{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T03:30:14Z","timestamp":1769916614341,"version":"3.49.0"},"reference-count":35,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,15]],"date-time":"2021-12-15T00:00:00Z","timestamp":1639526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,15]]},"DOI":"10.1109\/bigdata52589.2021.9672027","type":"proceedings-article","created":{"date-parts":[[2022,1,13]],"date-time":"2022-01-13T20:39:16Z","timestamp":1642106356000},"page":"4570-4577","source":"Crossref","is-referenced-by-count":4,"title":["Contextual Sentence Analysis for the Sentiment Prediction on Financial Data"],"prefix":"10.1109","author":[{"given":"Elvys Linhares","family":"Pontes","sequence":"first","affiliation":[]},{"given":"Mohamed","family":"Benjannet","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.coling-main.85"},{"key":"ref32","article-title":"Google’s neural machine translation system: Bridging the gap between human and machine translation","author":"wu","year":"2016"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3115\/1220575.1220619"},{"key":"ref30","first-page":"6000","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems NIPS’17"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/BigComp.2018.00026"},{"key":"ref34","first-page":"2324","article-title":"BERT post-training for review reading comprehension and aspect-based sentiment analysis","volume":"1","author":"xu","year":"0"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S17-2154"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S15-2080"},{"key":"ref12","first-page":"53","article-title":"The volatility of the stock market and news","author":"goonatilake","year":"2007","journal-title":"International Research Journal of Finance and Economics"},{"key":"ref13","first-page":"187","article-title":"Aspect-based sentiment analysis using BERT","author":"hoang","year":"0"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S17-2152"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S17-2150"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-017-1134-1"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/K17-1031"},{"key":"ref18","article-title":"Roberta: A robustly optimized bert pretraining approach","author":"liu","year":"2019"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3184558.3192301"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2019.00231"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.conll-1.35"},{"key":"ref27","author":"sanh","year":"2020","journal-title":"DistilBERT a distilled version of BERT smaller faster cheaper and lighter"},{"key":"ref3","article-title":"Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining","author":"baccianella","year":"2010","journal-title":"LREC"},{"key":"ref6","article-title":"Ntusd-fin : A market sentiment dictionary for financial social media data applications","author":"chen","year":"2018","journal-title":"Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.02.007"},{"key":"ref5","article-title":"Affective norms for english words (anew): Instruction manual and affective ratings","author":"bradley","year":"1999","journal-title":"Technical report c-1"},{"key":"ref8","article-title":"Social sentiment indices powered by x-scores","author":"davis","year":"2016","journal-title":"2nd International Conference on Big Data Small Data Linked Data and Open Data ALLDATA"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S17-2089"},{"key":"ref2","article-title":"Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining","author":"baccianella","year":"2010","journal-title":"LREC"},{"key":"ref1","article-title":"Finbert: Financial sentiment analysis with pre-trained language models","author":"araci","year":"2019"},{"key":"ref9","first-page":"4171","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"0"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S17-2138"},{"key":"ref22","first-page":"93","article-title":"A new ANEW: evaluation of a word list for sentiment analysis in microblogs","volume":"718","author":"nielsen","year":"2011","journal-title":"Proceedings of the ESWC2011 Workshop on ’Making Sense of Microposts’ Big things come in small packages"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3009626"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S17-2088"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s42521-019-00014-x"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S17-2139"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/S17-2148"}],"event":{"name":"2021 IEEE International Conference on Big Data (Big Data)","location":"Orlando, FL, USA","start":{"date-parts":[[2021,12,15]]},"end":{"date-parts":[[2021,12,18]]}},"container-title":["2021 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9671263\/9671273\/09672027.pdf?arnumber=9672027","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:55:33Z","timestamp":1652201733000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9672027\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,15]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/bigdata52589.2021.9672027","relation":{},"subject":[],"published":{"date-parts":[[2021,12,15]]}}}