family":"Yadav","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manoj","family":"Chavan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Parshvi","family":"Shah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"issue":"1","key":"1489_CR1","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1080\/0144929X.2022.2156387","volume":"43","author":"A Alslaity","year":"2024","unstructured":"Alslaity A, Orji R (2024) Machine learning techniques for emotion detection and sentiment analysis: current state, challenges, and future directions. Behav Inform Technol 43(1):139\u2013164","journal-title":"Behav Inform Technol"},{"key":"1489_CR2","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1016\/j.future.2020.08.005","volume":"115","author":"ME Basiri","year":"2021","unstructured":"Basiri ME, Nemati S, Abdar M, Cambria E, Acharya UR (2021) ABCDM: An attention-based bidirectional CNN-RNN deep model for sentiment analysis. Futur Gener Comput Syst 115:279\u2013294","journal-title":"Futur Gener Comput Syst"},{"issue":"4","key":"1489_CR3","doi-asserted-by":"publisher","first-page":"1780","DOI":"10.1016\/j.jfranklin.2017.06.007","volume":"355","author":"I Chaturvedi","year":"2018","unstructured":"Chaturvedi I, Ragusa E, Gastaldo P, Zunino R, Cambria E (2018) Bayesian network based extreme learning machine for subjectivity detection. J Franklin Inst 355(4):1780\u20131797","journal-title":"J Franklin Inst"},{"issue":"4","key":"1489_CR4","doi-asserted-by":"publisher","first-page":"285","DOI":"10.21512\/comtech.v7i4.3746","volume":"7","author":"H Christian","year":"2016","unstructured":"Christian H, Agus MP, Suharton D (2016) Single document automatic text summarization using term frequency-inverse document frequency (TF-IDF). ComTech: Comput Math Eng Appl 7(4):285\u2013294","journal-title":"ComTech: Comput Math Eng Appl"},{"issue":"1","key":"1489_CR5","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1017\/S1351324916000334","volume":"23","author":"KW Church","year":"2017","unstructured":"Church KW (2017) Word2Vec. Nat Lang Eng 23(1):155\u2013162","journal-title":"Nat Lang Eng"},{"key":"1489_CR6","unstructured":"Devlin J, Chang MW, Lee K, Toutanova K (2018) Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805"},{"key":"1489_CR7","doi-asserted-by":"publisher","first-page":"27983","DOI":"10.1109\/ACCESS.2019.2900335","volume":"7","author":"J Du","year":"2019","unstructured":"Du J, Gui L, He Y, Xu R, Wang X (2019) Convolution-based neural attention with applications to sentiment classification. IEEE Access 7:27983\u201327992","journal-title":"IEEE Access"},{"issue":"2\u20133","key":"1489_CR8","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1016\/0165-0114(94)90022-1","volume":"65","author":"H Ishibuchi","year":"1994","unstructured":"Ishibuchi H, Nozaki K, Yamamoto N, Tanaka H (1994) Construction of fuzzy classification systems with rectangular fuzzy rules using genetic algorithms. Fuzzy Sets Syst 65(2\u20133):237\u2013253","journal-title":"Fuzzy Sets Syst"},{"key":"1489_CR9","doi-asserted-by":"crossref","unstructured":"Jiang Z, Gao B, He Y, Han Y, Doyle P, Zhu Q (2021) Text classification using novel term weighting scheme-based improved tf-idf for internet media reports. Math Prob Eng 1\u201330","DOI":"10.1155\/2021\/6619088"},{"issue":"1","key":"1489_CR10","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1186\/s40537-022-00680-6","volume":"10","author":"G Kaur","year":"2023","unstructured":"Kaur G, Sharma A (2023) A deep learning-based model using hybrid feature extraction approach for consumer sentiment analysis. J Big Data 10(1):5","journal-title":"J Big Data"},{"key":"1489_CR11","unstructured":"Kharde V, Sonawane P (2016) Sentiment analysis of Twitter data: a survey of techniques. arXiv preprint arXiv:1601.06971"},{"issue":"1","key":"1489_CR12","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1007\/s13278-023-01043-6","volume":"13","author":"R Kora","year":"2023","unstructured":"Kora R, Mohammed A (2023) An enhanced approach for sentiment analysis based on meta-ensemble deep learning. Soc Netw Anal Min 13(1):38","journal-title":"Soc Netw Anal Min"},{"issue":"4","key":"1489_CR13","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.1336","volume":"9","author":"LR Krosuri","year":"2023","unstructured":"Krosuri LR, Aravapalli RS (2023) Feature level fine grained sentiment analysis using boosted long short-term memory with improvised local search whale optimization. PeerJ Comput Sci 9(4):e1336","journal-title":"PeerJ Comput Sci"},{"key":"1489_CR14","doi-asserted-by":"publisher","first-page":"13637","DOI":"10.1007\/s11042-023-16133-y","volume":"83","author":"LR Krosuri","year":"2024","unstructured":"Krosuri LR, Aravapalli RS (2024) Novel heuristic bidirectional-recurrent neural network framework for multiclass sentiment analysis classification using coot optimization. Multimed Tools Appl 83:13637\u201313657","journal-title":"Multimed Tools Appl"},{"key":"1489_CR15","doi-asserted-by":"crossref","unstructured":"Krosuri LR, Satish AR (2023) Novel Heuristic-Based Hybrid ResNeXt with Recurrent Neural Network to handle Multi class classification of sentiment Analysis. Mach Learn: Sci Technol 4(1)","DOI":"10.1088\/2632-2153\/acc0d5"},{"key":"1489_CR16","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.neucom.2021.09.057","volume":"467","author":"W Li","year":"2022","unstructured":"Li W, Shao W, Ji S, Cambria E (2022) BiERU: bidirectional emotional recurrent unit for conversational sentiment analysis. Neurocomputing 467:73\u201382","journal-title":"Neurocomputing"},{"key":"1489_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107643","volume":"235","author":"B Liang","year":"2022","unstructured":"Liang B, Su H, Gui L, Cambria E, Xu R (2022) Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks. Knowl-Based Syst 235:107643","journal-title":"Knowl-Based Syst"},{"key":"1489_CR18","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1007\/s12652-018-1095-6","volume":"11","author":"B Liu","year":"2020","unstructured":"Liu B (2020) Text sentiment analysis based on CBOW model and deep learning in big data environment. J Ambient Intell Humaniz Comput 11:451\u2013458","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"1489_CR19","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.inffus.2020.06.011","volume":"64","author":"Y Ma","year":"2020","unstructured":"Ma Y, Nguyen KL, Xing FZ, Cambria E (2020) A survey on empathetic dialogue systems. Inform Fusion 64:50\u201370","journal-title":"Inform Fusion"},{"issue":"3","key":"1489_CR20","doi-asserted-by":"publisher","first-page":"1445","DOI":"10.3390\/app13031445","volume":"13","author":"J Mutinda","year":"2023","unstructured":"Mutinda J, Mwangi W, Okeyo G (2023) Sentiment analysis of text reviews using lexicon-enhanced Bert embedding (LeBERT) model with convolutional neural network. Appl Sci 13(3):1445","journal-title":"Appl Sci"},{"key":"1489_CR21","doi-asserted-by":"publisher","first-page":"14270","DOI":"10.1109\/ACCESS.2022.3147869","volume":"10","author":"HT Nguyen","year":"2022","unstructured":"Nguyen HT, Li S, Cheah CC (2022) A layer-wise theoretical framework for deep learning of convolutional neural networks. IEEE Access 10:14270\u201314287","journal-title":"IEEE Access"},{"key":"1489_CR22","doi-asserted-by":"crossref","unstructured":"Nguyen TH, Shirai K (2015) Phrasernn: phrase recursive neural network for aspect-based sentiment analysis. In\u00a0Proceedings of the 2015 conference on empirical methods in natural language processing 2509\u20132514","DOI":"10.18653\/v1\/D15-1298"},{"key":"1489_CR23","doi-asserted-by":"crossref","unstructured":"Onan A (2021) Ensemble of classifiers and term weighting schemes for sentiment analysis in Turkish.\u00a0Sci Res Commun 1(1)","DOI":"10.52460\/src.2021.004"},{"key":"1489_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.117581","volume":"203","author":"A Pimpalkar","year":"2022","unstructured":"Pimpalkar A, Jeberson Retna Raj R (2022) MBiLSTMGloVe: embedding GloVe knowledge into the corpus using multi-layer BiLSTM deep learning model for social media sentiment analysis. Expert Syst Appl 203:117581","journal-title":"Expert Syst Appl"},{"issue":"4","key":"1489_CR25","doi-asserted-by":"publisher","first-page":"254","DOI":"10.46604\/aiti.2023.11743","volume":"8","author":"A Pimpalkar","year":"2023","unstructured":"Pimpalkar A, Raj JR (2023a) A Novel Paradigm for Sentiment Analysis ON COVID-19 tweets with transfer learning based fine-tuned BERT. Adv Technol Innov 8(4):254\u2013266","journal-title":"Adv Technol Innov"},{"issue":"3","key":"1489_CR26","doi-asserted-by":"publisher","first-page":"251","DOI":"10.46604\/ijeti.2023.11510","volume":"13","author":"A Pimpalkar","year":"2023","unstructured":"Pimpalkar A, Raj JR (2023b) A bi-directional GRU architecture for the self-attention mechanism: an adaptable, multi-layered approach with blend of word embedding. Int J Eng Technol Innov 13(3):251\u2013264","journal-title":"Int J Eng Technol Innov"},{"key":"1489_CR27","doi-asserted-by":"crossref","unstructured":"Pontiki M, Galanis D, Papageorgiou H, Manandhar S, Androutsopoulos I (2015) Semeval-2015 task 12: Aspect based sentiment analysis. In:\u00a0Proceedings of the 9th international workshop on semantic evaluation (SemEval 2015) 486\u2013495","DOI":"10.18653\/v1\/S15-2082"},{"issue":"2","key":"1489_CR28","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0294968","volume":"19","author":"NA Semary","year":"2024","unstructured":"Semary NA, Ahmed W, Amin K, P\u0142awiak P, Hammad M (2024) Enhancing machine learning-based sentiment analysis through feature extraction techniques. PLoS ONE 19(2):e0294968","journal-title":"PLoS ONE"},{"key":"1489_CR29","doi-asserted-by":"crossref","unstructured":"Sinha K, Dong Y, Cheung JCK, Ruths D (2018) A hierarchical neural attention-based text classifier. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing 817\u2013823","DOI":"10.18653\/v1\/D18-1094"},{"key":"1489_CR30","doi-asserted-by":"crossref","unstructured":"Sudheesh R, Mujahid M, Rustam F, Mallampati B, Chunduri V, de la Torre D\u00edez I, Ashraf\u200b I (2023a) Bidirectional encoder representations from transformers and deep learning model for analyzing smartphone-related tweets. PeerJ Comput Sci 9(5):1432","DOI":"10.7717\/peerj-cs.1432"},{"key":"1489_CR31","doi-asserted-by":"crossref","unstructured":"Sudheesh R, Mujahid M, Rustam F, Shafique R, Chunduri V, Villar MG, Ballester JB, de la Torre Diez I, Ashraf I (2023b) Analyzing sentiments regarding ChatGPT using novel BERT: a machine learning approach. Information 14(9)","DOI":"10.3390\/info14090474"},{"key":"1489_CR32","doi-asserted-by":"publisher","first-page":"103694","DOI":"10.1109\/ACCESS.2022.3210182","volume":"10","author":"KL Tan","year":"2022","unstructured":"Tan KL, Lee CP, Lim KM, Anbananthen KSM (2022) Sentiment analysis with ensemble hybrid deep learning model. IEEE Access 10:103694\u2013103704","journal-title":"IEEE Access"},{"key":"1489_CR33","doi-asserted-by":"crossref","unstructured":"Thakur RK, Deshpande MV (2018a) Kernel Optimized-Support Vector Machine and MapReduce framework for sentiment classification of train reviews. Sadhana 44(6)","DOI":"10.1007\/s12046-018-0980-1"},{"issue":"06","key":"1489_CR34","doi-asserted-by":"publisher","first-page":"1850054","DOI":"10.1142\/S179396231850054X","volume":"09","author":"RK Thakur","year":"2018","unstructured":"Thakur RK, Deshpande MV (2018b) OKO-SVM: online kernel optimization-based support vector machine for the incremental learning and classification of the sentiments in the train reviews. Int J Model Simul Sci Comput 09(06):1850054","journal-title":"Int J Model Simul Sci Comput"},{"key":"1489_CR35","unstructured":"The Amazon dataset will be taken from \u201chttps:\/\/nijianmo.github.io\/amazon\/index.html\u201d, accessed on February 2024"},{"key":"1489_CR36","unstructured":"The IMDB Dataset of 50K Movie Reviews will be taken from \u201chttps:\/\/www.kaggle.com\/datasets\/lakshmi25npathi\/imdb-dataset-of-50k-movie-reviews\u201d, accessed on February 2024"},{"key":"1489_CR37","unstructured":"The Sentiment Analysis Dataset will be taken from \u201c https:\/\/www.kaggle.com\/datasets\/abhi8923shriv\/sentiment-analysis-dataset\u201d, accessed on February 2024"},{"key":"1489_CR38","doi-asserted-by":"crossref","unstructured":"Wang J, Yu LC, Lai KR, Zhang X (2016) Dimensional sentiment analysis using a regional CNN-LSTM model. In\u00a0Proceedings of the 54th annual meeting of the association for computational linguistics (volume 2: Short papers) 225\u2013230","DOI":"10.18653\/v1\/P16-2037"},{"key":"1489_CR39","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1007\/s12559-014-9298-4","volume":"7","author":"Y Xia","year":"2015","unstructured":"Xia Y, Cambria E, Hussain A, Zhao H (2015) Word polarity disambiguation using Bayesian model and opinion-level features. Cogn Comput 7:369\u2013380","journal-title":"Cogn Comput"},{"key":"1489_CR40","doi-asserted-by":"publisher","first-page":"344","DOI":"10.1016\/j.neucom.2020.08.001","volume":"419","author":"H Yang","year":"2021","unstructured":"Yang H, Zeng B, Yang J, Song Y, Xu R (2021) A multi-task learning model for Chinese-oriented aspect polarity classification and aspect term extraction. Neurocomputing 419:344\u2013356","journal-title":"Neurocomputing"},{"key":"1489_CR41","first-page":"3085","volume":"83","author":"M Zulqarnain","year":"2024","unstructured":"Zulqarnain M, Ghazali R, Aamir M, Hassim YMM (2024) An efficient two-state GRU based on feature attention mechanism for sentiment analysis. Appl Adv Artif Intell Multimed Inform Sec 83:3085\u20133110","journal-title":"Appl Adv Artif Intell Multimed Inform Sec"}],"container-title":["Social Network Analysis and Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-025-01489-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13278-025-01489-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-025-01489-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T08:27:38Z","timestamp":1765960058000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13278-025-01489-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,24]]},"references-count":41,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1489"],"URL":"https:\/\/doi.org\/10.1007\/s13278-025-01489-w","relation":{},"ISSN":["1869-5469"],"issn-type":[{"type":"electronic","value":"1869-5469"}],"subject":[],"published":{"date-parts":[[2025,7,24]]},"assertion":[{"value":"26 June 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 June 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 July 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"75"}}