{"id":"https://openalex.org/W2460201800","doi":"https://doi.org/10.1145/2914586.2914638","title":"Issue-Focused Documentaries versus Other Films","display_name":"Issue-Focused Documentaries versus Other Films","publication_year":2016,"publication_date":"2016-07-08","ids":{"openalex":"https://openalex.org/W2460201800","doi":"https://doi.org/10.1145/2914586.2914638","mag":"2460201800"},"language":"en","primary_location":{"id":"doi:10.1145/2914586.2914638","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2914586.2914638","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM Conference on Hypertext and Social Media","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/A5050468340","display_name":"Ming Jiang","orcid":"https://orcid.org/0000-0002-3604-166X"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ming Jiang","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025085845","display_name":"Jana Diesner","orcid":"https://orcid.org/0000-0001-8183-7109"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jana Diesner","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5050468340"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.445,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.78375769,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"225","last_page":"230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9983999729156494,"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":0.9983999729156494,"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":0.9857000112533569,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.984000027179718,"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/feature-film","display_name":"Feature film","score":0.6941028237342834},{"id":"https://openalex.org/keywords/noun","display_name":"Noun","score":0.6503351926803589},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5796897411346436},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5404641628265381},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5242741107940674},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4736546277999878},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.4715029299259186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4550103545188904},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.41281306743621826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35941797494888306},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3462420701980591},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1916004717350006},{"id":"https://openalex.org/keywords/movie-theater","display_name":"Movie theater","score":0.16814449429512024},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.1454603374004364}],"concepts":[{"id":"https://openalex.org/C2992486779","wikidata":"https://www.wikidata.org/wiki/Q24869","display_name":"Feature film","level":3,"score":0.6941028237342834},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.6503351926803589},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5796897411346436},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5404641628265381},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5242741107940674},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4736546277999878},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.4715029299259186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4550103545188904},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.41281306743621826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35941797494888306},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3462420701980591},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1916004717350006},{"id":"https://openalex.org/C519580073","wikidata":"https://www.wikidata.org/wiki/Q41253","display_name":"Movie theater","level":2,"score":0.16814449429512024},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.1454603374004364},{"id":"https://openalex.org/C52119013","wikidata":"https://www.wikidata.org/wiki/Q50637","display_name":"Art history","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2914586.2914638","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2914586.2914638","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM Conference on Hypertext and Social Media","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W56793145","https://openalex.org/W104703790","https://openalex.org/W268801030","https://openalex.org/W1503159956","https://openalex.org/W1506229096","https://openalex.org/W1514621009","https://openalex.org/W1545467275","https://openalex.org/W1601807985","https://openalex.org/W1995875735","https://openalex.org/W2022204871","https://openalex.org/W2061873838","https://openalex.org/W2083467787","https://openalex.org/W2084046180","https://openalex.org/W2084127140","https://openalex.org/W2087294982","https://openalex.org/W2106477703","https://openalex.org/W2107787911","https://openalex.org/W2116401198","https://openalex.org/W2117138901","https://openalex.org/W2128279859","https://openalex.org/W2133280805","https://openalex.org/W2139979941","https://openalex.org/W2145955806","https://openalex.org/W2154416898","https://openalex.org/W2155328222","https://openalex.org/W2159662257","https://openalex.org/W2160660844","https://openalex.org/W2161686723","https://openalex.org/W2163455955","https://openalex.org/W2166706824","https://openalex.org/W2168455289","https://openalex.org/W2217066517","https://openalex.org/W2273771970","https://openalex.org/W2474404547","https://openalex.org/W2737168042","https://openalex.org/W2892737606","https://openalex.org/W2930957955","https://openalex.org/W2990634740","https://openalex.org/W2993383518","https://openalex.org/W3146306708","https://openalex.org/W4206070857","https://openalex.org/W4233384665","https://openalex.org/W4285719527","https://openalex.org/W7057999814"],"related_works":["https://openalex.org/W3089396779","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W4286571989","https://openalex.org/W2765903680"],"abstract_inverted_index":{"User-authored":[0],"reviews":[1,41,55,64,68,142],"offer":[2],"a":[3,14,60,187],"window":[4],"into":[5],"micro-level":[6],"engagement":[7],"with":[8,45,72,81,186],"issue-focused":[9],"documentary":[10,54],"films,":[11,115,145],"which":[12],"is":[13,84],"critical":[15],"yet":[16],"insufficiently":[17],"understood":[18],"topic":[19],"in":[20,111,139],"media":[21],"impact":[22,221],"assessment.":[23],"Based":[24],"on":[25,147,174,177,228],"our":[26,79,104,217],"data,":[27],"features,":[28],"and":[29,94,120,162,170,179,195,202,207],"supervised":[30],"learning":[31],"method,":[32],"we":[33,116],"find":[34,137],"that":[35,62,138],"ratings":[36,52],"of":[37,53,65,69,75,90,98,106,109,126,143,153,219,222,225],"non-documentary":[38],"(feature":[39],"film)":[40],"can":[42],"be":[43],"predicted":[44],"higher":[46],"accuracy":[47,74,89],"(73.67%,":[48],"F1":[49],"score)":[50],"than":[51,176,199],"(68.05%).":[56],"We":[57,136],"also":[58,117],"constructed":[59],"classifier":[61],"separates":[63],"documentaries":[66,110,148],"from":[67],"feature":[70,114,144],"films":[71,127],"an":[73],"71.32%.":[76],"However,":[77],"as":[78,128,130],"goal":[80],"this":[82,212],"paper":[83],"not":[85],"to":[86,102,113,141,182,215],"improve":[87],"the":[88,92,107,220],"predicting":[91],"rating":[93,189],"type":[95],"or":[96],"genre":[97],"film":[99],"reviews,":[100,184],"but":[101,151],"advance":[103],"understanding":[105,218],"perception":[108],"comparison":[112],"identified":[118],"commonalities":[119],"differences":[121],"between":[122,131],"these":[123],"two":[124],"types":[125,224],"well":[129],"low":[132],"versus":[133],"high":[134,188],"ratings.":[135],"contrast":[140],"comments":[146,185],"are":[149,156,166,171,190,192],"shorter":[150],"composed":[152],"longer":[154],"sentences,":[155],"less":[157,160,204],"emotional,":[158],"contain":[159,196],"positive":[161,198],"more":[163,168,172,193,197,208],"negative":[164,200],"terms,":[165],"lexically":[167],"concise,":[169],"focused":[173],"verbs":[175],"nouns":[178],"adjectives.":[180],"Compared":[181],"low-rated":[183],"shorter,":[191],"emotional":[194],"sentiment,":[201],"have":[203],"question":[205],"marks":[206],"exclamation":[209],"points.":[210],"Overall,":[211],"work":[213],"contributes":[214],"advancing":[216],"different":[223],"information":[226,230],"products":[227],"individual":[229],"consumers.":[231]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
