{"id":"https://openalex.org/W2740540254","doi":"https://doi.org/10.18653/v1/s17-1007","title":"Emotion Intensities in Tweets","display_name":"Emotion Intensities in Tweets","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2740540254","doi":"https://doi.org/10.18653/v1/s17-1007","mag":"2740540254"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s17-1007","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s17-1007","pdf_url":"https://www.aclweb.org/anthology/S17-1007.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th Joint Conference on Lexical and Computational\n          Semantics (*SEM 2017)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S17-1007.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033684482","display_name":"Saif M. Mohammad","orcid":"https://orcid.org/0000-0003-2716-7516"},"institutions":[{"id":"https://openalex.org/I197604219","display_name":"National Academies of Sciences, Engineering, and Medicine","ror":"https://ror.org/02eq2w707","country_code":"US","type":"government","lineage":["https://openalex.org/I197604219"]},{"id":"https://openalex.org/I4210159778","display_name":"National Research Council Canada","ror":"https://ror.org/04mte1k06","country_code":"CA","type":"government","lineage":["https://openalex.org/I4210159778"]}],"countries":["CA","US"],"is_corresponding":true,"raw_author_name":"Saif Mohammad","raw_affiliation_strings":["Information and Communications Technologies National Research Council Canada Ottawa, Canada","National Academies of Sciences, Engineering, and Medicine, Washington, United States"],"affiliations":[{"raw_affiliation_string":"Information and Communications Technologies National Research Council Canada Ottawa, Canada","institution_ids":["https://openalex.org/I4210159778"]},{"raw_affiliation_string":"National Academies of Sciences, Engineering, and Medicine, Washington, United States","institution_ids":["https://openalex.org/I197604219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047767877","display_name":"Felipe Bravo-M\u00e1rquez","orcid":"https://orcid.org/0000-0002-2153-4306"},"institutions":[{"id":"https://openalex.org/I52179390","display_name":"University of Waikato","ror":"https://ror.org/013fsnh78","country_code":"NZ","type":"education","lineage":["https://openalex.org/I52179390"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Felipe Bravo-Marquez","raw_affiliation_strings":["Department of Computer Science The University of Waikato Hamilton, New Zealand","University of Waikato, Hamilton, New Zealand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science The University of Waikato Hamilton, New Zealand","institution_ids":["https://openalex.org/I52179390"]},{"raw_affiliation_string":"University of Waikato, Hamilton, New Zealand","institution_ids":["https://openalex.org/I52179390"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033684482"],"corresponding_institution_ids":["https://openalex.org/I197604219","https://openalex.org/I4210159778"],"apc_list":null,"apc_paid":null,"fwci":3.3193,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.93799894,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"65","last_page":"77"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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":0.9998000264167786,"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/T12488","display_name":"Mental Health via Writing","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9908999800682068,"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/sadness","display_name":"Sadness","score":0.934749960899353},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.793113112449646},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6872080564498901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6228258609771729},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5928307175636292},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5618473887443542},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5263097286224365},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.5225645899772644},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4940994083881378},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4709160029888153},{"id":"https://openalex.org/keywords/emotion-detection","display_name":"Emotion detection","score":0.4537213444709778},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4335975646972656},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.4278486371040344},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.373147189617157},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.3444966673851013},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.32327890396118164},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.14848050475120544},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11474093794822693},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11246609687805176}],"concepts":[{"id":"https://openalex.org/C2779812673","wikidata":"https://www.wikidata.org/wiki/Q169251","display_name":"Sadness","level":3,"score":0.934749960899353},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.793113112449646},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6872080564498901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6228258609771729},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5928307175636292},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5618473887443542},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5263097286224365},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.5225645899772644},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4940994083881378},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4709160029888153},{"id":"https://openalex.org/C2988148770","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion detection","level":3,"score":0.4537213444709778},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4335975646972656},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.4278486371040344},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.373147189617157},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3444966673851013},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.32327890396118164},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.14848050475120544},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11474093794822693},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11246609687805176},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.18653/v1/s17-1007","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s17-1007","pdf_url":"https://www.aclweb.org/anthology/S17-1007.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th Joint Conference on Lexical and Computational\n          Semantics (*SEM 2017)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1708.03696","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.03696","pdf_url":"https://arxiv.org/pdf/1708.03696","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:cisti-icist.nrc-cnrc.ca:cistinparc:23002133","is_oa":true,"landing_page_url":"https://nrc-publications.canada.ca/fra/voir/objet/?id=ce218860-e351-49fc-8443-f227d219fe59","pdf_url":"https://nrc-publications.canada.ca/eng/view/ft/?id=ce218860-e351-49fc-8443-f227d219fe59","source":{"id":"https://openalex.org/S7407055245","display_name":"NPARC","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":null,"raw_type":"article"},{"id":"mag:2740540254","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1708.03696.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:researchcommons.waikato.ac.nz:10289/11513","is_oa":false,"landing_page_url":"https://hdl.handle.net/10289/11513","pdf_url":null,"source":{"id":"https://openalex.org/S4306400944","display_name":"Research Commons (University of Waikato)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I52179390","host_organization_name":"University of Waikato","host_organization_lineage":["https://openalex.org/I52179390"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"*SEM 2017","raw_type":"Conference Contribution"},{"id":"doi:10.48550/arxiv.1708.03696","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1708.03696","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.18653/v1/s17-1007","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s17-1007","pdf_url":"https://www.aclweb.org/anthology/S17-1007.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th Joint Conference on Lexical and Computational\n          Semantics (*SEM 2017)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2740540254.pdf","grobid_xml":"https://content.openalex.org/works/W2740540254.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W38739846","https://openalex.org/W40549020","https://openalex.org/W1513398909","https://openalex.org/W1569507287","https://openalex.org/W1800296434","https://openalex.org/W1966797434","https://openalex.org/W1987425720","https://openalex.org/W2022204871","https://openalex.org/W2028944185","https://openalex.org/W2033442452","https://openalex.org/W2040467972","https://openalex.org/W2064230935","https://openalex.org/W2098801107","https://openalex.org/W2121060109","https://openalex.org/W2133990480","https://openalex.org/W2134031328","https://openalex.org/W2135869619","https://openalex.org/W2136201510","https://openalex.org/W2156413587","https://openalex.org/W2160660844","https://openalex.org/W2165075134","https://openalex.org/W2168493061","https://openalex.org/W2168872737","https://openalex.org/W2250638193","https://openalex.org/W2252073650","https://openalex.org/W2269051851","https://openalex.org/W2270627573","https://openalex.org/W2294703018","https://openalex.org/W2347127863","https://openalex.org/W2611755161","https://openalex.org/W2741691725","https://openalex.org/W2785676972","https://openalex.org/W2945608433","https://openalex.org/W2949709688","https://openalex.org/W2949965121","https://openalex.org/W2950577311","https://openalex.org/W2950974174","https://openalex.org/W2963223838"],"related_works":["https://openalex.org/W2963177779","https://openalex.org/W1513398909","https://openalex.org/W2747541555","https://openalex.org/W2099885352","https://openalex.org/W2546702061","https://openalex.org/W2805939548","https://openalex.org/W2964208374","https://openalex.org/W3108752444","https://openalex.org/W2802350116","https://openalex.org/W2158179307","https://openalex.org/W2011664673","https://openalex.org/W3212826078","https://openalex.org/W3155683087","https://openalex.org/W2462090045","https://openalex.org/W2618591609","https://openalex.org/W2113317774","https://openalex.org/W3034524416","https://openalex.org/W3211291333","https://openalex.org/W2808336242","https://openalex.org/W2978228414"],"abstract_inverted_index":{"This":[0],"paper":[1],"examines":[2],"the":[3,14,80],"task":[4],"of":[5,8,17,90],"detecting":[6,76],"intensity":[7],"emotion":[9,51,77],"from":[10],"text.":[11],"We":[12,27,44],"create":[13,61],"first":[15],"datasets":[16],"tweets":[18],"annotated":[19],"for":[20,75],"anger,":[21],"fear,":[22],"joy,":[23],"and":[24,39,66],"sadness":[25],"intensities.":[26],"use":[28],"a":[29,55,62],"technique":[30],"called":[31],"best-worst":[32],"scaling":[33],"(BWS)":[34],"that":[35,46],"improves":[36],"annotation":[37],"consistency":[38],"obtains":[40],"reliable":[41],"fine-grained":[42],"scores.":[43],"show":[45],"emotion-word":[47],"hashtags":[48],"often":[49],"impact":[50],"intensity,":[52],"usually":[53],"conveying":[54],"more":[56],"intense":[57],"emotion.":[58],"Finally,":[59],"we":[60],"benchmark":[63],"regression":[64],"system":[65],"conduct":[67],"experiments":[68],"to":[69,82],"determine:":[70],"which":[71,83],"features":[72],"are":[73,86],"useful":[74],"intensity;":[78],"and,":[79],"extent":[81],"two":[84],"emotions":[85],"similar":[87],"in":[88,94],"terms":[89],"how":[91],"they":[92],"manifest":[93],"language.":[95]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}