{"id":"https://openalex.org/W4283159272","doi":"https://doi.org/10.1186/s40537-022-00614-2","title":"Readers\u2019 affect: predicting and understanding readers\u2019 emotions with deep learning","display_name":"Readers\u2019 affect: predicting and understanding readers\u2019 emotions with deep learning","publication_year":2022,"publication_date":"2022-06-20","ids":{"openalex":"https://openalex.org/W4283159272","doi":"https://doi.org/10.1186/s40537-022-00614-2"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-022-00614-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00614-2","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00614-2","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00614-2","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112026948","display_name":"K. Anoop","orcid":null},"institutions":[{"id":"https://openalex.org/I114176345","display_name":"University of Calicut","ror":"https://ror.org/05yeh3g67","country_code":"IN","type":"education","lineage":["https://openalex.org/I114176345"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anoop K.","raw_affiliation_strings":["Department of Computer Science, University of Calicut, Malappuram, Kerala, India"],"raw_orcid":"https://orcid.org/0000-0002-4335-5544","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Calicut, Malappuram, Kerala, India","institution_ids":["https://openalex.org/I114176345"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113740386","display_name":"P Deepak","orcid":null},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Deepak P.","raw_affiliation_strings":["School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, Northern Ireland, UK"],"raw_orcid":"https://orcid.org/0000-0002-1336-2356","affiliations":[{"raw_affiliation_string":"School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, Northern Ireland, UK","institution_ids":["https://openalex.org/I126231945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002631025","display_name":"Savitha Sam Abraham","orcid":"https://orcid.org/0000-0003-3902-2867"},"institutions":[{"id":"https://openalex.org/I26437253","display_name":"\u00d6rebro University","ror":"https://ror.org/05kytsw45","country_code":"SE","type":"education","lineage":["https://openalex.org/I26437253"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Savitha Sam Abraham","raw_affiliation_strings":["School of Science and Technology, \u00d6rebro University, \u00d6rebro, Sweden"],"raw_orcid":"https://orcid.org/0000-0003-3902-2867","affiliations":[{"raw_affiliation_string":"School of Science and Technology, \u00d6rebro University, \u00d6rebro, Sweden","institution_ids":["https://openalex.org/I26437253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012640897","display_name":"V. L. Lajish","orcid":null},"institutions":[{"id":"https://openalex.org/I114176345","display_name":"University of Calicut","ror":"https://ror.org/05yeh3g67","country_code":"IN","type":"education","lineage":["https://openalex.org/I114176345"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Lajish V. L.","raw_affiliation_strings":["Department of Computer Science, University of Calicut, Malappuram, Kerala, India"],"raw_orcid":"https://orcid.org/0000-0002-8897-3936","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Calicut, Malappuram, Kerala, India","institution_ids":["https://openalex.org/I114176345"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049404086","display_name":"Manjary P. Gangan","orcid":"https://orcid.org/0000-0003-2515-0227"},"institutions":[{"id":"https://openalex.org/I114176345","display_name":"University of Calicut","ror":"https://ror.org/05yeh3g67","country_code":"IN","type":"education","lineage":["https://openalex.org/I114176345"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manjary P. Gangan","raw_affiliation_strings":["Department of Computer Science, University of Calicut, Malappuram, Kerala, India"],"raw_orcid":"https://orcid.org/0000-0003-2515-0227","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Calicut, Malappuram, Kerala, India","institution_ids":["https://openalex.org/I114176345"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113740386"],"corresponding_institution_ids":["https://openalex.org/I126231945"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":1.8339,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.87260464,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"9","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8475658893585205},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7547718286514282},{"id":"https://openalex.org/keywords/emotion-detection","display_name":"Emotion detection","score":0.6805672645568848},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6608197093009949},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5833510160446167},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.578948974609375},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.5782946944236755},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5627866983413696},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.5372507572174072},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5359265208244324},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.5335232615470886},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4729677736759186},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4603360593318939},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.4582177698612213},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.14938119053840637},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.14316916465759277},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.12269207835197449}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8475658893585205},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7547718286514282},{"id":"https://openalex.org/C2988148770","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion detection","level":3,"score":0.6805672645568848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6608197093009949},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5833510160446167},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.578948974609375},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.5782946944236755},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5627866983413696},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.5372507572174072},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5359265208244324},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.5335232615470886},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4729677736759186},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4603360593318939},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4582177698612213},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.14938119053840637},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.14316916465759277},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.12269207835197449},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1186/s40537-022-00614-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00614-2","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00614-2","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:pure.qub.ac.uk/portal:publications/b58067a2-33cb-4caf-9cb0-573e56e3be4e","is_oa":false,"landing_page_url":"https://pure.qub.ac.uk/en/publications/b58067a2-33cb-4caf-9cb0-573e56e3be4e","pdf_url":null,"source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Kadan, A, Padmanabhan, D, Sam Abraham, S, Lajish, V L & P. Gangan, M 2022, 'Readers\u2019 affect: predicting and understanding readers\u2019 emotions with deep learning', Journal of Big Data, vol. 9, no. 82, 82. https://doi.org/10.1186/s40537-022-00614-2","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:eprints.soton.ac.uk:495958","is_oa":false,"landing_page_url":"http://doi.org/10.1186/s40537-022-00614-2>).","pdf_url":null,"source":{"id":"https://openalex.org/S4306401019","display_name":"ePrints Soton (University of Southampton)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I43439940","host_organization_name":"University of Southampton","host_organization_lineage":["https://openalex.org/I43439940"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:openaccess.city.ac.uk:36025","is_oa":false,"landing_page_url":"http://orcid.org/0000-0002-4335-5544>,","pdf_url":null,"source":{"id":"https://openalex.org/S4306401940","display_name":"City Research Online (City University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I180825142","host_organization_name":"City, University of London","host_organization_lineage":["https://openalex.org/I180825142"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:34f4463d6a234d8eb4b074789d5d5712","is_oa":false,"landing_page_url":"https://doaj.org/article/34f4463d6a234d8eb4b074789d5d5712","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 9, Iss 1, Pp 1-31 (2022)","raw_type":"article"},{"id":"pmh:oai:pure.qub.ac.uk/portal:datasets/5a18e243-750b-4480-907c-d42cb59717d2","is_oa":true,"landing_page_url":"https://dcs.uoc.ac.in/cida/resources/renh-4k.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},{"id":"pmh:oai:pure.qub.ac.uk/portal:datasets/6cd5ec1d-09b5-4543-9fc9-69f2d4a45016","is_oa":true,"landing_page_url":"https://dcs.uoc.ac.in/cida/resources/ren-10k.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.1186/s40537-022-00614-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-022-00614-2","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-022-00614-2","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5899999737739563}],"awards":[{"id":"https://openalex.org/G8793448908","display_name":null,"funder_award_id":"SR/WOS-A/PM-62/2018","funder_id":"https://openalex.org/F4320320719","funder_display_name":"Department of Science and Technology, Ministry of Science and Technology, India"}],"funders":[{"id":"https://openalex.org/F4320320719","display_name":"Department of Science and Technology, Ministry of Science and Technology, India","ror":"https://ror.org/0101xrq71"},{"id":"https://openalex.org/F4320322434","display_name":"Max-Planck-Gesellschaft","ror":"https://ror.org/01hhn8329"},{"id":"https://openalex.org/F4320328625","display_name":"University of Calicut","ror":"https://ror.org/05yeh3g67"},{"id":"https://openalex.org/F4320329486","display_name":"Mahatma Gandhi University","ror":"https://ror.org/00h4spn88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4283159272.pdf","grobid_xml":"https://content.openalex.org/works/W4283159272.grobid-xml"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W1964604284","https://openalex.org/W1990936741","https://openalex.org/W1999320905","https://openalex.org/W2045599215","https://openalex.org/W2045631398","https://openalex.org/W2062877045","https://openalex.org/W2079521622","https://openalex.org/W2083633991","https://openalex.org/W2099813784","https://openalex.org/W2104090402","https://openalex.org/W2105468141","https://openalex.org/W2110162085","https://openalex.org/W2131774270","https://openalex.org/W2146241755","https://openalex.org/W2155447859","https://openalex.org/W2165008816","https://openalex.org/W2250879510","https://openalex.org/W2347003557","https://openalex.org/W2519399605","https://openalex.org/W2563741043","https://openalex.org/W2593930476","https://openalex.org/W2737712635","https://openalex.org/W2796104818","https://openalex.org/W2805241691","https://openalex.org/W2805744755","https://openalex.org/W2806015244","https://openalex.org/W2806028205","https://openalex.org/W2806448740","https://openalex.org/W2806731175","https://openalex.org/W2806851714","https://openalex.org/W2807637782","https://openalex.org/W2884287800","https://openalex.org/W2889855823","https://openalex.org/W2891837125","https://openalex.org/W2900744882","https://openalex.org/W2905807898","https://openalex.org/W2914514293","https://openalex.org/W2918378401","https://openalex.org/W2954539723","https://openalex.org/W2954960254","https://openalex.org/W2961723205","https://openalex.org/W2962750587","https://openalex.org/W2963223838","https://openalex.org/W2963712766","https://openalex.org/W2963744503","https://openalex.org/W2968463578","https://openalex.org/W2970014349","https://openalex.org/W2970726176","https://openalex.org/W3005230635","https://openalex.org/W3006443909","https://openalex.org/W3006591657","https://openalex.org/W3010668918","https://openalex.org/W3034444624","https://openalex.org/W3080359515","https://openalex.org/W3203395742","https://openalex.org/W3204166654","https://openalex.org/W3209875211","https://openalex.org/W3211363741","https://openalex.org/W4213009331","https://openalex.org/W4251591997","https://openalex.org/W4391156274","https://openalex.org/W6702650806"],"related_works":["https://openalex.org/W2151226813","https://openalex.org/W4205336895","https://openalex.org/W3156356070","https://openalex.org/W2154970010","https://openalex.org/W4310609400","https://openalex.org/W2165412197","https://openalex.org/W104683736","https://openalex.org/W4360585483","https://openalex.org/W2890114324","https://openalex.org/W4377970469"],"abstract_inverted_index":{"Abstract":[0],"Emotions":[1],"are":[2],"highly":[3],"useful":[4],"to":[5,61,104,161,227],"model":[6,114,153,179,191,213],"human":[7],"behavior":[8,180],"being":[9,145],"at":[10],"the":[11,48,68,73,106,111,116,190],"core":[12],"of":[13,50,76,110,151,164,197,205],"what":[14,42],"makes":[15],"us":[16],"human.":[17],"Today,":[18],"people":[19],"abundantly":[20],"express":[21],"and":[22,72,108,127,148,172,199],"share":[23],"emotions":[24,40,223],"through":[25,89,192],"social":[26],"media.":[27],"Technological":[28],"advancements":[29],"in":[30,47,155],"such":[31],"platforms":[32],"enable":[33],"sharing":[34],"opinions":[35],"or":[36],"expressing":[37],"any":[38],"specific":[39,228],"towards":[41,181],"others":[43],"have":[44],"shared,":[45],"mainly":[46],"form":[49],"textual":[51,77],"data.":[52],"This":[53],"entails":[54],"an":[55],"interesting":[56],"arena":[57],"for":[58,85,115],"analysis;":[59],"as":[60,230,232],"whether":[62],"there":[63],"is":[64,103],"a":[65,95,132,140,194],"disconnect":[66],"between":[67],"writer\u2019s":[69],"intended":[70],"emotion":[71,165,183],"reader\u2019s":[74],"perception":[75],"content.":[78],"In":[79],"this":[80],"paper,":[81],"we":[82,121,177],"present":[83],"experiments":[84,206],"Readers\u2019":[86],"Emotion":[87],"Detection":[88],"multi-target":[90],"regression":[91],"settings":[92],"by":[93,189],"exploring":[94],"Bi-LSTM-based":[96],"Attention":[97,212],"model,":[98],"where":[99],"our":[100,152,209],"major":[101],"intention":[102],"analyze":[105],"interpretability":[107],"effectiveness":[109],"deep":[112,168],"learning":[113],"task.":[117],"To":[118],"conduct":[119],"experiments,":[120],"procure":[122],"two":[123],"extensive":[124],"datasets":[125],"REN-10k":[126],"RENh-4k,":[128],"apart":[129],"from":[130,136],"using":[131],"popular":[133],"benchmark":[134],"dataset":[135],"SemEval-2007.":[137],"We":[138],"perform":[139],"two-phase":[141],"experimental":[142],"evaluation,":[143],"first":[144,203],"various":[146],"coarse-grained":[147],"fine-grained":[149],"evaluations":[150],"performance":[154],"comparison":[156],"with":[157],"several":[158],"baselines":[159],"belonging":[160],"different":[162],"categories":[163],"detection,":[166],"viz.,":[167],"learning,":[169],"lexicon":[170],"based,":[171],"classical":[173],"machine":[174],"learning.":[175],"Secondly,":[176],"evaluate":[178],"readers\u2019":[182],"detection":[184],"assessing":[185],"attention":[186],"maps":[187],"generated":[188],"devising":[193],"novel":[195],"set":[196],"qualitative":[198],"quantitative":[200],"metrics.":[201],"The":[202,218],"phase":[204],"shows":[207],"that":[208,222],"Bi-LSTM":[210],"+":[211],"significantly":[214],"outperforms":[215],"all":[216],"baselines.":[217],"second":[219],"analysis":[220],"reveals":[221],"may":[224],"be":[225],"correlated":[226],"words":[229],"well":[231],"named":[233],"entities.":[234]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2022-06-21T00:00:00"}
