{"id":"https://openalex.org/W3042252174","doi":"https://doi.org/10.1145/3386392.3397600","title":"Designing with AI for Digital Marketing","display_name":"Designing with AI for Digital Marketing","publication_year":2020,"publication_date":"2020-07-13","ids":{"openalex":"https://openalex.org/W3042252174","doi":"https://doi.org/10.1145/3386392.3397600","mag":"3042252174"},"language":"en","primary_location":{"id":"doi:10.1145/3386392.3397600","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3386392.3397600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization","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/A5102835950","display_name":"Moumita Sinha","orcid":"https://orcid.org/0000-0001-5634-4345"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Moumita Sinha","raw_affiliation_strings":["Adobe Inc., San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Inc., San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072471679","display_name":"Jennifer Healey","orcid":"https://orcid.org/0000-0002-5700-4921"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer Healey","raw_affiliation_strings":["Adobe Research, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"Adobe Research, San Jose, CA, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058814287","display_name":"Tathagata Sengupta","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tathagata Sengupta","raw_affiliation_strings":["Adobe Inc., Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Adobe Inc., Bangalore, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102835950"],"corresponding_institution_ids":["https://openalex.org/I1306409833"],"apc_list":null,"apc_paid":null,"fwci":0.9279,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.80309441,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"65","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9980000257492065,"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":0.9980000257492065,"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/T12128","display_name":"AI in Service Interactions","score":0.9853000044822693,"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":0.9745000004768372,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7283304929733276},{"id":"https://openalex.org/keywords/readability","display_name":"Readability","score":0.6733739376068115},{"id":"https://openalex.org/keywords/formality","display_name":"Formality","score":0.5925153493881226},{"id":"https://openalex.org/keywords/usable","display_name":"USable","score":0.5514925718307495},{"id":"https://openalex.org/keywords/click-through-rate","display_name":"Click-through rate","score":0.4943552017211914},{"id":"https://openalex.org/keywords/online-advertising","display_name":"Online advertising","score":0.4712519943714142},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4452468454837799},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.4335050582885742},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3515254259109497},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.23962831497192383}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7283304929733276},{"id":"https://openalex.org/C2778143727","wikidata":"https://www.wikidata.org/wiki/Q1820650","display_name":"Readability","level":2,"score":0.6733739376068115},{"id":"https://openalex.org/C2777159308","wikidata":"https://www.wikidata.org/wiki/Q1757948","display_name":"Formality","level":2,"score":0.5925153493881226},{"id":"https://openalex.org/C2780615836","wikidata":"https://www.wikidata.org/wiki/Q2471869","display_name":"USable","level":2,"score":0.5514925718307495},{"id":"https://openalex.org/C115174607","wikidata":"https://www.wikidata.org/wiki/Q1100934","display_name":"Click-through rate","level":2,"score":0.4943552017211914},{"id":"https://openalex.org/C512338625","wikidata":"https://www.wikidata.org/wiki/Q624902","display_name":"Online advertising","level":3,"score":0.4712519943714142},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4452468454837799},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.4335050582885742},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3515254259109497},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.23962831497192383},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3386392.3397600","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3386392.3397600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1530186825","https://openalex.org/W1967390364","https://openalex.org/W1996430422","https://openalex.org/W2122369144","https://openalex.org/W2657160185","https://openalex.org/W2916072792","https://openalex.org/W3004121134","https://openalex.org/W4239946314","https://openalex.org/W4301409532"],"related_works":["https://openalex.org/W3121555120","https://openalex.org/W4286419063","https://openalex.org/W175164097","https://openalex.org/W2100597815","https://openalex.org/W2143648166","https://openalex.org/W1977797174","https://openalex.org/W2106728444","https://openalex.org/W2463331419","https://openalex.org/W3120879483","https://openalex.org/W2334894004"],"abstract_inverted_index":{"We":[0,35,99],"present":[1],"an":[2,121],"interactive":[3],"user":[4],"interface":[5],"that":[6,22,65,114,139],"allows":[7],"digital":[8,43,115],"marketing":[9,44,116],"professionals":[10,45,117],"to":[11,16,37,41,142,154],"have":[12],"real":[13],"time":[14],"access":[15],"insights":[17],"from":[18],"a":[19,108,148],"back-end":[20],"AI":[21,133],"predicts":[23],"potential":[24],"click-through":[25,144],"rates":[26,70],"of":[27,82,131],"composed":[28],"content":[29,64,72,138],"based":[30],"on":[31,107,147,157],"similar":[32],"past":[33],"campaigns.":[34],"wanted":[36],"investigate":[38],"the":[39,57,75,119,129,132],"extent":[40],"which":[42],"would":[46,62],"find":[47],"our":[48,59,101],"system":[49,60,120],"usable":[50],"and":[51,53,91,93,97,126],"useful":[52],"whether":[54],"or":[55],"not":[56],"advice":[58,130],"generated":[61],"create":[63],"had":[66],"higher":[67],"click":[68],"through":[69],"than":[71],"developed":[73],"without":[74],"system's":[76],"advice.":[77],"Our":[78],"framework":[79],"decomposes":[80],"aspects":[81],"prior":[83],"campaigns":[84],"into":[85],"features":[86],"including":[87],"image":[88],"quality,":[89],"memorability,":[90],"placement;":[92],"text":[94],"readability,":[95],"formality":[96],"sentiment.":[98],"show":[100],"algorithm":[102],"has":[103],"high":[104,123],"predictive":[105],"value":[106],"historical":[109],"test":[110],"set":[111],"(AUC":[112],".80);":[113],"give":[118],"overall":[122],"satisfaction":[124],"rating":[125],"that,":[127],"using":[128],"agent,":[134],"we":[135],"can":[136],"generate":[137],"creates":[140],"up":[141],"22%":[143],"rate":[145],"lift":[146],"700":[149],"A/B":[150],"preference":[151],"tasks":[152],"given":[153],"master":[155],"workers":[156],"AMT.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
