{"id":"https://openalex.org/W2598660323","doi":"https://doi.org/10.1145/3065953.3065955","title":"Discover trends in public emotion using social sensing","display_name":"Discover trends in public emotion using social sensing","publication_year":2017,"publication_date":"2017-03-27","ids":{"openalex":"https://openalex.org/W2598660323","doi":"https://doi.org/10.1145/3065953.3065955","mag":"2598660323"},"language":"en","primary_location":{"id":"doi:10.1145/3065953.3065955","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3065953.3065955","pdf_url":null,"source":{"id":"https://openalex.org/S4210205892","display_name":"ACM SIGWEB Newsletter","issn_l":"1931-1435","issn":["1931-1435","1931-1745"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGWEB Newsletter","raw_type":"journal-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/A5010485563","display_name":"Maryam Hasan","orcid":null},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Maryam Hasan","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008269094","display_name":"Elke A. Rundensteiner","orcid":"https://orcid.org/0000-0001-5375-9254"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elke Rundensteiner","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002930471","display_name":"Xiangnan Kong","orcid":"https://orcid.org/0000-0002-7403-5869"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiangnan Kong","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003809101","display_name":"Emmanuel Agu","orcid":"https://orcid.org/0000-0002-3361-4952"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emmanuel Agu","raw_affiliation_strings":["Worcester Polytechnic Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute","institution_ids":["https://openalex.org/I107077323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010485563"],"corresponding_institution_ids":["https://openalex.org/I107077323"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.02387663,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2017","issue":"Spring","first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9943000078201294,"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":0.9943000078201294,"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":0.9921000003814697,"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"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6974511742591858},{"id":"https://openalex.org/keywords/pace","display_name":"Pace","score":0.6737167835235596},{"id":"https://openalex.org/keywords/feeling","display_name":"Feeling","score":0.6462515592575073},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.621131181716919},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5302013158798218},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.49399858713150024},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.4909820854663849},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.4857228398323059},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.44130945205688477},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.43767186999320984},{"id":"https://openalex.org/keywords/terrorism","display_name":"Terrorism","score":0.4306911826133728},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.4268399477005005},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30179673433303833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.278779000043869},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.27254801988601685},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.25617849826812744},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.2389795482158661},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.11007434129714966}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6974511742591858},{"id":"https://openalex.org/C2777526511","wikidata":"https://www.wikidata.org/wiki/Q691543","display_name":"Pace","level":2,"score":0.6737167835235596},{"id":"https://openalex.org/C122980154","wikidata":"https://www.wikidata.org/wiki/Q205555","display_name":"Feeling","level":2,"score":0.6462515592575073},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.621131181716919},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5302013158798218},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.49399858713150024},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.4909820854663849},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4857228398323059},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.44130945205688477},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.43767186999320984},{"id":"https://openalex.org/C203133693","wikidata":"https://www.wikidata.org/wiki/Q7283","display_name":"Terrorism","level":2,"score":0.4306911826133728},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.4268399477005005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30179673433303833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.278779000043869},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.27254801988601685},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.25617849826812744},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.2389795482158661},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.11007434129714966},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3065953.3065955","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3065953.3065955","pdf_url":null,"source":{"id":"https://openalex.org/S4210205892","display_name":"ACM SIGWEB Newsletter","issn_l":"1931-1435","issn":["1931-1435","1931-1745"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM SIGWEB Newsletter","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2103012681","https://openalex.org/W2191779256","https://openalex.org/W2599253365","https://openalex.org/W4233413206","https://openalex.org/W6687711781"],"related_works":["https://openalex.org/W127192698","https://openalex.org/W2743735673","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W4361801939","https://openalex.org/W2802243998","https://openalex.org/W1521014365","https://openalex.org/W2736127210"],"abstract_inverted_index":{"Social":[0],"networks,":[1],"such":[2,60],"as":[3,61],"Twitter":[4],"and":[5,16,21,50,65,72,102,135,149],"Facebook,":[6],"are":[7],"increasingly":[8],"used":[9],"by":[10],"individuals":[11],"to":[12,56,81,98,129,145],"share":[13],"their":[14],"opinions":[15],"feelings":[17],"on":[18],"current":[19],"issues":[20],"events":[22],"in":[23,31,54,85,88,114],"the":[24,69],"form":[25],"of":[26,34,75,152,156],"text":[27,35,115,157],"messages.":[28,158],"This":[29],"results":[30],"massive":[32],"amounts":[33],"stream":[36,116],"data":[37,43,77],"rich":[38],"with":[39],"emotional":[40],"content.":[41],"Such":[42],"provides":[44],"a":[45,119,147],"great":[46],"opportunity":[47],"for":[48],"identifying":[49],"analyzing":[51,153],"people's":[52],"emotions":[53,84,112],"response":[55],"various":[57],"public":[58,83,100],"events,":[59],"epidemics,":[62],"terrorist":[63],"attacks":[64],"political":[66],"elections.":[67],"However,":[68],"high":[70],"volume":[71],"fast":[73,148],"pace":[74],"social":[76,86],"make":[78],"it":[79],"challenging":[80],"analyze":[82],"networks":[87],"real-time.":[89],"In":[90],"this":[91],"paper":[92],"we":[93,124],"propose":[94],"an":[95],"online":[96,154],"method":[97,142],"measure":[99],"emotion":[101,127,140],"detect":[103,136],"emotion-intensive":[104,137],"moments":[105],"during":[106],"real-life":[107],"events.":[108],"We":[109],"first":[110],"classify":[111],"expressed":[113],"messages":[117],"using":[118],"supervised":[120],"learning":[121],"approach.":[122],"Then":[123],"aggregate":[125],"each":[126],"class":[128],"discover":[130],"emotionevolving":[131],"patterns":[132],"over":[133],"time":[134],"moments.":[138],"Our":[139],"analysis":[141],"is":[143],"shown":[144],"present":[146],"robust":[150],"approach":[151],"streams":[155]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}