{"id":"https://openalex.org/W2115718228","doi":"https://doi.org/10.18653/v1/s15-2092","title":"RoseMerry: A Baseline Message-level Sentiment Classification System","display_name":"RoseMerry: A Baseline Message-level Sentiment Classification System","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2115718228","doi":"https://doi.org/10.18653/v1/s15-2092","mag":"2115718228"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s15-2092","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2092","pdf_url":"https://www.aclweb.org/anthology/S15-2092.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 International Workshop on Semantic Evaluation (SemEval 2015)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S15-2092.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075528828","display_name":"Huizhi Liang","orcid":"https://orcid.org/0000-0003-4408-4528"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Huizhi Liang","raw_affiliation_strings":["The University of Melbourne VIC 3010, Melbourne","University of Melbourne, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne VIC 3010, Melbourne","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"University of Melbourne, Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026981840","display_name":"Richard Fothergill","orcid":null},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Richard Fothergill","raw_affiliation_strings":["The University of Melbourne VIC 3010, Melbourne","University of Melbourne"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne VIC 3010, Melbourne","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103085805","display_name":"Timothy Baldwin","orcid":"https://orcid.org/0000-0002-4445-1386"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Timothy Baldwin","raw_affiliation_strings":["The University of Melbourne VIC 3010, Melbourne","University of Melbourne, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne VIC 3010, Melbourne","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"University of Melbourne, Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075528828"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":1.3353,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.86324397,"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":"551","last_page":"555"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9980999827384949,"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":0.9972000122070312,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.9090477228164673},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8498266935348511},{"id":"https://openalex.org/keywords/treebank","display_name":"Treebank","score":0.8074615001678467},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.8030091524124146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.684487521648407},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.662542998790741},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6306060552597046},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6294140815734863},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5775816440582275},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.519270658493042},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4550645053386688},{"id":"https://openalex.org/keywords/f1-score","display_name":"F1 score","score":0.42682594060897827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3399427533149719},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.05438151955604553}],"concepts":[{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.9090477228164673},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8498266935348511},{"id":"https://openalex.org/C206134035","wikidata":"https://www.wikidata.org/wiki/Q811525","display_name":"Treebank","level":3,"score":0.8074615001678467},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.8030091524124146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.684487521648407},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.662542998790741},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6306060552597046},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6294140815734863},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5775816440582275},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.519270658493042},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4550645053386688},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.42682594060897827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3399427533149719},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.05438151955604553},{"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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/s15-2092","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2092","pdf_url":"https://www.aclweb.org/anthology/S15-2092.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 International Workshop on Semantic Evaluation (SemEval 2015)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.700.6293","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.700.6293","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://alt.qcri.org/semeval2015/cdrom/pdf/SemEval092.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.18653/v1/s15-2092","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2092","pdf_url":"https://www.aclweb.org/anthology/S15-2092.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 International Workshop on Semantic Evaluation (SemEval 2015)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2115718228.pdf","grobid_xml":"https://content.openalex.org/works/W2115718228.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W2097726431","https://openalex.org/W2108646579","https://openalex.org/W2113459411","https://openalex.org/W2129011250","https://openalex.org/W2131744502","https://openalex.org/W2153635508","https://openalex.org/W2250243742","https://openalex.org/W2251939518","https://openalex.org/W2460474657","https://openalex.org/W2949547296","https://openalex.org/W2949709688","https://openalex.org/W3120421331","https://openalex.org/W4385414156"],"related_works":["https://openalex.org/W2117643817","https://openalex.org/W3117973240","https://openalex.org/W2252046358","https://openalex.org/W3115494066","https://openalex.org/W2159316909","https://openalex.org/W3115087542","https://openalex.org/W4287663240","https://openalex.org/W3117847293","https://openalex.org/W3087633719","https://openalex.org/W2955604406"],"abstract_inverted_index":{"In":[0,38],"this":[1],"paper,":[2],"we":[3,43],"propose":[4],"a":[5],"baseline":[6],"messagelevel":[7,35],"sentiment":[8,36],"classification":[9],"method,":[10],"as":[11,58,60],"developed":[12],"for":[13,34],"SemEval-2015":[14,53],"Task":[15,54],"10,":[16,55],"Subtask":[17,56],"B.":[18],"This":[19],"system":[20],"leverages":[21],"both":[22,74],"hand-crafted":[23],"features":[24],"and":[25,29],"message-level":[26],"embedding":[27,41],"features,":[28,42],"uses":[30],"an":[31],"SVM":[32],"classifier":[33],"classification.":[37],"pre-training":[39],"the":[40,61,68],"use":[44],"one":[45],"million":[46],"randomly-selected":[47],"tweets.":[48],"We":[49],"present":[50],"results":[51],"over":[52,73],"B,":[57],"well":[59],"Stanford":[62],"Sentiment":[63],"Treebank.":[64],"Our":[65],"experiments":[66],"show":[67],"effectiveness":[69],"of":[70],"our":[71],"method":[72],"datasets.":[75]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
