{"id":"https://openalex.org/W6949121270","doi":"https://doi.org/10.5281/zenodo.11409612","title":"CMFeed: A Benchmark Dataset for Controllable Multimodal Feedback Synthesis","display_name":"CMFeed: A Benchmark Dataset for Controllable Multimodal Feedback Synthesis","publication_year":2024,"publication_date":"2024-06-01","ids":{"openalex":"https://openalex.org/W6949121270","doi":"https://doi.org/10.5281/zenodo.11409612"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.11409612","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.11409612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.11409612","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kumar, Puneet","orcid":"https://orcid.org/0000-0002-4318-1353"},"institutions":[{"id":"https://openalex.org/I98381234","display_name":"University of Oulu","ror":"https://ror.org/03yj89h83","country_code":"FI","type":"education","lineage":["https://openalex.org/I98381234"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Kumar, Puneet","raw_affiliation_strings":["University of Oulu"],"raw_orcid":"https://orcid.org/0000-0002-4318-1353","affiliations":[{"raw_affiliation_string":"University of Oulu","institution_ids":["https://openalex.org/I98381234"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Malik, Sarthak","orcid":"https://orcid.org/0000-0001-5224-1445"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Malik, Sarthak","raw_affiliation_strings":["Indian Institute of Technology Roorkee"],"raw_orcid":"https://orcid.org/0000-0001-5224-1445","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Roorkee","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Raman, Balasubramanian","orcid":"https://orcid.org/0000-0001-6277-6267"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Raman, Balasubramanian","raw_affiliation_strings":["Indian Institute of Technology Roorkee"],"raw_orcid":"https://orcid.org/0000-0001-6277-6267","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Roorkee","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"last","author":{"id":null,"display_name":"Li, Xiaobai","orcid":"https://orcid.org/0000-0003-4519-7823"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li, Xiaobai","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":"https://orcid.org/0000-0003-4519-7823","affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.14730000495910645,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.14730000495910645,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.11540000140666962,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.10239999741315842,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.9007999897003174},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6608999967575073},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6269000172615051},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6134999990463257},{"id":"https://openalex.org/keywords/crawling","display_name":"Crawling","score":0.5922999978065491},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5138999819755554},{"id":"https://openalex.org/keywords/relevance-feedback","display_name":"Relevance feedback","score":0.44519999623298645},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.43790000677108765},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.40059998631477356}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9007999897003174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7508000135421753},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6608999967575073},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6269000172615051},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6134999990463257},{"id":"https://openalex.org/C100368936","wikidata":"https://www.wikidata.org/wiki/Q1411725","display_name":"Crawling","level":2,"score":0.5922999978065491},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5138999819755554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49559998512268066},{"id":"https://openalex.org/C2779532271","wikidata":"https://www.wikidata.org/wiki/Q445558","display_name":"Relevance feedback","level":4,"score":0.44519999623298645},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.43790000677108765},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40880000591278076},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.40059998631477356},{"id":"https://openalex.org/C186886427","wikidata":"https://www.wikidata.org/wiki/Q5441213","display_name":"Feedback loop","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C48209547","wikidata":"https://www.wikidata.org/wiki/Q1331104","display_name":"Controllability","level":2,"score":0.3587999939918518},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3517000079154968},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34850001335144043},{"id":"https://openalex.org/C130440534","wikidata":"https://www.wikidata.org/wiki/Q14946528","display_name":"Conflation","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.3377000093460083},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3228999972343445},{"id":"https://openalex.org/C2780660688","wikidata":"https://www.wikidata.org/wiki/Q25052564","display_name":"Multimodal learning","level":2,"score":0.3165999948978424},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2939000129699707},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26339998841285706},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C56288433","wikidata":"https://www.wikidata.org/wiki/Q58673","display_name":"Data manipulation language","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5281/zenodo.11409612","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.11409612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.5281/zenodo.11409612","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.11409612","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"OverviewThe":[0],"Controllable":[1],"Multimodal":[2],"Feedback":[3],"Synthesis":[4],"(CMFeed)":[5],"Dataset":[6,697,983,1105],"is":[7,91,255,280,326,506,740,822,892,918,1250,1299,1344,1409,1416,1441],"designed":[8,1287],"to":[9,28,167,188,268,296,328,334,485,495,546,554,560,581,617,659,744,768,789,802,843,1046,1059,1168,1206,1225,1255,1280,1340,1366,1418],"enable":[10],"the":[11,46,50,61,65,76,123,129,143,147,215,256,351,370,375,412,421,427,469,502,522,533,540,547,555,561,567,582,590,598,605,611,618,626,639,647,651,684,687,704,717,760,770,775,803,914,925,991,998,1013,1025,1031,1087,1097,1111,1164,1210,1263,1313,1325,1371,1388,1392,1396,1401],"generation":[12],"of":[13,52,86,125,146,214,356,369,456,463,468,501,532,539,565,589,595,609,625,641,686,706,716,720,774,805,853,976,990,1002,1005,1027,1036,1067,1093,1101,1114,1137,1163,1198,1212,1327,1374,1391],"sentiment-controlled":[14,37],"feedback":[15,30,54,67,89,422,1289],"from":[16,94,183,655,781,792,1041,1054,1161,1420],"multimodal":[17,88,155],"inputs,":[18],"including":[19],"text":[20,538],"and":[21,36,70,79,96,100,110,117,154,159,164,175,190,205,245,272,300,315,348,388,481,499,584,607,631,665,672,675,714,726,737,747,766,772,797,811,818,849,867,873,887,907,927,947,962,979,985,1023,1033,1050,1069,1081,1099,1107,1171,1209,1219,1319,1347,1361,1369,1382,1415],"images.":[22],"This":[23,162,518,970,1075,1130,1201,1297,1407],"dataset":[24,48,211,352,471,505,1088,1393,1408],"can":[25,121,816],"be":[26],"used":[27,258,418,1345],"train":[29],"synthesis":[31,68,90,423,1290],"models":[32,69,372],"in":[33,43,75,142,171,393,419,426,508,515,846,913,924,934,956,1072,1182,1195,1236,1306,1317,1376],"both":[34],"uncontrolled":[35],"manners.":[38],"Serving":[39],"a":[40,56,383,899,973,1064,1090,1196],"crucial":[41,842,1300],"role":[42],"advancing":[44],"research,":[45],"CMFeed":[47],"supports":[49],"development":[51],"human-like":[53],"synthesis,":[55],"novel":[57],"task":[58,85],"defined":[59],"by":[60,103,114,179],"dataset's":[62],"authors.":[63],"Additionally,":[64,1030],"corresponding":[66,148,428,494,513,1254,1397],"benchmark":[71],"results":[72],"are":[73,306,831,949,1016,1259,1274,1310,1431],"presented":[74],"associated":[77,1192],"code":[78],"research":[80,149,429,1413,1423],"publication.":[81],"Task":[82],"Uniqueness:":[83],"The":[84,193,320,530,537,944,1271],"controllable":[87],"unique,":[92],"distinct":[93,884],"LLMs":[95,106],"tasks":[97],"like":[98],"VisDial,":[99],"not":[101,248,338,417,778,788,967,1077,1303],"addressed":[102],"multi-modal":[104],"LLMs.":[105],"often":[107],"exhibit":[108],"errors":[109],"hallucinations,":[111],"as":[112,140,230,403,703,749,752,795,814,942,960,1301,1324],"evidenced":[113],"their":[115,585,883],"auto-regressive":[116],"black-box":[118],"nature,":[119],"which":[120],"obscure":[122],"influence":[124],"different":[126,782],"modalities":[127],"on":[128,250,324,330,374,597,621,629,638,755,838,1358],"generated":[130],"responses":[131,158],"[Ref1;":[132],"Ref2].":[133],"Our":[134,836,1332],"approach":[135,1076],"includes":[136,521],"an":[137,1293],"interpretability":[138,165,1295],"mechanism,":[139],"detailed":[141],"supplementary":[144],"material":[145],"publication,":[150],"demonstrating":[151],"how":[152,1308],"metadata":[153,228],"features":[156],"shape":[157],"learn":[160],"sentiments.":[161],"controllability":[163],"aim":[166,1365],"inspire":[168],"new":[169],"methodologies":[170],"related":[172,484,516,559],"fields.Data":[173],"Collection":[174],"AnnotationData":[176],"was":[177,208,219,841,1339],"collected":[178,1247],"crawling":[180],"Facebook":[181,207,218,254,279,325,800,839,1109,1155,1268],"posts":[182,1160,1176,1186],"major":[184],"news":[185,231,534,541,549,721,855,860,878,939,1038,1166,1256],"outlets,":[186],"adhering":[187],"ethical":[189,723,809,1151,1227,1240,1380],"legal":[191],"standards.":[192],"comments":[194,363,1273],"were":[195,396,401,416,880,1177],"annotated":[196],"using":[197],"four":[198,371,854,859,1165],"sentiment":[199,384,394,642,652,685],"analysis":[200,643],"models:":[201],"FLAIR,":[202],"SentimentR,":[203],"RoBERTa,":[204],"DistilBERT.":[206],"chosen":[209,220,881],"for":[210,221,298,302,308,411,710,833,882,894,920,1146,1153,1265,1335,1411,1425],"construction":[212],"because":[213,224],"following":[216,523,761,1262],"factors:\u2022":[217],"data":[222,711,731,739,764,780,791,847,1142,1156,1217,1222,1235,1248,1269],"collection":[223,1223],"it":[225,1302,1343],"uniquely":[226],"provides":[227,931],"such":[229,702,794,941,959,1323],"article":[232],"link,":[233],"post":[234,236,568,583],"shares,":[235],"reaction,":[237],"comment":[238,240,242,612,620,627,688,817],"like,":[239],"rank,":[241,244],"reaction":[243,482],"relevance":[246],"scores,":[247],"available":[249,1128,1234],"other":[251,826,938],"platforms.":[252],"\u2022":[253,278,319,528,851,982,1104],"most":[257],"social":[259,707,783,995,1007],"media":[260,708,784,996,1008],"platform,":[261],"with":[262,290,382,492,512,799,898,1089,1121,1238,1292,1378],"3.07":[263,988],"billion":[264,989,994],"monthly":[265],"users,":[266,997],"compared":[267,295],"550":[269],"million":[270,274],"Twitter":[271,299,798],"500":[273],"Reddit":[275,336,796],"users.":[276],"[Ref]":[277,318,342],"popular":[281],"across":[282,1018],"all":[283,1191],"age":[284],"groups":[285],"(18-29,":[286],"30-49,":[287],"50-64,":[288],"65+),":[289],"at":[291,365,1400,1435],"least":[292,366],"58%":[293],"usage,":[294],"6%":[297],"3%":[301],"Reddit.":[303],"[Ref].":[304,1229,1245,1270],"Trends":[305],"similar":[307],"gender,":[309],"race,":[310],"ethnicity,":[311],"income,":[312],"education,":[313],"community,":[314],"political":[316,977,1034,1052,1070],"affiliation":[317],"male-to-female":[321],"user":[322,591,1000],"ratio":[323],"56.3%":[327],"43.7%;":[329],"Twitter,":[331],"it's":[332],"66.72%":[333],"23.28%;":[335],"does":[337],"report":[339],"this":[340,1122,1337,1433],"data.":[341,1118,1129],"Filtering":[343],"Process:":[344],"To":[345],"ensure":[346,748,769,844,871,1341],"high-quality":[347],"reliable":[349],"data,":[350,718],"underwent":[353],"two":[354,473],"levels":[355],"filtering:a)":[357],"Model":[358],"Agreement":[359],"Filtering:":[360],"Retained":[361],"only":[362,1078,1304,1414],"where":[364],"three":[367],"out":[368],"agreed":[373],"sentiment.b)":[376],"Probability":[377],"Range":[378],"Safety":[379],"Margin:":[380],"Comments":[381],"probability":[385],"between":[386],"0.49":[387],"0.51,":[389],"indicating":[390],"low":[391],"confidence":[392],"classification,":[395],"excluded.After":[397],"filtering,":[398],"4,512":[399],"samples":[400,407],"marked":[402],"XX.":[404],"Though":[405],"these":[406,756,824,1037],"have":[408,966,1285],"been":[409,570,968],"released":[410,1410],"reader's":[413],"understanding,":[414],"they":[415,965],"training":[420],"model":[424],"proposed":[425],"paper.Dataset":[430],"Description\u2022":[431],"Total":[432,435,441],"Samples:":[433],"61,734\u2022":[434],"Samples":[436],"Annotated:":[437],"57,222":[438],"after":[439,1179],"filtering.\u2022":[440],"Posts:":[442],"3,646\u2022":[443],"Average":[444,449,454,461],"Likes":[445,450],"per":[446,451,465],"Post:":[447,466,529],"65.1\u2022":[448],"Comment:":[452,587],"10.5\u2022":[453],"Length":[455],"News":[457,891,903,917,930],"Text:":[458],"655":[459],"words\u2022":[460],"Number":[462,564,594],"Images":[464,488],"3.7Components":[467],"DatasetThe":[470],"comprises":[472],"main":[474],"components:\u2022":[475],"CMFeed.csv":[476,509],"File:":[477],"Contains":[478,490],"metadata,":[479,807],"comment,":[480],"details":[483],"each":[486,496,1162],"post.\u2022":[487,562],"Folder:":[489],"folders":[491],"images":[493,514,558],"post.Data":[497],"Format":[498],"Fields":[500],"CSV":[503,519],"FileThe":[504],"structured":[507],"file":[510,520],"along":[511],"folders.":[517],"fields:\u2022":[524],"Id:":[525],"Unique":[526],"identifier":[527],"heading":[531],"article.\u2022":[535,542,550],"News_text:":[536],"News_link:":[543],"URL":[544,615],"link":[545,616],"original":[548,619,1333],"News_Images:":[551],"A":[552,573,601],"path":[553],"folder":[556],"containing":[557],"Post_shares:":[563],"times":[566],"has":[569],"shared.\u2022":[571],"Post_reaction:":[572],"JSON":[574,602],"object":[575,603],"capturing":[576],"reactions":[577,610],"(like,":[578],"love,":[579],"etc.)":[580],"counts.\u2022":[586],"Text":[588],"comment.\u2022":[592,599],"Comment_like:":[593],"likes":[596],"Comment_reaction_rank:":[600],"detailing":[604],"type":[606],"count":[608],"received.\u2022":[613],"Comment_link:":[614],"Facebook.\u2022":[622],"Comment_rank:":[623],"Rank":[624],"based":[628,637],"engagement":[630,1009],"relevance.\u2022":[632],"Score:":[633],"Sentiment":[634],"score":[635],"computed":[636],"consensus":[640,648],"models.\u2022":[644],"Agreement:":[645],"Indicates":[646],"level":[649],"among":[650],"models,":[653],"ranging":[654,1040],"-4":[656],"(all":[657,661],"negative)":[658],"4":[660],"positive).":[662],"3":[663,673],"negative":[664,677],"1":[666,676,690],"positive":[667,1351],"will":[668,678],"result":[669,679],"into":[670,680,689],"-2":[671],"positives":[674],"+2.\u2022":[681],"Sentiment_class:":[682],"Categorizes":[683],"(positive)":[691],"or":[692,1329,1422],"0":[693],"(negative).More":[694],"Considerations":[695],"During":[696],"ConstructionWe":[698],"thoroughly":[699],"considered":[700],"issues":[701],"choice":[705],"platform":[709],"collection,":[712],"bias":[713,1022],"generalizability":[715,751,1026],"selection":[719,971],"handles/websites,":[722],"protocols,":[724],"privacy":[725,1218],"potential":[727,1282],"misuse":[728,1220],"before":[729],"beginning":[730],"collection.":[732],"While":[733],"achieving":[734],"completely":[735],"unbiased":[736],"fair":[738],"unattainable,":[741],"we":[742,758,1124,1284,1364],"endeavored":[743],"minimize":[745],"biases":[746,1083],"much":[750],"possible.":[753],"Building":[754],"considerations,":[757,1216],"made":[759,1311],"decisions":[762,1309],"about":[763],"sources":[765],"handling":[767],"integrity":[771,1211],"utility":[773],"dataset:\u2022":[776],"Why":[777],"merge":[779,790],"platforms?":[785],"We":[786,857,1149,1188,1230,1246],"chose":[787],"platforms":[793,825],"due":[801],"lack":[804],"comprehensive":[806,874],"clear":[808],"guidelines,":[810],"control":[812],"mechanisms\u2014such":[813],"who":[815],"whether":[819],"users'":[820,1116],"anonymity":[821],"maintained\u2014on":[823],"than":[827],"Facebook.":[828],"These":[829,877],"factors":[830],"critical":[832],"our":[834,1028,1073,1102,1141,1213,1288,1379],"analysis.":[835],"focus":[837],"alone":[840],"consistency":[845],"quality":[848],"format.":[850],"Choice":[852],"handles:":[856],"selected":[858],"handles\u2014BBC":[861],"News,":[862,864,866],"Sky":[863,902],"Fox":[865,916],"NY":[868,928],"Daily":[869,929,1044,1057],"News\u2014to":[870],"diversity":[872,1035,1170],"regional":[875,885,957,1080],"coverage.":[876],"outlets":[879],"focuses":[886],"editorial":[888],"perspectives:":[889],"BBC":[890],"known":[893],"its":[895,921,1115,1350],"global":[896,1068],"coverage":[897,933],"centrist":[900],"view,":[901],"offers":[904],"geographically":[905],"targeted":[906],"politically":[908],"varied":[909],"content":[910,923],"learning":[911],"center/right":[912],"UK/EU/US,":[915],"recognized":[919],"right-leaning":[922],"US,":[926],"left-leaning":[932],"New":[935],"York.":[936],"Many":[937],"handles":[940,1167],"NDTV,":[943],"Hindu,":[945],"Xinhua,":[946],"SCMP":[948],"also":[950,1085,1316],"large-scale":[951],"but":[952,1084,1144,1315],"may":[953],"contain":[954],"information":[955],"languages":[958],"Indian":[961],"Chinese,":[963],"hence,":[964],"selected.":[969],"ensures":[972,1011,1063,1204],"broad":[974],"spectrum":[975],"discourse":[978],"audience":[980],"engagement.":[981],"Generalizability":[984],"Bias:":[986],"With":[987],"total":[992,1197],"5":[993],"extensive":[999],"base":[1001],"Facebook,":[1003],"reflective":[1004],"broader":[1006],"patterns,":[1010],"that":[1012,1249,1258,1342,1429],"insights":[1014],"gained":[1015],"applicable":[1017],"various":[1019],"platforms,":[1020],"reducing":[1021],"strengthening":[1024],"findings.":[1029],"geographic":[1032],"sources,":[1039],"local":[1042],"(NY":[1043,1056],"News)":[1045,1058],"international":[1047],"(BBC":[1048],"News),":[1049,1062],"spanning":[1051],"spectra":[1053],"left":[1055],"right":[1060],"(Fox":[1061],"balanced":[1065],"representation":[1066],"viewpoints":[1071],"dataset.":[1074,1214],"mitigates":[1079],"ideological":[1082],"enriches":[1086],"wide":[1091],"array":[1092],"perspectives,":[1094],"further":[1095],"solidifying":[1096],"robustness":[1098],"applicability":[1100],"research.":[1103],"size":[1106],"diversity:":[1108],"prohibits":[1110],"automatic":[1112,1243],"scraping":[1113,1154,1244,1267],"personal":[1117],"In":[1119],"compliance":[1120,1237],"policy,":[1123],"manually":[1125,1231],"scraped":[1126,1232],"publicly":[1127,1233,1251,1260],"labor-intensive":[1131],"process":[1132],"requiring":[1133],"around":[1134],"800":[1135],"hours":[1136],"manual":[1138,1202],"effort,":[1139],"limited":[1140],"volume":[1143],"allowed":[1145],"precise":[1147],"selection.":[1148],"followed":[1150],"protocols":[1152,1264],",":[1157],"selecting":[1158],"1000":[1159],"enhance":[1169],"reduce":[1172],"bias.":[1173],"Initially,":[1174],"4000":[1175],"collected;":[1178],"preprocessing":[1180],"(detailed":[1181],"Section":[1183],"3.1),":[1184],"3646":[1185],"remained.":[1187],"then":[1189],"processed":[1190],"comments,":[1193],"resulting":[1194],"61734":[1199],"comments.":[1200],"method":[1203],"adherence":[1205],"Facebook\u2019s":[1207,1226],"policies":[1208],"Ethical":[1215],"preventionThe":[1221],"adheres":[1224],"guidelines":[1228,1241],"Facebook's":[1239],"prohibiting":[1242],"available,":[1252],"specifically":[1253],"articles":[1257],"accessible":[1261],"ethically":[1266],"human-generated":[1272],"included":[1275],"without":[1276],"identifying":[1277],"information.":[1278],"Aiming":[1279],"prevent":[1281],"misuse,":[1283,1322],"proactively":[1286],"system":[1291,1314],"integral":[1294],"module.":[1296],"feature":[1298],"helps":[1305],"explaining":[1307],"within":[1312],"detecting":[1318],"preventing":[1320],"any":[1321],"creation":[1326],"misleading":[1328],"manipulative":[1330],"content.":[1331],"motivation":[1334],"integrating":[1336],"technology":[1338,1375],"responsibly":[1346],"ethically,":[1348],"enhancing":[1349],"impact":[1352],"while":[1353],"minimizing":[1354],"risks.":[1355],"By":[1356],"focusing":[1357],"developing":[1359],"robust":[1360],"transparent":[1362],"systems,":[1363],"foster":[1367],"trust":[1368],"encourage":[1370],"responsible":[1372],"use":[1373],"line":[1377],"commitments.Code":[1381],"Citation\u2022":[1383],"Code":[1384],"Repository:":[1385],"https://github.com/MIntelligence-Group/CMFeed/\u2022":[1386],"Citing":[1387],"Dataset:":[1389],"Users":[1390],"should":[1394],"cite":[1395],"paper":[1398],"described":[1399],"above":[1402],"GitHub":[1403],"Repository.License":[1404],"&":[1405],"Access\u2022":[1406],"academic":[1412],"free":[1417],"researchers":[1419],"educational":[1421],"institutes":[1424],"non-commercial":[1426],"purposes.\u2022":[1427],"Note":[1428],"you":[1430],"downloading":[1432],"corpus":[1434],"your":[1436],"own":[1437],"risk.":[1438],"No":[1439],"guarantee":[1440],"provided,":[1442],"e.g.":[1443],"regardi":[1444]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-10-10T00:00:00"}