{"id":"https://openalex.org/W2946697491","doi":"https://doi.org/10.1145/3308560.3316490","title":"Problems and Opportunities of Working with a Telco's Large Data Sets of Mobile Data*","display_name":"Problems and Opportunities of Working with a Telco's Large Data Sets of Mobile Data*","publication_year":2019,"publication_date":"2019-05-13","ids":{"openalex":"https://openalex.org/W2946697491","doi":"https://doi.org/10.1145/3308560.3316490","mag":"2946697491"},"language":"en","primary_location":{"id":"doi:10.1145/3308560.3316490","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3308560.3316490","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of The 2019 World Wide Web Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3308560.3316490","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5096566768","display_name":"Universidad del Desarrollo Leo Ferres","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Leo Ferres, Universidad del Desarrollo, Santiago","raw_affiliation_strings":[""],"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5096566768"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3505,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.68789019,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"229","last_page":"229"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13979","display_name":"Communication and COVID-19 Impact","score":0.7979999780654907,"subfield":{"id":"https://openalex.org/subfields/3315","display_name":"Communication"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13979","display_name":"Communication and COVID-19 Impact","score":0.7979999780654907,"subfield":{"id":"https://openalex.org/subfields/3315","display_name":"Communication"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11891","display_name":"Big Data and Business Intelligence","score":0.6898999810218811,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14100","display_name":"Scientific Research and Technology","score":0.6643999814987183,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/government","display_name":"Government (linguistics)","score":0.6375616192817688},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5351200103759766},{"id":"https://openalex.org/keywords/inclusion","display_name":"Inclusion (mineral)","score":0.527975857257843},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.4925883412361145},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.48429933190345764},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4506545066833496},{"id":"https://openalex.org/keywords/public-relations","display_name":"Public relations","score":0.4418381154537201},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4337530732154846},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4332963824272156},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.41633403301239014},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33016133308410645},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3233494162559509},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.29298925399780273},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.2697601020336151},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23087218403816223},{"id":"https://openalex.org/keywords/social-science","display_name":"Social science","score":0.12909084558486938}],"concepts":[{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.6375616192817688},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5351200103759766},{"id":"https://openalex.org/C109359841","wikidata":"https://www.wikidata.org/wiki/Q728944","display_name":"Inclusion (mineral)","level":2,"score":0.527975857257843},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.4925883412361145},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.48429933190345764},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4506545066833496},{"id":"https://openalex.org/C39549134","wikidata":"https://www.wikidata.org/wiki/Q133080","display_name":"Public relations","level":1,"score":0.4418381154537201},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4337530732154846},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4332963824272156},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.41633403301239014},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33016133308410645},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3233494162559509},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.29298925399780273},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.2697601020336151},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23087218403816223},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.12909084558486938},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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:10.1145/3308560.3316490","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3308560.3316490","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of The 2019 World Wide Web Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3308560.3316490","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3308560.3316490","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Companion Proceedings of The 2019 World Wide Web Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8399999737739563,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3185553570","https://openalex.org/W2155401483","https://openalex.org/W3045247719","https://openalex.org/W2102102835","https://openalex.org/W2082438799","https://openalex.org/W1966986837","https://openalex.org/W2360138227","https://openalex.org/W2757130632","https://openalex.org/W3185163327","https://openalex.org/W4385987771"],"abstract_inverted_index":{"Since":[0],"2016,":[1],"through":[2],"an":[3],"association":[4],"between":[5],"Telef\u00f3nica":[6,259],"R&D":[7],"and":[8,20,56,155,181,187,192,218,225,228,244,260,286],"the":[9,46,77,117,153,173,204,221,238,242],"Institute":[10],"of":[11,18,27,39,50,79,88,90,102,147,185,203,216,223,230,274],"Data":[12],"Science":[13],"in":[14,95,116,161,269],"Chile,":[15],"a":[16,80,183,200,256,261,270],"group":[17],"researchers":[19],"myself":[21],"have":[22,58],"been":[23,43,179],"working":[24],"with":[25,175,208],"trillions":[26],"digital":[28],"traces":[29],"left":[30],"behind":[31],"when":[32,134],"people":[33,71,89,135],"use":[34],"their":[35,162],"mobile":[36,82],"phones.":[37],"All":[38],"this":[40,171,195],"work":[41,205],"has":[42,177],"done":[44,207],"under":[45],"general":[47],"umbrella":[48],"term":[49],"\"data":[51],"science":[52],"for":[53,210,237,255],"social":[54,86,124,148,211],"good\",":[55],"we":[57],"worked":[59],"on":[60],"anything":[61],"from":[62,107],"population":[63],"displacement":[64],"after":[65,76,169],"external":[66],"events":[67],"like":[68,258,264],"earthquakes,":[69],"how":[70,114,128,142,150,156],"started":[72],"using":[73],"public":[74],"spaces":[75],"introduction":[78],"popular":[81],"game,":[83],"to":[84,138,266],"actual":[85],"inclusion":[87],"different":[91,157],"socio-economic":[92],"backgrounds":[93],"mixing":[94],"shopping":[96],"malls":[97,144],"or":[98,104],"reading":[99],"certain":[100,143],"kinds":[101],"news,":[103],"patterns":[105],"arising":[106],"gendered":[108],"data":[109,115],"sets.":[110],"We":[111],"will":[112,198,247],"show":[113],"private":[118],"sector":[119],"made":[120],"us":[121,265],"learn":[122],"important":[123],"lessons":[125],"such":[126],"as":[127],"parks":[129],"can":[130],"become":[131],"more":[132],"secure":[133],"went":[136],"out":[137],"play":[139],"Pokemon":[140],"Go,":[141],"are":[145],"hubs":[146],"inclusion,":[149],"gender":[151],"segregates":[152],"city":[154],"demographics":[158],"keep":[159],"themselves":[160],"own":[163],"informational":[164],"filter":[165],"bubble.":[166],"However,":[167],"even":[168],"all":[170],"benefits,":[172],"relationship":[174],"industry":[176],"never":[178],"fluid,":[180],"involves":[182],"lot":[184],"small":[186,190],"not":[188],"so":[189],"compromises":[191],"\"battles\".":[193],"In":[194],"talk,":[196],"I":[197,246],"present":[199],"technical":[201],"history":[202],"we've":[206],"X/CDRs":[209],"good":[212],"including":[213],"practical":[214],"aspects":[215],"accessing":[217],"sharing":[219],"data,":[220,276],"balance":[222],"research":[224,262],"industrial":[226],"innovation,":[227],"issues":[229],"transactions":[231],"costs":[232],"while":[233],"still":[234],"providing":[235],"value":[236],"company":[239,257],"itself,":[240],"government,":[241],"university":[243,263,284],"society.":[245],"also":[248],"recount":[249],"experiences":[250],"about":[251],"what":[252],"it":[253],"meant":[254],"travel":[267],"together":[268],"very":[271],"interesting":[272],"context":[273],"huge":[275],"incredible":[277],"insights,":[278],"privacy":[279],"considerations,":[280],"money,":[281],"corporate":[282],"interests,":[283],"expectations,":[285],"data-driven":[287],"discovery.":[288]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}