{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T03:30:44Z","timestamp":1771558244298,"version":"3.50.1"},"reference-count":14,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,5,4]],"date-time":"2018-05-04T00:00:00Z","timestamp":1525392000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>With the extensive growth of user interactions through prominent advances of the Web, sentiment analysis has obtained more focus from an academic and a commercial point of view. Recently, sentiment analysis in the Bangla language is progressively being considered as an important task, for which previous approaches have attempted to detect the overall polarity of a Bangla document. To the best of our knowledge, there is no research on the aspect-based sentiment analysis (ABSA) of Bangla text. This can be described as being due to the lack of available datasets for ABSA. In this paper, we provide two publicly available datasets to perform the ABSA task in Bangla. One of the datasets consists of human-annotated user comments on cricket, and the other dataset consists of customer reviews of restaurants. We also describe a baseline approach for the subtask of aspect category extraction to evaluate our datasets.<\/jats:p>","DOI":"10.3390\/data3020015","type":"journal-article","created":{"date-parts":[[2018,5,4]],"date-time":"2018-05-04T03:08:21Z","timestamp":1525403301000},"page":"15","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":73,"title":["Datasets for Aspect-Based Sentiment Analysis in Bangla and Its Baseline Evaluation"],"prefix":"10.3390","volume":"3","author":[{"given":"Md. Atikur","family":"Rahman","sequence":"first","affiliation":[{"name":"Institute of Information Technology, University of Dhaka, Dhaka 1000, Bangladesh"}]},{"given":"Emon","family":"Kumar Dey","sequence":"additional","affiliation":[{"name":"Institute of Information Technology, University of Dhaka, Dhaka 1000, Bangladesh"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1509\/jmkg.73.5.90","article-title":"Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site","volume":"73","author":"Trusov","year":"2009","journal-title":"J. Mark."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Jeyapriya, A., and Selvi, C.K. (2015, January 26\u201327). Extracting Aspects and Mining Opinions in Product Reviews Using Supervised Learning Algorithm. Proceedings of the 2015 2nd International Conference on Electronics and Communication Systems (ICECS), Coimbatore, India.","DOI":"10.1109\/ECS.2015.7124967"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Pontiki, M., Galanis, D., Pavlopoulos, J., Papageorgiou, H., Androutsopoulos, I., and Manandhar, S. (2018, May 03). SemEval-2014 Task 4: Aspect Based Sentiment Analysis. Available online: http:\/\/www.aclweb.org\/anthology\/S14-2004.","DOI":"10.3115\/v1\/S14-2004"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Al-Smadi, M., Qawasmeh, O., Talafha, B., and Quwaider, M. (2015, January 24\u201326). Human Annotated Arabic Dataset of Book Reviews for Aspect Based Sentiment Analysis. Proceedings of the 2015 3rd International Conference on Future Internet of Things and Cloud (FiCloud), Rome, Italy.","DOI":"10.1109\/FiCloud.2015.62"},{"key":"ref_5","unstructured":"Tamchyna, A., Fiala, O., and Veselovsk\u00e1, K. (2018, May 03). Czech Aspect-Based Sentiment Analysis: A New Dataset and Preliminary Results. Available online: https:\/\/pdfs.semanticscholar.org\/cbd8\/7f4201c427db33783b1890bca65f5bf99d2c.pdf."},{"key":"ref_6","unstructured":"Apidianaki, M., Tannier, X., and Richart, C. (2018, May 03). Datasets for Aspect-Based Sentiment Analysis in French. Available online: http:\/\/www.lrec-conf.org\/proceedings\/lrec2016\/pdf\/61_Paper.pdf."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Gayatree, G., Elhadad, N., and Marian, A. (2018, May 03). Beyond the Stars: Improving Rating Predictions Using Review Text Content. Available online: http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.150.140&rep=rep1&type=pdf.","DOI":"10.3390\/info10010001"},{"key":"ref_8","unstructured":"Kiritchenko, S., Zhu, X., Cherry, C., and Mohammad, S. (2018, May 03). NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews. Available online: http:\/\/www.aclweb.org\/anthology\/S14-2076."},{"key":"ref_9","unstructured":"Kiritchenko, S., Zhu, X., Cherry, C., and Mohammad, S. (2017). Supervised and Unsupervised Aspect Category Detection for Sentiment Analysis with Co-cccurrence Data. IEEE Transactions on Cybernetics, IEEE."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.knosys.2016.06.009","article-title":"Aspect extraction for opinion mining with a deep convolutional neural network","volume":"108","author":"Soujanya","year":"2016","journal-title":"Knowl.-Based Syst."},{"key":"ref_11","unstructured":"Pengfei, L., Joty, S., and Meng, H. (2018, May 03). Fine-Grained Opinion Mining with Recurrent Neural Networks and Word Embeddings. Available online: http:\/\/www.aclweb.org\/anthology\/D15-1168."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Pontiki, M., Galanis, D., Papageorgiou, H., Manandhar, S., and Androutsopoulos, I. (2018, May 03). Semeval-2015 Task 12: Aspect Based Sentiment Analysis. Available online: http:\/\/www.aclweb.org\/anthology\/S15-2082.","DOI":"10.18653\/v1\/S15-2082"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Pontiki, M., Galanis, D., Papageorgiou, H., Androutsopoulos, I., Manandhar, S., AL-Smadi, M., Al-Ayyoub, M., Zhao, Y., Qin, B., and De Clercq, O. (2018, May 03). SemEval-2016 Task 5: Aspect Based Sentiment Analysis. Available online: http:\/\/www.aclweb.org\/anthology\/S16-1002.","DOI":"10.18653\/v1\/S16-1002"},{"key":"ref_14","unstructured":"Pak, A., and Paroubek, P. (2018, May 03). Twitter as A Corpus for Sentiment Analysis and Opinion Mining. Available online: http:\/\/crowdsourcing-class.org\/assignments\/downloads\/pak-paroubek.pdf."}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/3\/2\/15\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:03:13Z","timestamp":1760194993000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/3\/2\/15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,4]]},"references-count":14,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2018,6]]}},"alternative-id":["data3020015"],"URL":"https:\/\/doi.org\/10.3390\/data3020015","relation":{},"ISSN":["2306-5729"],"issn-type":[{"value":"2306-5729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,5,4]]}}}