{"id":"https://openalex.org/W2425210833","doi":"https://doi.org/10.18653/v1/s16-1010","title":"TwiSE at SemEval-2016 Task 4: Twitter Sentiment Classification","display_name":"TwiSE at SemEval-2016 Task 4: Twitter Sentiment Classification","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2425210833","doi":"https://doi.org/10.18653/v1/s16-1010","mag":"2425210833"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s16-1010","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1010","pdf_url":"https://aclanthology.org/S16-1010.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 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/S16-1010.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069431438","display_name":"Georgios Balikas","orcid":"https://orcid.org/0009-0009-5885-4336"},"institutions":[{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Georgios Balikas","raw_affiliation_strings":["Universit\u00e9 Grenoble Alpes, Saint-Martin-d'H\u00e8res, France"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 Grenoble Alpes, Saint-Martin-d'H\u00e8res, France","institution_ids":["https://openalex.org/I899635006"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044686680","display_name":"Massih-Reza Amini","orcid":"https://orcid.org/0000-0001-9032-4233"},"institutions":[{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Massih-Reza Amini","raw_affiliation_strings":["Universit\u00e9 Grenoble Alpes, Saint-Martin-d'H\u00e8res, France"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 Grenoble Alpes, Saint-Martin-d'H\u00e8res, France","institution_ids":["https://openalex.org/I899635006"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5069431438"],"corresponding_institution_ids":["https://openalex.org/I899635006"],"apc_list":null,"apc_paid":null,"fwci":0.56375376,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.86414638,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"85","last_page":"91"},"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/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9340866208076477},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8467414975166321},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7633838653564453},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6928043961524963},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.672303318977356},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.6127743124961853},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5782039761543274},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5774174332618713},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5169905424118042},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5155153274536133},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4451940953731537},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35523301362991333},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3386841416358948},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.165835440158844},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08718428015708923},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.05894842743873596},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.05237242579460144}],"concepts":[{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.9340866208076477},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8467414975166321},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7633838653564453},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6928043961524963},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.672303318977356},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.6127743124961853},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5782039761543274},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5774174332618713},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5169905424118042},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5155153274536133},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4451940953731537},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35523301362991333},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3386841416358948},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.165835440158844},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08718428015708923},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.05894842743873596},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.05237242579460144},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/s16-1010","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1010","pdf_url":"https://aclanthology.org/S16-1010.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 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1606.04351","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1606.04351","pdf_url":"https://arxiv.org/pdf/1606.04351","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":null},{"id":"mag:2425210833","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1606.04351.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":"doi:10.48550/arxiv.1606.04351","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1606.04351","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/s16-1010","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1010","pdf_url":"https://aclanthology.org/S16-1010.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 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2425210833.pdf","grobid_xml":"https://content.openalex.org/works/W2425210833.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1521626219","https://openalex.org/W1618905105","https://openalex.org/W1984309565","https://openalex.org/W2022204871","https://openalex.org/W2024011160","https://openalex.org/W2070996757","https://openalex.org/W2101234009","https://openalex.org/W2102667697","https://openalex.org/W2108712612","https://openalex.org/W2156413587","https://openalex.org/W2157765050","https://openalex.org/W2157791002","https://openalex.org/W2160660844","https://openalex.org/W2162010436","https://openalex.org/W2190044943","https://openalex.org/W2257942484","https://openalex.org/W2467186984","https://openalex.org/W2752201871","https://openalex.org/W2949709688"],"related_works":["https://openalex.org/W2964267846","https://openalex.org/W2752120242","https://openalex.org/W2753458434","https://openalex.org/W2521196866","https://openalex.org/W2171255559","https://openalex.org/W2751857726","https://openalex.org/W2751927167","https://openalex.org/W2465978385","https://openalex.org/W2805837477","https://openalex.org/W3115343927","https://openalex.org/W2751402495","https://openalex.org/W3044187542","https://openalex.org/W2806801285","https://openalex.org/W2806593956","https://openalex.org/W2963712766","https://openalex.org/W2954283529","https://openalex.org/W2955921953","https://openalex.org/W3047453320","https://openalex.org/W3184069441","https://openalex.org/W2750893234"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"the":[3,6,10,46,62,73,79,82,86,101,105,128,131,134,154],"participation":[4],"of":[5,42,64,66,69,81,85,130],"team":[7],"\"TwiSE\"":[8],"in":[9,17,23],"SemEval":[11],"2016":[12],"challenge.":[13],"Specifically,":[14],"we":[15,27,49,76,92,112,137],"participated":[16],"Task":[18],"4,":[19],"namely":[20],"\"Sentiment":[21],"Analysis":[22],"Twitter\"":[24],"for":[25,32,56,120,127,145,157],"which":[26],"implemented":[28],"sentiment":[29,58],"classification":[30],"systems":[31],"subtasks":[33,146],"A,":[34,147],"B,":[35,148],"C":[36,149],"and":[37,51,123,143,150],"D.":[38],"Our":[39],"approach":[40,117],"consists":[41],"two":[43],"steps.":[44],"In":[45,72,133],"first":[47],"step,":[48,75],"generate":[50],"validate":[52],"diverse":[53],"feature":[54],"sets":[55],"twitter":[57],"evaluation,":[59],"inspired":[60],"by":[61,97,104],"work":[63],"participants":[65],"previous":[67],"editions":[68],"such":[70],"challenges.":[71],"second":[74],"focus":[77],"on":[78,100],"optimization":[80],"evaluation":[83],"measures":[84],"different":[87,94],"subtasks.":[88,132],"To":[89],"this":[90],"end,":[91],"examine":[93],"learning":[95,116],"strategies":[96],"validating":[98],"them":[99],"data":[102],"provided":[103],"task":[106],"organisers.":[107],"For":[108],"our":[109],"final":[110],"submissions":[111],"used":[113],"an":[114],"ensemble":[115],"(stacked":[118],"generalization)":[119],"Subtask":[121],"A":[122],"single":[124],"linear":[125],"models":[126],"rest":[129],"official":[135],"leaderboard":[136],"were":[138],"ranked":[139],"9/35,":[140],"8/19,":[141],"1/11":[142],"2/14":[144],"D":[151],"respectively.\\footnote{We":[152],"make":[153],"code":[155],"available":[156],"research":[158],"purposes":[159],"at":[160],"\\url{https://github.com/balikasg/SemEval2016-Twitter\\_Sentiment\\_Evaluation}.}":[161]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}