{"id":"https://openalex.org/W2797520209","doi":"https://doi.org/10.18653/v1/s18-1002","title":"SeerNet at SemEval-2018 Task 1: Domain Adaptation for Affect in Tweets","display_name":"SeerNet at SemEval-2018 Task 1: Domain Adaptation for Affect in Tweets","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2797520209","doi":"https://doi.org/10.18653/v1/s18-1002","mag":"2797520209"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s18-1002","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1002","pdf_url":"https://www.aclweb.org/anthology/S18-1002.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 12th International Workshop on Semantic Evaluation","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/S18-1002.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070617445","display_name":"Venkatesh Duppada","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Venkatesh Duppada","raw_affiliation_strings":["Seernet Technologies, LLC"],"affiliations":[{"raw_affiliation_string":"Seernet Technologies, LLC","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009910197","display_name":"Royal Jain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Royal Jain","raw_affiliation_strings":["Seernet Technologies, LLC"],"affiliations":[{"raw_affiliation_string":"Seernet Technologies, LLC","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038037490","display_name":"Sushant Hiray","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sushant Hiray","raw_affiliation_strings":["Seernet Technologies, LLC"],"affiliations":[{"raw_affiliation_string":"Seernet Technologies, LLC","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070617445"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.79424984,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75848123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"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":0.9994999766349792,"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":0.9994999766349792,"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":0.9983999729156494,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8971157073974609},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.8648332953453064},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.724602222442627},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6602879166603088},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.5748162269592285},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.5335880517959595},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.46252354979515076},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44210129976272583},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.4181543290615082},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.38107338547706604},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37745440006256104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3751199543476105},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3276124596595764},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.23079073429107666},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.1624782383441925},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15712258219718933},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12372705340385437},{"id":"https://openalex.org/keywords/communication","display_name":"Communication","score":0.092017263174057}],"concepts":[{"id":"https://openalex.org/C2779812673","wikidata":"https://www.wikidata.org/wiki/Q169251","display_name":"Sadness","level":3,"score":0.8971157073974609},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.8648332953453064},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.724602222442627},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6602879166603088},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.5748162269592285},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.5335880517959595},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.46252354979515076},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44210129976272583},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.4181543290615082},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.38107338547706604},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37745440006256104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3751199543476105},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3276124596595764},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.23079073429107666},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.1624782383441925},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15712258219718933},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12372705340385437},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.092017263174057},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/s18-1002","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1002","pdf_url":"https://www.aclweb.org/anthology/S18-1002.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 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1804.06137","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1804.06137","pdf_url":"https://arxiv.org/pdf/1804.06137","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":"mag:2797520209","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1804.06137","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":"doi:10.48550/arxiv.1804.06137","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1804.06137","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/s18-1002","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s18-1002","pdf_url":"https://www.aclweb.org/anthology/S18-1002.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 12th International Workshop on Semantic Evaluation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2797520209.pdf","grobid_xml":"https://content.openalex.org/works/W2797520209.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W652662681","https://openalex.org/W2162010436","https://openalex.org/W2165698076","https://openalex.org/W2395693197","https://openalex.org/W2606347107","https://openalex.org/W2611755161","https://openalex.org/W2747541555","https://openalex.org/W2749639054","https://openalex.org/W2805744755","https://openalex.org/W2949709688","https://openalex.org/W2950726992","https://openalex.org/W2950974174","https://openalex.org/W3106003309"],"related_works":["https://openalex.org/W2963662881","https://openalex.org/W2024403085","https://openalex.org/W2808336242","https://openalex.org/W2099885352","https://openalex.org/W2955429306","https://openalex.org/W2964208374","https://openalex.org/W2747541555","https://openalex.org/W2956016035","https://openalex.org/W2948349826","https://openalex.org/W2955000657","https://openalex.org/W3029690717","https://openalex.org/W2113317774","https://openalex.org/W2899963683","https://openalex.org/W2955246356","https://openalex.org/W2900338016","https://openalex.org/W2401248876","https://openalex.org/W2996007668","https://openalex.org/W3122950306","https://openalex.org/W3008446209","https://openalex.org/W2899723212"],"abstract_inverted_index":{"The":[0,15,65,76,94],"paper":[1],"describes":[2],"the":[3,8,19,69,91,107,112,124],"best":[4],"performing":[5],"system":[6,16,77,96],"for":[7,25,56],"SemEval-2018":[9],"Affect":[10],"in":[11,106],"Tweets":[12],"(English)":[13],"sub-tasks.":[14,109],"focuses":[17],"on":[18],"ordinal":[20,30],"classification":[21,31],"and":[22,27,63,73,85],"regression":[23,66],"sub-tasks":[24,67],"valence":[26,32,72],"emotion.":[28,75],"For":[29],"is":[33,46],"classified":[34,47],"into":[35,48],"7":[36],"different":[37,50,83],"classes":[38,51],"ranging":[39,117],"from":[40,118],"-3":[41],"to":[42,53,89,120],"3":[43,54],"whereas":[44],"emotion":[45,58],"4":[49,82],"0":[52],"separately":[55],"each":[57,74],"namely":[59],"anger,":[60],"fear,":[61],"joy":[62],"sadness.":[64],"estimate":[68],"intensity":[70],"of":[71,81,101],"performs":[78],"domain":[79],"adaptation":[80],"models":[84],"creates":[86],"an":[87],"ensemble":[88],"give":[90],"final":[92],"prediction.":[93],"proposed":[95],"achieved":[97],"1st":[98],"position":[99],"out":[100],"75":[102],"teams":[103],"which":[104],"participated":[105],"fore-mentioned":[108],"We":[110],"outperform":[111],"baseline":[113],"model":[114],"by":[115],"margins":[116],"49.2%":[119],"76.4%,":[121],"thus,":[122],"pushing":[123],"state-of-the-art":[125],"significantly.":[126]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}