{"id":"https://openalex.org/W2963603845","doi":"https://doi.org/10.1109/bigdata.2015.7364016","title":"Identifying actionable messages on social media","display_name":"Identifying actionable messages on social media","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2963603845","doi":"https://doi.org/10.1109/bigdata.2015.7364016","mag":"2963603845"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2015.7364016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2015.7364016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Big Data (Big Data)","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/A5015501509","display_name":"Nemanja Spasojevic","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150505","display_name":"Lithium Power (United States)","ror":"https://ror.org/052s8df17","country_code":"US","type":"company","lineage":["https://openalex.org/I4210150505"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nemanja Spasojevic","raw_affiliation_strings":["Lithium Technologies/Klout, San Francisco, CA"],"affiliations":[{"raw_affiliation_string":"Lithium Technologies/Klout, San Francisco, CA","institution_ids":["https://openalex.org/I4210150505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046414714","display_name":"Adithya Rao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150505","display_name":"Lithium Power (United States)","ror":"https://ror.org/052s8df17","country_code":"US","type":"company","lineage":["https://openalex.org/I4210150505"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adithya Rao","raw_affiliation_strings":["Lithium Technologies/Klout, San Francisco, CA"],"affiliations":[{"raw_affiliation_string":"Lithium Technologies/Klout, San Francisco, CA","institution_ids":["https://openalex.org/I4210150505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015501509"],"corresponding_institution_ids":["https://openalex.org/I4210150505"],"apc_list":null,"apc_paid":null,"fwci":2.5886,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.92080885,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"5","issue":null,"first_page":"2273","last_page":"2281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9952999949455261,"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/T10260","display_name":"Software Engineering Research","score":0.9939000010490417,"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/social-media","display_name":"Social media","score":0.7993828058242798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7960624694824219},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.7391670942306519},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5624173283576965},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5087280869483948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5043741464614868},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.45996078848838806},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4576311707496643},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4566958546638489},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.45073240995407104},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4395006597042084},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4240865707397461},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.39639419317245483},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3956599235534668},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3615685999393463},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3133147358894348},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.23744970560073853},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07089650630950928}],"concepts":[{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7993828058242798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7960624694824219},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.7391670942306519},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5624173283576965},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5087280869483948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5043741464614868},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.45996078848838806},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4576311707496643},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4566958546638489},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.45073240995407104},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4395006597042084},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4240865707397461},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39639419317245483},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3956599235534668},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3615685999393463},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3133147358894348},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.23744970560073853},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07089650630950928},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2015.7364016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2015.7364016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7300000190734863,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W17814598","https://openalex.org/W22861983","https://openalex.org/W118913126","https://openalex.org/W193524605","https://openalex.org/W1507711477","https://openalex.org/W1572771420","https://openalex.org/W1743243001","https://openalex.org/W1966771059","https://openalex.org/W2057308560","https://openalex.org/W2068372750","https://openalex.org/W2077587655","https://openalex.org/W2084046180","https://openalex.org/W2085852184","https://openalex.org/W2086277751","https://openalex.org/W2137191349","https://openalex.org/W2145956377","https://openalex.org/W2156413587","https://openalex.org/W2166305731","https://openalex.org/W2251939518","https://openalex.org/W6600736262","https://openalex.org/W6600949241","https://openalex.org/W6604805935","https://openalex.org/W6607799657","https://openalex.org/W6630319548","https://openalex.org/W6634275188","https://openalex.org/W6637805623","https://openalex.org/W6641990611","https://openalex.org/W6681772862","https://openalex.org/W6691459498"],"related_works":["https://openalex.org/W2130553454","https://openalex.org/W3022007134","https://openalex.org/W4317548404","https://openalex.org/W3104108945","https://openalex.org/W2033364610","https://openalex.org/W3163689946","https://openalex.org/W2797776314","https://openalex.org/W2153927146","https://openalex.org/W2091066410","https://openalex.org/W4390190783"],"abstract_inverted_index":{"Text":[0],"actionability":[1,37],"detection":[2],"is":[3],"the":[4],"problem":[5],"of":[6,39,95,99,103],"classifying":[7],"user":[8],"authored":[9],"natural":[10],"language":[11],"text,":[12],"according":[13],"to":[14,59,71],"whether":[15],"it":[16],"can":[17],"be":[18],"acted":[19],"upon":[20],"by":[21],"a":[22,30],"responding":[23],"agent.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28],"propose":[29],"supervised":[31],"learning":[32],"framework":[33],"for":[34,50],"domain-aware,":[35],"large-scale":[36],"classification":[38],"social":[40],"media":[41],"messages.":[42],"We":[43,67],"derive":[44],"lexicons,":[45],"perform":[46],"an":[47,90],"in-depth":[48],"analysis":[49],"over":[51,72,104],"25":[52],"text":[53],"based":[54],"features,":[55],"and":[56,79,85,97],"explore":[57],"strategies":[58],"handle":[60],"domains":[61],"that":[62],"have":[63],"limited":[64],"training":[65],"data.":[66],"apply":[68],"these":[69],"methods":[70],"46":[73],"million":[74],"messages":[75],"spanning":[76],"75":[77],"companies":[78],"35":[80],"languages,":[81],"from":[82],"both":[83],"Facebook":[84],"Twitter.":[86],"The":[87],"models":[88],"achieve":[89],"aggregate":[91],"population-weighted":[92],"F":[93],"measure":[94],"0.78":[96],"accuracy":[98],"0.74,":[100],"with":[101],"values":[102],"0.9":[105],"in":[106],"some":[107],"cases.":[108]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}