{"id":"https://openalex.org/W2045344096","doi":"https://doi.org/10.1145/1940761.1940903","title":"Comparing values and sentiment using Mechanical Turk","display_name":"Comparing values and sentiment using Mechanical Turk","publication_year":2011,"publication_date":"2011-02-08","ids":{"openalex":"https://openalex.org/W2045344096","doi":"https://doi.org/10.1145/1940761.1940903","mag":"2045344096"},"language":"en","primary_location":{"id":"doi:10.1145/1940761.1940903","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1940761.1940903","pdf_url":null,"source":{"id":"https://openalex.org/S4306523619","display_name":"Proceedings of the 2011 iConference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2011 iConference","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/A5060893781","display_name":"Thomas Clay Templeton","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Thomas Clay Templeton","raw_affiliation_strings":["University of Maryland, College Park, MD"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070270738","display_name":"Kenneth R. Fleischmann","orcid":"https://orcid.org/0000-0002-0323-3526"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kenneth R. Fleischmann","raw_affiliation_strings":["University of Maryland, College Park, MD"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081307846","display_name":"Jordan Boyd\u2010Graber","orcid":"https://orcid.org/0000-0002-7770-4431"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jordan Boyd-Graber","raw_affiliation_strings":["University of Maryland, College Park, MD"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5060893781"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":3.4206,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.92688951,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"783","last_page":"784"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9961000084877014,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/paragraph","display_name":"Paragraph","score":0.9291749596595764},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6931675672531128},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6346224546432495},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5831952095031738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5393085479736328},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5168431401252747},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49060192704200745},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24169960618019104},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.12252172827720642}],"concepts":[{"id":"https://openalex.org/C2777206241","wikidata":"https://www.wikidata.org/wiki/Q194431","display_name":"Paragraph","level":2,"score":0.9291749596595764},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6931675672531128},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6346224546432495},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5831952095031738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5393085479736328},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5168431401252747},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49060192704200745},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24169960618019104},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.12252172827720642}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1940761.1940903","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1940761.1940903","pdf_url":null,"source":{"id":"https://openalex.org/S4306523619","display_name":"Proceedings of the 2011 iConference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2011 iConference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3289138679","display_name":null,"funder_award_id":"IIS-0729459IIS-0734894","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W600888349","https://openalex.org/W2007320125","https://openalex.org/W2056775433","https://openalex.org/W2097726431","https://openalex.org/W2500489334","https://openalex.org/W4205184193"],"related_works":["https://openalex.org/W2377059580","https://openalex.org/W4200355488","https://openalex.org/W127000293","https://openalex.org/W3215892509","https://openalex.org/W2928616779","https://openalex.org/W2412592434","https://openalex.org/W2010523086","https://openalex.org/W4244602709","https://openalex.org/W594987446","https://openalex.org/W2012131063"],"abstract_inverted_index":{"Human":[0],"values":[1,17],"can":[2],"help":[3],"to":[4,59,64,70],"explain":[5],"people's":[6,16],"sentiment":[7],"toward":[8],"current":[9],"events.":[10],"In":[11],"this":[12],"experiment,":[13],"we":[14],"compare":[15],"with":[18,23,74],"their":[19],"agreement":[20,45],"or":[21,31,72],"disagreement":[22],"paragraphs":[24,75],"that":[25,38],"were":[26],"classified":[27],"as":[28],"either":[29],"supporting":[30,50],"opposing":[32,52],"a":[33,78],"specific":[34,79],"topic.":[35],"We":[36,57],"found":[37],"five":[39],"value":[40,80],"types":[41],"have":[42],"statistically":[43],"significant":[44],"(p<0.001)":[46],"for":[47],"both":[48],"the":[49],"and":[51],"paragraphs,":[53],"in":[54],"opposite":[55],"directions.":[56],"hope":[58],"use":[60],"these":[61],"paragraph":[62],"ratings":[63],"train":[65],"an":[66],"automatic":[67],"text":[68],"classifier":[69],"agree":[71],"disagree":[73],"based":[76],"on":[77],"profile.":[81]},"counts_by_year":[{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}