{"id":"https://openalex.org/W4361002670","doi":"https://doi.org/10.1140/epjds/s13688-023-00383-9","title":"Experimental evaluation of baselines for forecasting social media timeseries","display_name":"Experimental evaluation of baselines for forecasting social media timeseries","publication_year":2023,"publication_date":"2023-03-27","ids":{"openalex":"https://openalex.org/W4361002670","doi":"https://doi.org/10.1140/epjds/s13688-023-00383-9","pmid":"https://pubmed.ncbi.nlm.nih.gov/37006640"},"language":"en","primary_location":{"id":"doi:10.1140/epjds/s13688-023-00383-9","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1140/epjds/s13688-023-00383-9","pdf_url":"https://link.springer.com/content/pdf/10.1140/epjds/s13688-023-00383-9.pdf","source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1140/epjds/s13688-023-00383-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036896676","display_name":"Kin Wai Ng","orcid":"https://orcid.org/0000-0001-9784-8427"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kin Wai Ng","raw_affiliation_strings":["University of South Florida, 4202 E. Fowler Ave, 33620 Tampa, FL USA","University of South Florida, 4202 E. Fowler Ave, 33620, Tampa, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Florida, 4202 E. Fowler Ave, 33620 Tampa, FL USA","institution_ids":["https://openalex.org/I2613432"]},{"raw_affiliation_string":"University of South Florida, 4202 E. Fowler Ave, 33620, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042367791","display_name":"Frederick Mubang","orcid":null},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Frederick Mubang","raw_affiliation_strings":["University of South Florida, 4202 E. Fowler Ave, 33620 Tampa, FL USA","University of South Florida, 4202 E. Fowler Ave, 33620, Tampa, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Florida, 4202 E. Fowler Ave, 33620 Tampa, FL USA","institution_ids":["https://openalex.org/I2613432"]},{"raw_affiliation_string":"University of South Florida, 4202 E. Fowler Ave, 33620, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000168449","display_name":"Lawrence Hall","orcid":"https://orcid.org/0000-0002-7898-8456"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lawrence O. Hall","raw_affiliation_strings":["University of South Florida, 4202 E. Fowler Ave, 33620 Tampa, FL USA","University of South Florida, 4202 E. Fowler Ave, 33620, Tampa, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Florida, 4202 E. Fowler Ave, 33620 Tampa, FL USA","institution_ids":["https://openalex.org/I2613432"]},{"raw_affiliation_string":"University of South Florida, 4202 E. Fowler Ave, 33620, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014846800","display_name":"John Skvoretz","orcid":"https://orcid.org/0000-0003-0573-1710"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Skvoretz","raw_affiliation_strings":["University of South Florida, 4202 E. Fowler Ave, 33620 Tampa, FL USA","University of South Florida, 4202 E. Fowler Ave, 33620, Tampa, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of South Florida, 4202 E. Fowler Ave, 33620 Tampa, FL USA","institution_ids":["https://openalex.org/I2613432"]},{"raw_affiliation_string":"University of South Florida, 4202 E. Fowler Ave, 33620, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007419039","display_name":"Adriana Iamnitchi","orcid":"https://orcid.org/0000-0002-2397-8963"},"institutions":[{"id":"https://openalex.org/I34352273","display_name":"Maastricht University","ror":"https://ror.org/02jz4aj89","country_code":"NL","type":"education","lineage":["https://openalex.org/I34352273"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Adriana Iamnitchi","raw_affiliation_strings":["Maastricht University, Minderbroedersberg 4-6, 6211 LK Maastricht, The Netherlands","Maastricht University, Minderbroedersberg 4-6, 6211 LK, Maastricht, The Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-2397-8963","affiliations":[{"raw_affiliation_string":"Maastricht University, Minderbroedersberg 4-6, 6211 LK Maastricht, The Netherlands","institution_ids":["https://openalex.org/I34352273"]},{"raw_affiliation_string":"Maastricht University, Minderbroedersberg 4-6, 6211 LK, Maastricht, The Netherlands","institution_ids":["https://openalex.org/I34352273"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5007419039"],"corresponding_institution_ids":["https://openalex.org/I34352273"],"apc_list":{"value":1190,"currency":"GBP","value_usd":1459},"apc_paid":{"value":1190,"currency":"GBP","value_usd":1459},"fwci":1.2403,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76891596,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"12","issue":"1","first_page":"8","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9958999752998352,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9958999752998352,"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"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9950000047683716,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7603049278259277},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7421591877937317},{"id":"https://openalex.org/keywords/currency","display_name":"Currency","score":0.5349007844924927},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.497149258852005},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.47528401017189026},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34089672565460205},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3404633402824402},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.14574912190437317}],"concepts":[{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7603049278259277},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7421591877937317},{"id":"https://openalex.org/C141121606","wikidata":"https://www.wikidata.org/wiki/Q8142","display_name":"Currency","level":2,"score":0.5349007844924927},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.497149258852005},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.47528401017189026},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34089672565460205},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3404633402824402},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.14574912190437317},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C556758197","wikidata":"https://www.wikidata.org/wiki/Q580018","display_name":"Monetary economics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1140/epjds/s13688-023-00383-9","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1140/epjds/s13688-023-00383-9","pdf_url":"https://link.springer.com/content/pdf/10.1140/epjds/s13688-023-00383-9.pdf","source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Data Science","raw_type":"journal-article"},{"id":"pmid:37006640","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37006640","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ data science","raw_type":null},{"id":"pmh:oai:cris.maastrichtuniversity.nl:openaire_cris_publications/3ff4f448-bf18-4bb4-994e-a9b0f5714330","is_oa":true,"landing_page_url":"https://cris.maastrichtuniversity.nl/en/publications/3ff4f448-bf18-4bb4-994e-a9b0f5714330","pdf_url":null,"source":{"id":"https://openalex.org/S4306402616","display_name":"Research Publications (Maastricht University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I34352273","host_organization_name":"Maastricht University","host_organization_lineage":["https://openalex.org/I34352273"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Ng, K W, Mubang, F, Hall, L O, Skvoretz, J & Iamnitchi, A 2023, 'Experimental evaluation of baselines for forecasting social media timeseries', EPJ Data Science, vol. 12, no. 1, 8. https://doi.org/10.1140/epjds/s13688-023-00383-9","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pubmedcentral.nih.gov:10042102","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10042102","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10042102/pdf/13688_2023_Article_383.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EPJ Data Sci","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:79e7bf3b96ae41f58d7de2a550ceb534","is_oa":true,"landing_page_url":"https://doaj.org/article/79e7bf3b96ae41f58d7de2a550ceb534","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EPJ Data Science, Vol 12, Iss 1, Pp 1-26 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1140/epjds/s13688-023-00383-9","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1140/epjds/s13688-023-00383-9","pdf_url":"https://link.springer.com/content/pdf/10.1140/epjds/s13688-023-00383-9.pdf","source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Data Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1438141514","display_name":null,"funder_award_id":"FA8650-18-C-7825","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G2078018843","display_name":null,"funder_award_id":"FA8650-18-C-7825","funder_id":"https://openalex.org/F4320338294","funder_display_name":"Air Force Research Laboratory"},{"id":"https://openalex.org/G7053229769","display_name":null,"funder_award_id":"FA8650-18-C-7825","funder_id":"https://openalex.org/F4320337531","funder_display_name":"Defense Sciences Office, DARPA"}],"funders":[{"id":"https://openalex.org/F4320315952","display_name":"Leidos","ror":"https://ror.org/012cvds63"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337531","display_name":"Defense Sciences Office, DARPA","ror":"https://ror.org/0447fe631"},{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4361002670.pdf","grobid_xml":"https://content.openalex.org/works/W4361002670.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1480674897","https://openalex.org/W1586335931","https://openalex.org/W1594866779","https://openalex.org/W1598265492","https://openalex.org/W1985790185","https://openalex.org/W2069849731","https://openalex.org/W2119114394","https://openalex.org/W2170389435","https://openalex.org/W2276587416","https://openalex.org/W2515728551","https://openalex.org/W2773050805","https://openalex.org/W2779419748","https://openalex.org/W2898019631","https://openalex.org/W2909877301","https://openalex.org/W2949377321","https://openalex.org/W2988651635","https://openalex.org/W2989986002","https://openalex.org/W3002841825","https://openalex.org/W3016053201","https://openalex.org/W3032916997","https://openalex.org/W3035390927","https://openalex.org/W3049290562","https://openalex.org/W3102147628","https://openalex.org/W3111484910","https://openalex.org/W3122471732","https://openalex.org/W3134841863","https://openalex.org/W4212937970","https://openalex.org/W4213275585","https://openalex.org/W4285292438","https://openalex.org/W4290509785","https://openalex.org/W4294597351","https://openalex.org/W4298854966","https://openalex.org/W6677096361"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2043093291"],"abstract_inverted_index":{"Forecasting":[0],"social":[1,74,123],"media":[2,75,124],"activity":[3,71],"can":[4],"be":[5],"of":[6,66],"practical":[7],"use":[8],"in":[9,25,72,122],"many":[10],"scenarios,":[11],"from":[12],"understanding":[13],"trends,":[14],"such":[15,33],"as":[16,34],"which":[17,56,108],"topics":[18],"are":[19,97,109],"likely":[20],"to":[21,29,47,52,57,81],"engage":[22],"more":[23],"users":[24],"the":[26,64,106],"coming":[27],"week,":[28],"identifying":[30],"unusual":[31],"behavior,":[32],"coordinated":[35],"information":[36],"operations":[37],"or":[38],"currency":[39],"manipulation":[40],"efforts.":[41],"To":[42],"evaluate":[43,63],"a":[44],"new":[45],"approach":[46],"forecasting,":[48],"it":[49],"is":[50],"important":[51],"have":[53],"baselines":[54,68,107],"against":[55],"assess":[58],"performance":[59,65],"gains.":[60],"We":[61],"experimentally":[62],"four":[67],"for":[69,112,119],"forecasting":[70],"several":[73],"datasets":[76],"that":[77],"record":[78],"discussions":[79],"related":[80],"three":[82],"different":[83,91],"geo-political":[84],"contexts":[85],"synchronously":[86],"taking":[87],"place":[88],"on":[89],"two":[90],"platforms,":[92],"Twitter":[93],"and":[94,115],"YouTube.":[95],"Experiments":[96],"done":[98],"over":[99],"hourly":[100],"time":[101],"periods.":[102],"Our":[103],"evaluation":[104],"identifies":[105],"most":[110],"accurate":[111],"particular":[113],"metrics":[114],"thus":[116],"provides":[117],"guidance":[118],"future":[120],"work":[121],"modeling.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
