{"id":"https://openalex.org/W2898424934","doi":"https://doi.org/10.1109/asonam.2018.8508257","title":"Content-Aware Tweet Location Inference Using Quadtree Spatial Partitioning and Jaccard-Cosine Word Embedding","display_name":"Content-Aware Tweet Location Inference Using Quadtree Spatial Partitioning and Jaccard-Cosine Word Embedding","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2898424934","doi":"https://doi.org/10.1109/asonam.2018.8508257","mag":"2898424934"},"language":"en","primary_location":{"id":"doi:10.1109/asonam.2018.8508257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2018.8508257","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2401.08506","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047025794","display_name":"Oluwaseun Ajao","orcid":"https://orcid.org/0000-0002-6606-6569"},"institutions":[{"id":"https://openalex.org/I71422933","display_name":"Sheffield Hallam University","ror":"https://ror.org/019wt1929","country_code":"GB","type":"education","lineage":["https://openalex.org/I71422933"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Oluwaseun Ajao","raw_affiliation_strings":["Sheffield Hallam University, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Sheffield Hallam University, United Kingdom","institution_ids":["https://openalex.org/I71422933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088113932","display_name":"Deepayan Bhowmik","orcid":"https://orcid.org/0000-0003-1762-1578"},"institutions":[{"id":"https://openalex.org/I12093191","display_name":"University of Stirling","ror":"https://ror.org/045wgfr59","country_code":"GB","type":"education","lineage":["https://openalex.org/I12093191"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Deepayan Bhowmik","raw_affiliation_strings":["University of Stirling, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of Stirling, United Kingdom","institution_ids":["https://openalex.org/I12093191"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049717843","display_name":"Shahrzad Zargari","orcid":"https://orcid.org/0000-0001-6511-7646"},"institutions":[{"id":"https://openalex.org/I71422933","display_name":"Sheffield Hallam University","ror":"https://ror.org/019wt1929","country_code":"GB","type":"education","lineage":["https://openalex.org/I71422933"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shahrzad Zargari","raw_affiliation_strings":["Sheffield Hallam University, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Sheffield Hallam University, United Kingdom","institution_ids":["https://openalex.org/I71422933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5047025794"],"corresponding_institution_ids":["https://openalex.org/I71422933"],"apc_list":null,"apc_paid":null,"fwci":2.083,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.89839737,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"68","issue":null,"first_page":"1116","last_page":"1123"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10757","display_name":"Geographic Information Systems Studies","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"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/T10757","display_name":"Geographic Information Systems Studies","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9918000102043152,"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/T11106","display_name":"Data Management and Algorithms","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/jaccard-index","display_name":"Jaccard index","score":0.7863055467605591},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7657980918884277},{"id":"https://openalex.org/keywords/quadtree","display_name":"Quadtree","score":0.6700242757797241},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5529270768165588},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5520902276039124},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.5487349033355713},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.47662508487701416},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4707750976085663},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4629019498825073},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.442928284406662},{"id":"https://openalex.org/keywords/geotagging","display_name":"Geotagging","score":0.4332359731197357},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4205435812473297},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4190242290496826},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3340781331062317},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3097083568572998},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12280532717704773},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11456534266471863}],"concepts":[{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.7863055467605591},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7657980918884277},{"id":"https://openalex.org/C151416825","wikidata":"https://www.wikidata.org/wiki/Q934791","display_name":"Quadtree","level":2,"score":0.6700242757797241},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5529270768165588},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5520902276039124},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.5487349033355713},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.47662508487701416},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4707750976085663},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4629019498825073},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.442928284406662},{"id":"https://openalex.org/C53605480","wikidata":"https://www.wikidata.org/wiki/Q852595","display_name":"Geotagging","level":2,"score":0.4332359731197357},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4205435812473297},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4190242290496826},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3340781331062317},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3097083568572998},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12280532717704773},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11456534266471863},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/asonam.2018.8508257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2018.8508257","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-article"},{"id":"pmh:oai:e-space.mmu.ac.uk:633977","is_oa":false,"landing_page_url":"https://e-space.mmu.ac.uk/view/authors/c79fea4bff67715a0b0890d0811999cf.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4306401617","display_name":"e-space (Manchester Metropolitan University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11983389","host_organization_name":"Manchester Metropolitan University","host_organization_lineage":["https://openalex.org/I11983389"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:shura.shu.ac.uk:23724","is_oa":false,"landing_page_url":"http://orcid.org/0000-0003-1762-1578>","pdf_url":null,"source":{"id":"https://openalex.org/S4306401600","display_name":"SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I71422933","host_organization_name":"Sheffield Hallam University","host_organization_lineage":["https://openalex.org/I71422933"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"PeerReviewed"},{"id":"pmh:oai:arXiv.org:2401.08506","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.08506","pdf_url":"https://arxiv.org/pdf/2401.08506","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},{"id":"pmh:oai:dspace.stir.ac.uk:1893/28144","is_oa":false,"landing_page_url":"http://hdl.handle.net/1893/28144","pdf_url":null,"source":{"id":"https://openalex.org/S4306400268","display_name":"Stirling Online Research Repository (University of Stirling)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I12093191","host_organization_name":"University of Stirling","host_organization_lineage":["https://openalex.org/I12093191"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2401.08506","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2401.08506","pdf_url":"https://arxiv.org/pdf/2401.08506","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2898424934.pdf","grobid_xml":"https://content.openalex.org/works/W2898424934.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W50479354","https://openalex.org/W100415715","https://openalex.org/W195533127","https://openalex.org/W564800084","https://openalex.org/W772778685","https://openalex.org/W1532325895","https://openalex.org/W1980867644","https://openalex.org/W1989134410","https://openalex.org/W1994286274","https://openalex.org/W2006239241","https://openalex.org/W2007791237","https://openalex.org/W2018277822","https://openalex.org/W2021278340","https://openalex.org/W2067219739","https://openalex.org/W2093588201","https://openalex.org/W2123294561","https://openalex.org/W2131049870","https://openalex.org/W2137435333","https://openalex.org/W2141854027","https://openalex.org/W2142191319","https://openalex.org/W2142889507","https://openalex.org/W2153579005","https://openalex.org/W2165442870","https://openalex.org/W2167521368","https://openalex.org/W2188871609","https://openalex.org/W2250539671","https://openalex.org/W2282112529","https://openalex.org/W2296740734","https://openalex.org/W2345018813","https://openalex.org/W2759710598","https://openalex.org/W2810047920","https://openalex.org/W3012723716","https://openalex.org/W3103872969","https://openalex.org/W4213009331","https://openalex.org/W4285719527","https://openalex.org/W4294170691","https://openalex.org/W6601987534","https://openalex.org/W6604108467","https://openalex.org/W6607976765","https://openalex.org/W6680314648","https://openalex.org/W6681249963","https://openalex.org/W6682691769","https://openalex.org/W6684253257","https://openalex.org/W6687031031","https://openalex.org/W6744750916","https://openalex.org/W6775238447"],"related_works":["https://openalex.org/W4381948805","https://openalex.org/W4214483597","https://openalex.org/W4388145912","https://openalex.org/W1437580529","https://openalex.org/W2307895033","https://openalex.org/W3048951355","https://openalex.org/W4313532769","https://openalex.org/W3215923396","https://openalex.org/W4286850906","https://openalex.org/W3096938301"],"abstract_inverted_index":{"Inferring":[0],"locations":[1,138],"from":[2,29,103],"user":[3],"texts":[4],"on":[5,150],"social":[6,68],"media":[7,69],"platforms":[8],"is":[9,93],"a":[10,21,140],"non-trivial":[11],"and":[12,47,51,59,75,82,109,122,143],"challenging":[13],"problem":[14],"relating":[15],"to":[16,72,99,132],"public":[17],"safety.":[18],"We":[19,62],"propose":[20],"novel":[22],"non-uniform":[23],"grid-based":[24,125],"approach":[25,92],"for":[26,44,55,77],"location":[27,101,127],"inference":[28,102,128],"Twitter":[30,64],"messages":[31],"using":[32,105],"Quadtree":[33,106],"spatial":[34,107],"partitions.":[35],"The":[36,115],"proposed":[37,116],"algorithm":[38,117],"uses":[39],"natural":[40],"language":[41],"processing":[42],"(NLP)":[43],"semantic":[45],"understanding":[46],"incorporates":[48],"Cosine":[49],"similarity":[50,53],"Jaccard":[52],"measures":[54],"feature":[56],"vector":[57],"extraction":[58],"dimensionality":[60],"reduction.":[61],"chose":[63],"as":[65],"our":[66],"experimental":[67],"platform":[70],"due":[71],"its":[73,97],"popularity":[74],"effectiveness":[76],"the":[78,89,94],"dissemination":[79],"of":[80,96],"news":[81],"stories":[83],"about":[84],"recent":[85],"events":[86],"happening":[87],"around":[88],"world.":[90],"Our":[91],"first":[95],"kind":[98],"make":[100],"tweets":[104],"partitions":[108],"NLP,":[110],"in":[111,134,146],"hybrid":[112],"word-vector":[113],"representations.":[114],"achieved":[118],"significant":[119],"classification":[120],"accuracy":[121],"outperformed":[123],"state-of-the-art":[124],"content-only":[126],"methods":[129],"by":[130,144],"up":[131],"24%":[133],"correctly":[135],"predicting":[136],"tweet":[137],"within":[139],"161km":[141],"radius":[142],"300km":[145],"median":[147],"error":[148],"distance":[149],"benchmark":[151],"datasets.":[152]},"counts_by_year":[{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}