{"id":"https://openalex.org/W2895956802","doi":"https://doi.org/10.1145/3240508.3266438","title":"An Effective Text-based Characterization Combined with Numerical Features for Social Media Headline Prediction","display_name":"An Effective Text-based Characterization Combined with Numerical Features for Social Media Headline Prediction","publication_year":2018,"publication_date":"2018-10-15","ids":{"openalex":"https://openalex.org/W2895956802","doi":"https://doi.org/10.1145/3240508.3266438","mag":"2895956802"},"language":"en","primary_location":{"id":"doi:10.1145/3240508.3266438","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3240508.3266438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM international conference on Multimedia","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/A5029641017","display_name":"Liuwu Li","orcid":"https://orcid.org/0000-0002-6237-5380"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liuwu Li","raw_affiliation_strings":["Guangdong University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015970947","display_name":"Sihong Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sihong Huang","raw_affiliation_strings":["Guangdong University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101061259","display_name":"Ziliang He","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziliang He","raw_affiliation_strings":["Guangdong University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073720799","display_name":"Wenyin Liu","orcid":"https://orcid.org/0000-0002-6237-6607"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyin Liu","raw_affiliation_strings":["Guangdong University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0137,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82937341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2003","last_page":"2007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9939000010490417,"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":0.9914000034332275,"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/headline","display_name":"Headline","score":0.9861055612564087},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7696048617362976},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.7429183721542358},{"id":"https://openalex.org/keywords/characterization","display_name":"Characterization (materials science)","score":0.6711946725845337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4411838948726654},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41751915216445923},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3510294556617737},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3323463797569275},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.23505538702011108},{"id":"https://openalex.org/keywords/advertising","display_name":"Advertising","score":0.13252538442611694}],"concepts":[{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.9861055612564087},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7696048617362976},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7429183721542358},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.6711946725845337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4411838948726654},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41751915216445923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3510294556617737},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3323463797569275},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.23505538702011108},{"id":"https://openalex.org/C112698675","wikidata":"https://www.wikidata.org/wiki/Q37038","display_name":"Advertising","level":1,"score":0.13252538442611694},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3240508.3266438","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3240508.3266438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM international conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2090059852","https://openalex.org/W2112477171","https://openalex.org/W2546239132","https://openalex.org/W2766233751","https://openalex.org/W2766908198","https://openalex.org/W2767127404","https://openalex.org/W2805259353","https://openalex.org/W4249977334"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4285135530","https://openalex.org/W2380567098","https://openalex.org/W2035489689","https://openalex.org/W906669285","https://openalex.org/W1553197492","https://openalex.org/W85886512","https://openalex.org/W1586468330","https://openalex.org/W1514610457","https://openalex.org/W3173716828"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,39],"text-based":[4,31],"characterization":[5,32],"combined":[6],"with":[7],"numerical":[8,61],"features":[9,36,43],"for":[10],"Social":[11],"Media":[12],"Headline":[13],"Prediction":[14],"(SMHP)":[15],"is":[16],"proposed.":[17],"Description":[18],"of":[19,44,50,72],"images,":[20],"users'":[21],"emotions":[22],"and":[23],"opinions":[24],"are":[25],"all":[26],"described":[27],"in":[28],"text,":[29],"our":[30],"learns":[33],"these":[34],"important":[35],"by":[37],"training":[38],"Doc2vec":[40],"model.":[41],"Numerical":[42],"social":[45,51],"cues":[46],"contain":[47],"general":[48],"characteristics":[49],"media":[52],"headline,":[53],"we":[54],"build":[55],"an":[56],"effective":[57],"method":[58],"to":[59],"extract":[60],"features.":[62],"Experiments":[63],"conducted":[64],"on":[65],"real-world":[66],"SMHP":[67],"dataset":[68],"manifest":[69],"the":[70,73,78],"effectiveness":[71],"proposed":[74],"approach,":[75],"which":[76],"achieves":[77],"following":[79],"performance:":[80],"Spearmanr's":[81],"Rho:":[82],"0.4559,":[83],"MAE:1.9797.":[84]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
