{"id":"https://openalex.org/W2137544940","doi":"https://doi.org/10.1145/2396761.2398481","title":"If you are happy and you know it... tweet","display_name":"If you are happy and you know it... tweet","publication_year":2012,"publication_date":"2012-10-29","ids":{"openalex":"https://openalex.org/W2137544940","doi":"https://doi.org/10.1145/2396761.2398481","mag":"2137544940"},"language":"en","primary_location":{"id":"doi:10.1145/2396761.2398481","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2396761.2398481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Information and knowledge management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103814256","display_name":"Amir Asiaee T.","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Amir Asiaee T.","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA",", University of Minnesota, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":", University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005986086","display_name":"Mariano Tepper","orcid":"https://orcid.org/0000-0001-6053-925X"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mariano Tepper","raw_affiliation_strings":["Duke University, Durham, NC, USA"],"affiliations":[{"raw_affiliation_string":"Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014459472","display_name":"Arindam Banerjee","orcid":"https://orcid.org/0000-0002-7856-5699"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arindam Banerjee","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA",", University of Minnesota, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":", University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025218580","display_name":"Guillermo Sapiro","orcid":"https://orcid.org/0000-0001-9190-6964"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guillermo Sapiro","raw_affiliation_strings":["Duke University, Durham, NC, USA"],"affiliations":[{"raw_affiliation_string":"Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103814256"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":8.1345,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.97514607,"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":"1602","last_page":"1606"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9988999962806702,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9988999962806702,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9986000061035156,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.8812318444252014},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7806391716003418},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.6487571597099304},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.6367566585540771},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4892992675304413},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4225923717021942},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3803868889808655},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.352963924407959},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.35218656063079834},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.34521394968032837},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15600693225860596},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08270680904388428}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8812318444252014},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7806391716003418},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.6487571597099304},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.6367566585540771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4892992675304413},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4225923717021942},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3803868889808655},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.352963924407959},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35218656063079834},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.34521394968032837},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15600693225860596},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08270680904388428},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2396761.2398481","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2396761.2398481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Information and knowledge management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W40549020","https://openalex.org/W359818833","https://openalex.org/W1489608533","https://openalex.org/W1663973292","https://openalex.org/W1743243001","https://openalex.org/W1968120338","https://openalex.org/W1976709621","https://openalex.org/W1983989471","https://openalex.org/W1992405901","https://openalex.org/W2008803468","https://openalex.org/W2070996757","https://openalex.org/W2097089247","https://openalex.org/W2097726431","https://openalex.org/W2099366530","https://openalex.org/W2113125055","https://openalex.org/W2115119296","https://openalex.org/W2124156373","https://openalex.org/W2171468534","https://openalex.org/W2949965121","https://openalex.org/W2951238624","https://openalex.org/W3203591315","https://openalex.org/W4205184193","https://openalex.org/W6629510986","https://openalex.org/W6637805623","https://openalex.org/W6764172607"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2548633793","https://openalex.org/W2941935829","https://openalex.org/W3089396779","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W3013279174","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W4286571989"],"abstract_inverted_index":{"Extracting":[0],"sentiment":[1,22,48,158],"from":[2,71],"Twitter":[3],"data":[4],"is":[5],"one":[6],"of":[7,23,46,81,84,98,120],"the":[8,20,79,95,125],"fundamental":[9],"problems":[10],"in":[11,103],"social":[12],"media":[13],"analytics.":[14],"Twitter's":[15],"length":[16],"constraint":[17],"renders":[18],"determining":[19],"positive/negative":[21],"a":[24,29,37,57,82,104,145,152],"tweet":[25,157],"difficult,":[26],"even":[27],"for":[28,40,155],"human":[30],"judge.":[31],"In":[32,114],"this":[33],"work":[34],"we":[35,77,116,135],"present":[36,117],"general":[38],"framework":[39],"per-tweet":[41,141],"(in":[42],"contrast":[43],"with":[44,64],"batches":[45],"tweets)":[47],"analysis":[49],"which":[50,129],"consists":[51],"of:":[52],"(1)":[53],"extracting":[54],"tweets":[55,63,99],"about":[56],"desired":[58],"target":[59],"subject,":[60],"(2)":[61],"separating":[62],"sentiment,":[65],"and":[66,86],"(3)":[67],"setting":[68],"apart":[69],"positive":[70],"negative":[72],"tweets.":[73],"For":[74],"each":[75],"step,":[76],"study":[78],"performance":[80],"number":[83],"classical":[85],"new":[87],"machine":[88],"learning":[89],"algorithms.":[90],"We":[91],"also":[92],"show":[93,136],"that":[94,137],"intrinsic":[96],"sparsity":[97],"allows":[100],"performing":[101],"classification":[102,132,142],"low":[105],"dimensional":[106],"space,":[107],"via":[108],"random":[109],"projections,":[110],"without":[111],"losing":[112],"accuracy.":[113,133],"addition,":[115],"weighted":[118],"variants":[119],"all":[121],"employed":[122],"algorithms,":[123],"exploiting":[124],"available":[126],"labeling":[127],"uncertainty,":[128],"further":[130],"improve":[131],"Finally,":[134],"spatially":[138],"aggregating":[139],"our":[140,150],"results":[143],"produces":[144],"very":[146],"satisfactory":[147],"outcome,":[148],"making":[149],"approach":[151],"good":[153],"candidate":[154],"batch":[156],"analysis.":[159]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}