{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T04:57:48Z","timestamp":1785819468320,"version":"3.56.0"},"reference-count":63,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100012171","name":"Ontario Research Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012171","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Brain Inf."],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Annually, over three million people in North America suffer concussions. Every age group is susceptible to concussion, but youth involved in sporting activities are particularly vulnerable, with about 6% of all youth suffering a concussion annually. Youth who suffer concussion have also been shown to have higher rates of suicidal ideation, substance and alcohol use, and violent behaviors. A significant body of research over the last decade has led to changes in policies and laws intended to reduce the incidence and burden of concussions. However, it is also clear that youth engaging in high-risk activities like sport often underreport concussion, while others may embellish reports for specific purposes. For such policies and laws to work, they must operate effectively within a facilitative social context so understanding the culture around concussion becomes essential to reducing concussion and its consequences. We present an automated deep neural network approach to analyze tweets with sport-related concussion context to identify the general public\u2019s sentiment towards concerns in sport-related concussion. A single-layer and multi-layer convolutional neural networks, Long Short-Term Memory (LSTM) networks, and Bidirectional LSTM were trained to classify the sentiments of the tweets. Afterwards, we train an ensemble model to aggregate the predictions of our networks to provide a final decision of the tweet\u2019s sentiment. The system achieves an evaluation F1 score of 62.71% based on Precision and Recall. The trained system is then used to analyze the tweets in the FIFA World Cup 2018 to measure audience reaction to events involving concussion. The neural network system provides an understanding of the culture around concussion through sentiment analysis.<\/jats:p>","DOI":"10.1186\/s40708-021-00134-4","type":"journal-article","created":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T17:04:02Z","timestamp":1625159042000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["A deep neural network approach for sentiment analysis of medically related texts: an analysis of tweets related to concussions in sports"],"prefix":"10.1186","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0676-1818","authenticated-orcid":false,"given":"Kayvan","family":"Tirdad","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Dela Cruz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alireza","family":"Sadeghian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Cusimano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,7,1]]},"reference":[{"key":"134_CR1","unstructured":"Peterson AB, Xu L, Daugherty J, Breiding MJ (2014) Surveillance report of traumatic brain injury-related emergency department visits, hospitalizations, and deaths, united states"},{"issue":"1","key":"134_CR2","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1197\/j.aem.2005.07.038","volume":"13","author":"JJ Bazarian","year":"2006","unstructured":"Bazarian JJ, Veazie P, Mookerjee S, Lerner EB (2006) Accuracy of mild traumatic brain injury case ascertainment using ICD-9 codes. Acad Emerg Med 13(1):31\u201338. https:\/\/doi.org\/10.1197\/j.aem.2005.07.038","journal-title":"Acad Emerg Med"},{"key":"134_CR3","unstructured":"National Center for Injury Prevention and Control (U.S.) (2003) Report to congress on mild traumatic brain injury in the united states; steps to prevent a serious public health problem"},{"key":"134_CR4","unstructured":"Centers for Disease Control and Prevention. TBI: Get the Facts | Concussion | Traumatic Brain Injury | CDC Injury Center. https:\/\/www.cdc.gov\/traumaticbraininjury\/get_the_facts.html Accessed 22 May 2018"},{"issue":"3","key":"134_CR5","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1089\/neu.2009.1068","volume":"27","author":"JJ Bazarian","year":"2010","unstructured":"Bazarian JJ, Blyth B, Mookerjee S, He H, McDermott MP (2010) Sex differences in outcome after mild traumatic brain injury. J Neurotrauma 27(3):527\u2013539. https:\/\/doi.org\/10.1089\/neu.2009.1068","journal-title":"J Neurotrauma"},{"issue":"6","key":"134_CR6","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1097\/00042752-200211000-00003","volume":"12","author":"JS Delaney","year":"2002","unstructured":"Delaney JS, Lacroix VJ, Leclerc S, Johnston KM (2002) Concussions among university football and soccer players. Clin J Sports Med 12(6):331\u2013338. https:\/\/doi.org\/10.1097\/00042752-200211000-00003","journal-title":"Clin J Sports Med"},{"issue":"2","key":"134_CR7","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1080\/026990500120827","volume":"14","author":"JL Guerrero","year":"2000","unstructured":"Guerrero JL, Thurman DJ, Sniezek JE (2000) Emergency department visits associated with traumatic brain injury: United states1995\u20131996. Brain Injury 14(2):181\u2013186","journal-title":"Brain Injury"},{"issue":"19","key":"134_CR8","doi-asserted-by":"publisher","first-page":"2549","DOI":"10.1001\/jama.290.19.2549","volume":"290","author":"KM Guskiewicz","year":"2003","unstructured":"Guskiewicz KM, McCrea M, Marshall SW, Cantu RC, Randolph C, Barr W, Onate JA, Kelly JP (2003) Cumulative effects associated with recurrent concussion in collegiate football players: the NCAA concussion study. Jama 290(19):2549\u20132555. https:\/\/doi.org\/10.1001\/jama.290.19.2549","journal-title":"Jama"},{"issue":"5","key":"134_CR9","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1080\/02699050310001617352","volume":"18","author":"GL Iverson","year":"2004","unstructured":"Iverson GL, Gaetz M, Lovell MR, Collins MW (2004) Cumulative effects of concussion in amateur athletes. Brain Injury 18(5):433\u2013443. https:\/\/doi.org\/10.1080\/02699050310001617352","journal-title":"Brain Injury"},{"issue":"3","key":"134_CR10","first-page":"303","volume":"36","author":"SN Macciocchi","year":"2001","unstructured":"Macciocchi SN, Barth JT, Littlefield L, Cantu RC (2001) Multiple concussions and neuropsychological functioning in collegiate football players. J Athl Train 36(3):303\u2013306","journal-title":"J Athl Train"},{"issue":"9","key":"134_CR11","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1097\/01.PHM.0000083666.74494.BA","volume":"82","author":"ED Zemper","year":"2003","unstructured":"Zemper ED (2003) Two-year prospective study of relative risk of a second cerebral concussion. Am J Phys Med Rehabil 82(9):653\u2013659. https:\/\/doi.org\/10.1097\/01.PHM.0000083666.74494.BA","journal-title":"Am J Phys Med Rehabil"},{"issue":"4","key":"134_CR12","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1093\/neurosurgery\/57.4.719","volume":"57","author":"KM Guskiewicz","year":"2005","unstructured":"Guskiewicz KM, Marshall SW, Bailes J, McCrea M, Cantu RC, Randolph C, Jordan BD (2005) Association between recurrent concussion and late-life cognitive impairment in retired professional football players. Neurosurgery 57(4):719\u2013726719726. https:\/\/doi.org\/10.1093\/neurosurgery\/57.4.719","journal-title":"Neurosurgery"},{"issue":"6","key":"134_CR13","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1249\/mss.0b013e3180383da5","volume":"39","author":"KM Guskiewicz","year":"2007","unstructured":"Guskiewicz KM, Marshall SW, Bailes J, McCrea M, Harding HP, Matthews A, Mihalik JR, Cantu RC (2007) Recurrent concussion and risk of depression in retired professional football players. Med Sci Sports Exerc 39(6):903\u2013909. https:\/\/doi.org\/10.1249\/mss.0b013e3180383da5","journal-title":"Med Sci Sports Exerc"},{"issue":"7","key":"134_CR14","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1097\/NEN.0b013e3181a9d503","volume":"68","author":"AC McKee","year":"2009","unstructured":"McKee AC, Cantu RC, Nowinski CJ, Hedley-Whyte ET, Gavett BE, Budson AE, Santini VE, Lee H-S, Kubilus CA, Stern RA (2009) Chronic traumatic encephalopathy in athletes: progressive tauopathy after repetitive head injury. J Neuropathol Exp Neurol 68(7):709\u2013735. https:\/\/doi.org\/10.1097\/NEN.0b013e3181a9d503","journal-title":"J Neuropathol Exp Neurol"},{"key":"134_CR15","doi-asserted-by":"crossref","unstructured":"McCrory P, Meeuwisse W, Johnston K, Dvorak J, Aubry M, Molloy M, Cantu R (2008) Consensus statement on concussion in sport. In: The 3rd international conference on concussion in sport held in zurich, november 2008, vol 44(4), pp 434\u2013448. Accessed 12 Nov 2020","DOI":"10.4085\/1062-6050-44.4.434"},{"key":"134_CR16","unstructured":"Kepner T (2012) Line Drive Strikes Tigers Starter, and Prompts Concerns. N Y Times"},{"key":"134_CR17","doi-asserted-by":"publisher","unstructured":"McCrory P, Meeuwisse W, Dvo\u0159\u00e1k J, Aubry M, Bailes J, Broglio S, Cantu RC, Cassidy D, Echemendia RJ, Castellani RJ, Davis GA, Ellenbogen R, Emery C, Engebretsen L, Feddermann-Dem ont N, Giza CC, Guskiewicz KM, Herring S, Iverson GL, Johnston KM, Kissick J, Kutcher J, Leddy JJ, Maddocks D, Makdissi M, Manley GT, McCrea M, Meehan WP, Nagahiro S, Patricios J, Putukian M, Schneider KJ, Sills A, Tator CH, Turner M, Vos PE (2016) Consensus statement on concussion in sport-the 5th international conference on concussion in sport held in berlin, october 2016, vol 51(11), pp 838\u2013847. https:\/\/doi.org\/10.1136\/bjsports-2017-097699","DOI":"10.1136\/bjsports-2017-097699"},{"issue":"4","key":"134_CR18","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1097\/JSM.0000000000000372","volume":"27","author":"MD Cusimano","year":"2017","unstructured":"Cusimano MD, Topolovec-Vranic J, Zhang S, Mullen SJ, Wong M, Ilie G (2017) Factors influencing the underreporting of concussion in sports: a qualitative study of minor hockey participants. Clin J Sports Med 27(4):375\u2013380. https:\/\/doi.org\/10.1097\/JSM.0000000000000372","journal-title":"Clin J Sports Med"},{"issue":"5","key":"134_CR19","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1097\/JSM.0b013e318291d3b3","volume":"23","author":"WP Meehan","year":"2013","unstructured":"Meehan WP, Mannix RC, O'Brien MJ, Collins MW (2013) The prevalence of undiagnosed concussions in athletes. Can J Sport Med 23(5):339\u2013342. https:\/\/doi.org\/10.1097\/JSM.0b013e318291d3b3","journal-title":"Can J Sport Med"},{"issue":"5","key":"134_CR20","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1016\/j.jsams.2014.07.008","volume":"18","author":"TB Meier","year":"2015","unstructured":"Meier TB, Brummel BJ, Singh R, Nerio CJ, Polanski DW, Bellgowan PSF (2015) The underreporting of self-reported symptoms following sports-related concussion. J Sci Sport Med 18(5):507\u2013511. https:\/\/doi.org\/10.1016\/j.jsams.2014.07.008","journal-title":"J Sci Sport Med"},{"key":"134_CR21","unstructured":"Centers for Disease Control and Prevention (2020) The Lystedt law: a concussion Survivor\u2019s journey. https:\/\/www.cdc.gov\/headsup\/pdfs\/stories\/031210-zack-story.pdf. Accessed 01 Nov 2020"},{"key":"134_CR22","unstructured":"Government of Ontario (2020) Rowans Law day | Ontario.ca. https:\/\/www.ontario.ca\/page\/rowans-law-day Accessed 01 Nov 2020"},{"issue":"2","key":"134_CR23","doi-asserted-by":"publisher","first-page":"165","DOI":"10.17269\/s41997-019-00174-8","volume":"110","author":"MD McCradden","year":"2019","unstructured":"McCradden MD, Cusimano MD (2019) Staying true to rowan's law: how changing sport culture can realize the goal of the legislation. Can J Public Health 110(2):165\u2013168. https:\/\/doi.org\/10.17269\/s41997-019-00174-8","journal-title":"Can J Public Health"},{"issue":"3","key":"134_CR24","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1177\/0899764001303006","volume":"30","author":"JM Kennedy","year":"2001","unstructured":"Kennedy JM, Vargus B (2001) Challenges in survey research and their implications for philanthropic studies research. Nonprofit Volunt Sect Q 30(3):483\u2013494. https:\/\/doi.org\/10.1177\/0899764001303006","journal-title":"Nonprofit Volunt Sect Q"},{"key":"134_CR25","unstructured":"Pew Research Center (2015) Collecting survey data. http:\/\/www.pewresearch.org\/methodology\/u-s-survey-research\/collecting-survey-data\/ Accessed 22 May 2018"},{"key":"134_CR26","unstructured":"Statista: Twitter MAU worldwide 2018 | Statistic. https:\/\/www.statista.com\/statistics\/282087\/number-of-monthly-active-twitter-users\/ Accessed 22 May 2018"},{"key":"134_CR27","doi-asserted-by":"publisher","unstructured":"Golder S, O'Connor K, Hennessy S, Gross R, Gonzalez-Hernandez G (2020) Assessment of beliefs and attitudes about statins posted on twitter. JAMA Netw Open. https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.8953","DOI":"10.1001\/jamanetworkopen.2020.8953"},{"issue":"8","key":"134_CR28","doi-asserted-by":"publisher","first-page":"14077","DOI":"10.2196\/14077","volume":"21","author":"A Garcia-Rudolph","year":"2019","unstructured":"Garcia-Rudolph A, Laxe S, Saur\u00ed J, Guitart MB (2019) Sentiment and topic analysis from a gender perspective. J Med Internet Res 21(8):14077. https:\/\/doi.org\/10.2196\/14077","journal-title":"J Med Internet Res"},{"issue":"1","key":"134_CR29","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1177\/0193723514558928","volume":"39","author":"K Hull","year":"2015","unstructured":"Hull K, Schmittel A (2015) A fumbled opportunity? a case study of twitter's role in concussion awareness opportunities during the super bowl. J Sport Soc Issue 39(1):78\u201394. https:\/\/doi.org\/10.1177\/0193723514558928","journal-title":"J Sport Soc Issue"},{"key":"134_CR30","doi-asserted-by":"publisher","first-page":"205031211772005","DOI":"10.1177\/2050312117720057","volume":"5","author":"AM Workewych","year":"2017","unstructured":"Workewych AM, Ciuffetelli Muzzi M, Jing R, Zhang S, Topolovec-Vranic J, Cusimano MD (2017) Twitter and traumatic brain injury: a content and sentiment analysis of tweets pertaining to sport-related brain injury. SAGE Open Med 5:2050312117720057. https:\/\/doi.org\/10.1177\/2050312117720057","journal-title":"SAGE Open Med"},{"issue":"1","key":"134_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12559-020-09773-x","volume":"13","author":"M Mahmud","year":"2021","unstructured":"Mahmud M, Kaiser MS, McGinnity TM, Hussain A (2021) Deep learning in mining biological data. Cogn Comput 13(1):1\u201333. https:\/\/doi.org\/10.1007\/s12559-020-09773-x (Accessed 2021-05-03)","journal-title":"Cogn Comput"},{"issue":"1","key":"134_CR32","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/s40708-015-0010-6","volume":"2","author":"ZF Siddiqui","year":"2015","unstructured":"Siddiqui ZF, Krempl G, Spiliopoulou M, Pe\u00f1a JM, Paul N, Maestu F (2015) Predicting the post-treatment recovery of patients suffering from traumatic brain injury (TBI). Brain Inf 2(1):33\u201344. https:\/\/doi.org\/10.1007\/s40708-015-0010-6","journal-title":"Brain Inf"},{"issue":"1","key":"134_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s40708-015-0026-y","volume":"3","author":"K-P Wong","year":"2016","unstructured":"Wong K-P, Bergsneider M, Glenn TC, Kepe V, Barrio JR, Hovda DA, Vespa PM, Huang S-C (2016) A semi-automated workflow solution for multimodal neuroimaging: application to patients with traumatic brain injury. Brain Inf 3(1):1\u201315. https:\/\/doi.org\/10.1007\/s40708-015-0026-y","journal-title":"Brain Inf"},{"issue":"1","key":"134_CR34","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1097\/00042752-200401000-00003","volume":"14","author":"M McCrea","year":"2004","unstructured":"McCrea M, Hammeke T, Olsen G, Leo P, Guskiewicz K (2004) Unreported concussion in high school football players: implications for prevention. Clin J Sport Med 14(1):13\u201317","journal-title":"Clin J Sport Med"},{"issue":"24","key":"134_CR35","doi-asserted-by":"publisher","first-page":"2548","DOI":"10.1001\/jama.2017.6204","volume":"317","author":"MD Cusimano","year":"2017","unstructured":"Cusimano MD, Casey J, Jing R, Mishra A, Solarski M, Techar K, Zhang S (2017) Assessment of head collision events during the 2014 FIFA world cup tournament. Jama 317(24):2548\u20132549. https:\/\/doi.org\/10.1001\/jama.2017.6204","journal-title":"Jama"},{"key":"134_CR36","doi-asserted-by":"publisher","unstructured":"Poornima A, Priya KS (2020) A comparative sentiment analysis of sentence embedding using machine learning techniques. In: 2020 6th international conference on advanced computing and communication systems (ICACCS), pp 493\u2013496. https:\/\/doi.org\/10.1109\/ICACCS48705.2020.9074312","DOI":"10.1109\/ICACCS48705.2020.9074312"},{"issue":"2","key":"134_CR37","doi-asserted-by":"publisher","first-page":"361","DOI":"10.14569\/IJACSA.2019.0100248","volume":"10","author":"A Alsaeedi","year":"2019","unstructured":"Alsaeedi A, Zubair M (2019) A study on sentiment analysis techniques of Twitter data. Int J Adv Comput Sci Appl 10(2):361\u2013374. https:\/\/doi.org\/10.14569\/IJACSA.2019.0100248","journal-title":"Int J Adv Comput Sci Appl"},{"key":"134_CR38","series-title":"Computer communications and networks","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1007\/978-3-030-33624-0_8","volume-title":"Software engineering in the era of cloud computing","author":"A L\u00f3pez-Chau","year":"2020","unstructured":"L\u00f3pez-Chau A, Valle-Cruz D, Sandoval-Almaz\u00e1n R (2020) Sentiment analysis of Twitter data through machine learning techniques. In: Ramachandran M, Mahmood Z (eds) Software engineering in the era of cloud computing. Computer communications and networks. Springer, Cham, pp 185\u2013209. https:\/\/doi.org\/10.1007\/978-3-030-33624-0_8"},{"key":"134_CR39","doi-asserted-by":"publisher","unstructured":"Tiwari S, Verma A, Garg P, Bansal D (2020) Social media sentiment analysis on Twitter datasets. In: 2020 6th international conference on advanced computing and communication systems (ICACCS), pp 925\u2013927. https:\/\/doi.org\/10.1109\/ICACCS48705.2020.9074208","DOI":"10.1109\/ICACCS48705.2020.9074208"},{"key":"134_CR40","doi-asserted-by":"crossref","unstructured":"Deriu J, Gonzenbach M, Uzdilli F, Lucchi A, De\u00a0Luca V, Jaggi M (2016) SwissCheese at SemEval-2016 task 4: Sentiment classification using an ensemble of convolutional neural networks with distant supervision. In: Proceedings of the 10th international workshop on semantic evaluation (SemEval-2016), pp 1124\u20131128. Association for Computational Linguistics. http:\/\/www.aclweb.org\/anthology\/S16-1173 Accessed 05 June 2018","DOI":"10.18653\/v1\/S16-1173"},{"key":"134_CR41","doi-asserted-by":"publisher","unstructured":"Cliche M (2017) BB\\_twtr at SemEval-2017 task 4: Twitter sentiment analysis with CNNs and LSTMs. In: Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017), pp 573\u2013580. Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/S17-2094. https:\/\/www.aclweb.org\/anthology\/S17-2094 Accessed 06 Nov 2020","DOI":"10.18653\/v1\/S17-2094"},{"key":"134_CR42","doi-asserted-by":"crossref","unstructured":"Baziotis C, Pelekis N, Doulkeridis C (2017) DataStories at SemEval-2017 task 4: Deep LSTM with attention for message-level and topic-based sentiment analysis. In: Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017), pp 747\u2013754. Association for Computational Linguistics. http:\/\/www.aclweb.org\/anthology\/S17-2126 Accessed 04 June 2018","DOI":"10.18653\/v1\/S17-2126"},{"issue":"2","key":"134_CR43","doi-asserted-by":"publisher","first-page":"218","DOI":"10.3390\/iot1020014","volume":"1","author":"R Patel","year":"2020","unstructured":"Patel R, Passi K (2020) Sentiment analysis on Twitter data of world cup soccer tournament using machine learning. IoT 1(2):218\u2013239. https:\/\/doi.org\/10.3390\/iot1020014","journal-title":"IoT"},{"key":"134_CR44","unstructured":"Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient estimation of word representations in vector space. In: Bengio Y, LeCun Y eds. 1st international conference on learning representations, ICLR 2013, Scottsdale, Arizona, USA, May 2\u20134, 2013, workshop track proceedings. arXiv:1301.3781"},{"key":"134_CR45","doi-asserted-by":"crossref","unstructured":"Joulin A, Grave E, Bojanowski P, Mikolov T (2017) Bag of tricks for efficient text classification. In: Proceedings of the 15th conference of the European chapter of the association for computational linguistics, vol 2, Short Papers, pp 427\u2013431. Association for Computational Linguistics. https:\/\/www.aclweb.org\/anthology\/E17-2068 Accessed 06 Nov 2020","DOI":"10.18653\/v1\/E17-2068"},{"key":"134_CR46","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1162\/tacl_a_00051","volume":"5","author":"P Bojanowski","year":"2017","unstructured":"Bojanowski P, Grave E, Joulin A, Mikolov T (2017) Enriching word vectors with subword information. Trans Assoc Comput Linguist 5:135\u2013146. https:\/\/doi.org\/10.1162\/tacl_a_00051","journal-title":"Trans Assoc Comput Linguist"},{"key":"134_CR47","doi-asserted-by":"publisher","unstructured":"Pennington J, Socher R, Manning C (2014) GloVe: Global vectors for word representation. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), pp 1532\u20131543. Association for Computational Linguistics. https:\/\/doi.org\/10.3115\/v1\/D14-1162. https:\/\/www.aclweb.org\/anthology\/D14-1162 Accessed 06 Nov 2020","DOI":"10.3115\/v1\/D14-1162"},{"issue":"4","key":"134_CR48","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1136\/bjsm.2010.080341","volume":"46","author":"SJ Sullivan","year":"2012","unstructured":"Sullivan SJ, Schneiders AG, Cheang C-W, Kitto E, Lee H, Redhead J, Ward S, Ahmed OH, McCrory PR (2012) 'what's happening?' A content analysis of concussion-related traffic on twitter. Br J Sports Med 46(4):258\u2013263. https:\/\/doi.org\/10.1136\/bjsm.2010.080341","journal-title":"Br J Sports Med"},{"key":"134_CR49","unstructured":"International C.: Lemmatization. In: Cambridge international dictionary of English. Cambridge University Press. https:\/\/dictionary.cambridge.org\/dictionary\/english\/lemmatization. Accessed 01 Dec 2020"},{"key":"134_CR50","unstructured":"Agarwal A, Xie B, Vovsha I, Rambow O, Passonneau R (2011) Sentiment analysis of twitter data. In: Proceedings of the workshop on language in social media (LSM 2011), pp 30\u201338. Association for Computational Linguistics. http:\/\/www.aclweb.org\/anthology\/W11-0705. Accessed 24 Jul 2018"},{"key":"134_CR51","doi-asserted-by":"publisher","unstructured":"Finkel JR, Grenager T, Manning C (2005) Incorporating non-local information into information extraction systems by gibbs sampling. In: Proceedings of the 43rd annual meeting on Association for Computational Linguistics. ACL \u201905, pp 363\u2013370. Association for Computational Linguistics. https:\/\/doi.org\/10.3115\/1219840.1219885.","DOI":"10.3115\/1219840.1219885"},{"key":"134_CR52","first-page":"37","volume":"1990","author":"B Santorini","year":"1990","unstructured":"Santorini B (1990) Part-of-speech tagging guidelines for the Penn Treebank Project (3rd Revision). Tech Rep CIS 1990:37","journal-title":"Tech Rep CIS"},{"key":"134_CR53","unstructured":"Heidenreich H (2018): Introduction to word embeddings. http:\/\/hunterheidenreich.com\/blog\/intro-to-word-embeddings\/ Accessed 01 Dec 2020"},{"key":"134_CR54","unstructured":"Baccianella S, Esuli A, Sebastiani F (2010) SentiWordNet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining. In: Proceedings of LREC"},{"key":"134_CR55","doi-asserted-by":"publisher","unstructured":"Li S, Wang Z, Lee SYM, Huang CR (2013) Sentiment classification with polarity shifting detection. In: 2013 International conference on Asian language processing, pp 129\u2013132. https:\/\/doi.org\/10.1109\/IALP.2013.44","DOI":"10.1109\/IALP.2013.44"},{"key":"134_CR56","unstructured":"Nielsen MA (2015) Neural networks and deep learning. Determination Press. http:\/\/neuralnetworksanddeeplearning.com Accessed 17 Jul 2018"},{"key":"134_CR57","unstructured":"Dunne RA, Campbell NA (1997) On the pairing of the softmax activation and cross-entropy penalty functions and the derivation of the softmax activation function, vol 181, p 185. Citeseer"},{"key":"134_CR58","unstructured":"Brothrer B, Khanchebemehr E (2018) How RNNs and LSTM work? https:\/\/elham-khanche.github.io\/blog\/RNNs_and_LSTM\/ Accessed 05 Aug 2018"},{"key":"134_CR59","doi-asserted-by":"publisher","unstructured":"Cho K, van Merri\u00ebnboer B, Gulcehre C, Bahdanau D, Bougares F, Schwenk H, Bengio Y (2014) Learning phrase representations using RNN encoder-decoder for statistical machine translation. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), pp 1724\u20131734. Association for Computational Linguistics. https:\/\/doi.org\/10.3115\/v1\/D14-1179. https:\/\/www.aclweb.org\/anthology\/D14-1179 Accessed 06 Nov 2020","DOI":"10.3115\/v1\/D14-1179"},{"key":"134_CR60","unstructured":"Chung J, Gulcehre C, Cho K, Bengio Y (2014) Empirical evaluation of gated recurrent neural networks on sequence modeling. Accessed 06 Nov 2020"},{"key":"134_CR61","unstructured":"Bai S, Kolter JZ, Koltun V (2018) An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv:1803.01271. Accessed 06 Nov 2020"},{"key":"134_CR62","doi-asserted-by":"publisher","unstructured":"Nakov P, Ritter A, Rosenthal S, Sebastiani F, Stoyanov V (2016) Semeval-2016 task 4 Sentiment analysis in twitter. In: Proceedings of the 10th international workshop on semantic evaluation (SemEval-2016), pp 1\u201318. Association for Computational Linguistics. https:\/\/doi.org\/10.18653\/v1\/S16-1001. https:\/\/www.aclweb.org\/anthology\/S16-1001 Accessed 06 Nov 2020","DOI":"10.18653\/v1\/S16-1001"},{"key":"134_CR63","doi-asserted-by":"publisher","unstructured":"Liu R, Shi Y, Ji C, Jia M (2019) A survey of sentiment analysis based on transfer learning vol 7, pp 85401\u201385412. https:\/\/doi.org\/10.1109\/ACCESS.2019.2925059. Conference Name: IEEE Access","DOI":"10.1109\/ACCESS.2019.2925059"}],"container-title":["Brain Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40708-021-00134-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40708-021-00134-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40708-021-00134-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T17:07:09Z","timestamp":1625159229000},"score":1,"resource":{"primary":{"URL":"https:\/\/braininformatics.springeropen.com\/articles\/10.1186\/s40708-021-00134-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,1]]},"references-count":63,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["134"],"URL":"https:\/\/doi.org\/10.1186\/s40708-021-00134-4","relation":{},"ISSN":["2198-4018","2198-4026"],"issn-type":[{"value":"2198-4018","type":"print"},{"value":"2198-4026","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,1]]},"assertion":[{"value":"22 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 June 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 July 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors provide consent for publication of this article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"12"}}