{"id":"https://openalex.org/W2900348157","doi":"https://doi.org/10.18653/v1/w18-6235","title":"BrainT at IEST 2018: Fine-tuning Multiclass Perceptron For Implicit Emotion Classification","display_name":"BrainT at IEST 2018: Fine-tuning Multiclass Perceptron For Implicit Emotion Classification","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2900348157","doi":"https://doi.org/10.18653/v1/w18-6235","mag":"2900348157"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w18-6235","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-6235","pdf_url":"https://www.aclweb.org/anthology/W18-6235.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 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W18-6235.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023258023","display_name":"Vachagan Gratian","orcid":null},"institutions":[{"id":"https://openalex.org/I31582689","display_name":"Stuttgart University of Applied Sciences","ror":"https://ror.org/039gdg280","country_code":"DE","type":"education","lineage":["https://openalex.org/I31582689"]},{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Vachagan Gratian","raw_affiliation_strings":["Universitt Stuttgart","Universit\u00e4t Stuttgart"],"affiliations":[{"raw_affiliation_string":"Universitt Stuttgart","institution_ids":["https://openalex.org/I100066346","https://openalex.org/I31582689"]},{"raw_affiliation_string":"Universit\u00e4t Stuttgart","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044979342","display_name":"Marina Haid","orcid":null},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]},{"id":"https://openalex.org/I31582689","display_name":"Stuttgart University of Applied Sciences","ror":"https://ror.org/039gdg280","country_code":"DE","type":"education","lineage":["https://openalex.org/I31582689"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marina Haid","raw_affiliation_strings":["Universitt Stuttgart","Universit\u00e4t Stuttgart"],"affiliations":[{"raw_affiliation_string":"Universitt Stuttgart","institution_ids":["https://openalex.org/I100066346","https://openalex.org/I31582689"]},{"raw_affiliation_string":"Universit\u00e4t Stuttgart","institution_ids":["https://openalex.org/I100066346"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023258023"],"corresponding_institution_ids":["https://openalex.org/I100066346","https://openalex.org/I31582689"],"apc_list":null,"apc_paid":null,"fwci":0.4887,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73702478,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"243","last_page":"247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9997000098228455,"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":0.9997000098228455,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9972000122070312,"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":0.996399998664856,"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/trigram","display_name":"Trigram","score":0.7611680030822754},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7529404759407043},{"id":"https://openalex.org/keywords/bigram","display_name":"Bigram","score":0.7046440243721008},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6279168725013733},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.619800329208374},{"id":"https://openalex.org/keywords/emoji","display_name":"Emoji","score":0.6114675998687744},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5636922717094421},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4797552824020386},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.45953038334846497},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4145238697528839},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.40591782331466675},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3926770091056824},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.25858211517333984},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.1966857612133026}],"concepts":[{"id":"https://openalex.org/C137546455","wikidata":"https://www.wikidata.org/wiki/Q3213474","display_name":"Trigram","level":2,"score":0.7611680030822754},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7529404759407043},{"id":"https://openalex.org/C108757681","wikidata":"https://www.wikidata.org/wiki/Q2773912","display_name":"Bigram","level":3,"score":0.7046440243721008},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6279168725013733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.619800329208374},{"id":"https://openalex.org/C2779247141","wikidata":"https://www.wikidata.org/wiki/Q1049294","display_name":"Emoji","level":3,"score":0.6114675998687744},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5636922717094421},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4797552824020386},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.45953038334846497},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4145238697528839},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40591782331466675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3926770091056824},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25858211517333984},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.1966857612133026},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w18-6235","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-6235","pdf_url":"https://www.aclweb.org/anthology/W18-6235.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 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w18-6235","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w18-6235","pdf_url":"https://www.aclweb.org/anthology/W18-6235.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 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2900348157.pdf","grobid_xml":"https://content.openalex.org/works/W2900348157.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W220841388","https://openalex.org/W1588401315","https://openalex.org/W1966797434","https://openalex.org/W1971028513","https://openalex.org/W2008652694","https://openalex.org/W2057656120","https://openalex.org/W2133590167","https://openalex.org/W2251345040","https://openalex.org/W2267835966","https://openalex.org/W2891209320","https://openalex.org/W2964351885","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2011383762","https://openalex.org/W4327499987","https://openalex.org/W2048414027","https://openalex.org/W3173084154","https://openalex.org/W2940857995","https://openalex.org/W2895883758","https://openalex.org/W2940684586","https://openalex.org/W2809276897","https://openalex.org/W2031891814","https://openalex.org/W353876725"],"abstract_inverted_index":{"We":[0,14],"present":[1],"BrainT,":[2],"a":[3,100],"multi-class,":[4],"averaged":[5],"perceptron":[6],"tested":[7],"on":[8,75,84],"implicit":[9],"emotion":[10],"prediction":[11,42],"of":[12,56,79,103],"tweets.":[13],"show":[15],"that":[16,33],"the":[17,27,34,38,57,85,91],"dataset":[18],"is":[19,73],"linearly":[20],"separable":[21],"and":[22,41,50,65,82],"explore":[23],"ways":[24],"in":[25],"finetuning":[26],"baseline":[28],"classifier.":[29],"Our":[30],"results":[31],"indicate":[32],"bag-of-words":[35],"features":[36],"benefit":[37],"model":[39,72],"moderately":[40],"can":[43],"be":[44],"improved":[45],"with":[46],"bigrams,":[47],"trigrams,":[48],"skip-onetetragrams":[49],"POS-tags.":[51],"Furthermore,":[52],"we":[53],"find":[54],"preprocessing":[55],"n-grams,":[58],"including":[59],"stemming,":[60],"lowercasing,":[61],"stopword":[62],"filtering,":[63],"emoji":[64],"emoticon":[66],"conversion":[67],"generally":[68],"not":[69],"useful.":[70],"The":[71],"trained":[74],"an":[76],"annotated":[77],"corpus":[78],"153,383":[80],"tweets":[81],"predictions":[83],"test":[86],"data":[87],"were":[88],"submitted":[89],"to":[90],"WASSA-2018":[92],"Implicit":[93],"Emotion":[94],"Shared":[95],"Task.":[96],"BrainT":[97],"1":[98],"attained":[99],"Macro":[101],"F-score":[102],"0.63.":[104]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
