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Urban data: harnessing subjective sociocultural data from local newspapers

Mello Rose, Filipe,Chang, Juiwen

Abstract

As data-based governance becomes mainstream, social and cultural interactions that characterise urban life are at risk of being ignored in decision-making practices if only supposedly objective, quantifiable data are used. In this context, this article conceptualises subjective sociocultural data as a data form that considers a city’s intangible and unquantifiable social and cultural aspects. A methodology is proposed for collecting and using subjective sociocultural data by highlighting local press articles as a potential data source. A pilot application conducted in Hamburg, Germany, demonstrates a potential integration of subjective sociocultural data into urban planning processes by analysing over 2500 local newspaper articles. The findings reveal that local journalism can be a data source for understanding diverse social and cultural interactions between citizens and urban places. This street-level information from local newspaper articles can (1) provide urban planners with an overview of newspaper mentions of any specific urban areas, (2) support the identification of local debates, and (3) aid in the observation of emerging places of sociocultural interactions. This approach can support the diverse government and non-government stakeholders engaged in data-based governance to better account for intangible sociocultural aspects of urban life.

Full text

SPECIAL COLLECTION: DATA POLITICS IN THE BUILT ENVIRONMENT RESEARCH CORRESPONDING AUTHOR: Filipe Mello Rose Digi al Ci y Science, Ha enCi y Uni e si y Hambu g, Hambu g, DE; Labo a o y o Knowledge A chi ec u e, Technical Uni e si y D esden, D esden, DE [email p o ec ed] KEYWORDS: ci ies; da a-based go e nance; da a poli ics; da a ica ion; local jou nalism; planning; sociocul u al da a; subjec i e da a; u ban da a; u ban go e nance TO CITE THIS ARTICLE: Mello Rose, F., & Chang, J. (2023). U ban da a: ha nessing subjec i e sociocul u al da a om local newspape s. Buildings and Ci ies, 4(1), pp. 369–385. DOI: h ps://doi.o g/10.5334/bc.300 U ban da a: ha nessing subjec i e sociocul u al da a om local newspape s FILIPE MELLO ROSE JUIWEN CHANG ABSTRACT As da a-based go e nance becomes mains eam, social and cul u al in e ac ions ha cha ac e ise u ban li e a e a isk o being igno ed in decision-making p ac ices i only supposedly objec i e, quan i iable da a a e used. In his con ex , his a icle concep ualises subjec i e sociocul u al da a as a da a o m ha conside s a ci y’s in angible and unquan i iable social and cul u al aspec s. A me hodology is p oposed o collec ing and using subjec i e sociocul u al da a by highligh ing local p ess a icles as a po en ial da a sou ce. A pilo applica ion conduc ed in Hambu g, Ge many, demons a es a po en ial in eg a ion o subjec i e sociocul u al da a in o u ban planning p ocesses by analysing o e 2500 local newspape a icles. The indings e eal ha local jou nalism can be a da a sou ce o unde s anding di e se social and cul u al in e ac ions be ween ci izens and u ban places. This s ee -le el in o ma ion om local newspape a icles can (1) p o ide u ban planne s wi h an o e iew o newspape men ions o any speci ic u ban a eas, (2) suppo he iden i ica ion o local deba es, and (3) aid in he obse a ion o eme ging places o sociocul u al in e ac ions. This app oach can suppo he di e se go e nmen and non-go e nmen s akeholde s engaged in da a-based go e nance o be e accoun o in angible sociocul u al aspec s o u ban li e. PRACTICE RELEVANCE This esea ch suppo s go e nance ac o s in dealing wi h he epis emological limi a ions o pu posely ga he ed and/o objec i e da a by concep ualising a new—cu en ly un apped—da a ype: subjec i e sociocul u al da a sou ced om local jou nalism. By using geog aphical ex analysis on local newspape a icles, u ban planne s and decision-make s gain access o a weal h o s ee -le el in o ma ion, local deba es and empo al dynamics o u ban issues. This app oach p o ides a comp ehensi e unde s anding o in angible and unquan i iable aspec s o u ban li e, allowing o mo e in o med and con ex -sensi i e decision-making. The p ac ical bene i s include iden i ying di e se uses o u ban spaces, cap u ing local public deba es, and acking he eme gence and disappea ance o places in he public sphe e, possibly leading o mo e e ec i e and inclusi e u ban planning p ac ices. *Au ho a ilia ions can be ound in he back ma e o his a icle 370Mello Rose and Chang Buildings and Ci ies DOI: 10.5334/bc.300 1. INTRODUCTION: BETTER DATA FOR URBAN GOVERNANCE Many new ends in u ban planning, such as algo i hmic go e nance, sma ci ies and digi al wins, es on da a-based u ban go e nance. In his ype o u ban go e nance, ‘a complex sys em o ac o s, ela ionships, p ocesses, and echnologies’ is designed o decide on u ban issues based on di e se se s o a ailable and analysable da a (Ma ei e al. 2020: 124). Da a-based planning is a c ucial ins umen o add essing he upcoming en i onmen al and socie al challenges (Ba y & Yang 2022: 146) as i allows comp ehensi e and in e disciplina y analyses o complex p oblems by making hem ‘mo e “legible” o go e ning’ (Mejias & Could y 2019: 4). A he same ime, he da a ica ion o u ban go e nance aises a ious issues conce ning da a alidi y, as well as he eliabili y, ep esen a i eness and in e ope abili y o a ailable da a (Bunde s & Va ó 2019). C ucially, da a-based u ban go e nance is limi ed by all u ban p oblems no being ‘equally knowable and sol able’ by da a-based go e nance p ac ices (Bunde s & Va ó 2019). Many key in angible and unquan i iable aspec s o u ban li e (e.g. he ole o amily-owned co ne shops in a local neighbou hood) play a i al ole in he day- o-day u ban expe iences o ci izens (Jacobs 1961/1992). Likewise, u ban places such as pa ks o pa emen s ‘mean no hing di o ced om hei p ac ical, angible uses’ (Jacobs 1961/1992: 111). This in o ma ion is ha dly quan i iable and is hus igno ed in da a-based go e nance. These limi a ions o da a-based go e nance can a leas be mi iga ed by including b oade and mo e a iega ed da ase s (Ba y 2019). In his sense, he p esen a icle concep ualises subjec i e sociocul u al da a as an impo an ye equen ly igno ed o unde used inpu o da a-based go e nance. Wi h his concep ualisa ion and an exempla pilo me hodology, he aim o his pape is o suppo he di e se s akeholde s engaged in da a-based go e nance (including go e nmen and non-go e nmen ac o s) o be e accoun o in angible and unquan i iable aspec s o u ban li e in hei decision-making. Subjec i e da a a e a pa icula da a o m ha explici ly in ol es human judgmen in i s collec ion. Sociocul u al da a depic aspec s ‘ ela ed o he di e en g oups o people in socie y and hei habi s, adi ions, and belie s’ (Camb idge Uni e si y P ess n.d.). Join ly, subjec i e sociocul u al u ban da a depic sel - epo ed and e alua ed accoun s o a ci y’s social and cul u al p ac ices (i.e. he in e ac ions o ming a ci y’s social and cul u al ab ic). In pu suing he esea ch goal o b oadening he da a sou ces o u ban go e nance, his a icle concep ualises he u ili y o subjec i e sociocul u al u ban da a and p oposes a me hodology o collec ing and using his da a ype. This concep ualisa ion and me hodology es on a c i ical e iew o he li e a u e on he di e en ypes o da a used in u ban go e nance and a syn hesis o concep ual discussions on subjec i e da a. Mo eo e , local p ess a icles we e iden i ied as a po en ial and la gely un apped sou ce o subjec i e sociocul u al u ban da a, which, once geo- e e enced and syn hesised, can in o m local go e nance decisions. Empi ically, his s udy e lec s on a pilo s udy ha aims o in eg a e subjec i e sociocul u al da a in o u ban planning by d awing on a esea ch p ojec ca ied ou wi h he s a e-owned company o eal es a e managemen and land asse s o he Ge man ci y o Hambu g: he Landesbe ieb Immobilienmanagemen und G und e mögen Hambu g (LIG). The pilo s udy de eloped a geo- pa sing module wi h subjec i e sociocul u al da a ha aims o complemen ‘objec i e’ da a used in decision-making ega ding public eal es a e policies. This s udy d aws on da a om 2539 local newspape a icles om Hambu g published online be ween 2018 and 2022. The a icles we e au oma ically analysed o spa ial e e ences in Hambu g (i.e. geo-pa sed and geocoded) and clus e ed a ound 10 algo i hmically gene a ed opics. The pilo use cases show ha local jou nalism can (1) p o ide u ban planne s wi h an o e iew o newspape men ions o any speci ic u ban a eas, (2) suppo he iden i ica ion o local deba es, and (3) aid in he obse a ion o eme ging places o sociocul u al in e ac ions. In concep ualising local p ess a icles as a sou ce o subjec i e sociocul u al u ban da a o u ban go e nance, his s udy d aws on and con ibu es o esea ch on da a ica ion p ocesses in go e nance. Howe e , as ‘da a ica ion is c oss-disciplina y in na u e’ (Lombo g e al. 2020), his s udy also d aws on mul iple academic ields. Fi s , i d aws on media s udies o a gue o he gene al u ili y o (local) jou nalism as a da a sou ce o he da a-based go e nance (Ba is ini e 371Mello Rose and Chang Buildings and Ci ies DOI: 10.5334/bc.300 al. 2013; Sa ın & Uluğ ekin 2019). Second, i d aws on digi al na u al language p ocessing (NLP) me hods o geog aphical ex analysis and opic modelling (Cai 2021; Middle on e al. 2018; Po e e al. 2015). This a icle is s uc u ed as ollows. Following his in oduc ion, he pape concep ualises and si ua es subjec i e sociocul u al da a among o he u ban da a o ms used o u ban planning. The me hodology is hen desc ibed and he esul s o an empi ical pilo applica ion a e epo ed. This empi ical sec ion se s ou he NLP me hods and h ee po en ial use cases o he ou lined echniques. The las sec ion e iews and discusses he use o subjec i e sociocul u al da a o u ban go e nance. 2. EXPLICITLY SUBJECTIVE DATA FOR DATA-BASED GOVERNANCE 2.1 FROM GOVERNMENT DATA TO DATA-BASED GOVERNANCE In con as o he adi ional go e nmen s’ use o sel -collec ed da a, da a-based go e nance d aws on a a ie y o da a sou ces. These ange om ou comes o algo i hms and he In e ne o Things (Cole a & Ki chin 2017), as well as la ge da ase s, dashboa ds o su eillance sys ems o c ea e a mo e e icien adminis a ion and go e nance o places (Bunde s & Va ó 2019; Ki chin & McA dle 2017; Valdez e al. 2018; Zubo 2019). Mo eo e , wi h he inc easing p e alence o sou ces in da a-based go e nance, many s akeholde s a e able and needed o p o ide o analyse da a. Mos no ably, in e na ional pla o m co po a ions now also in o m decision-making and policy de elopmen wi h hei da ase s and analy ical ools (e.g. Re be g 2020). Along wi h nume ous o he ac o s, his da a ica ion has hus u he ad anced he shi om adi ional go e nmen o go e nance by beyond- he-s a e ‘ho izon al associa ional ne wo ks o p i a e (ma ke ), ci il socie y […] and s a e ac o s’ (Swyngedouw 2005: 1992). Da a-based go e nance, hus, coo dina es his ‘beyond- he-s a e go e ning’ a angemen by p o iding and analysing signi ican and di e se da ase s. This da a ica ion imp o es he capaci y o an icipa o y planning in a go e nance sys em ha includes an e e g ea e a ie y o ac o s (beyond adi ional go e nmen adminis a ions) by using da a ‘ o e olu ionize he p ocess o policy analysis’ (Ma ei e al. 2020: 124). While da a- based go e nance can hus ep esen new business oppo uni ies o companies collec ing da a as a by-p oduc (e.g. Re be g 2020), i can also allow esea che s o ci il socie y o ganisa ions o pu go e nmen s and co po a ions unde g ea e sc u iny (e.g. Dal on 2019). C ucially: da a ica ion enables us o deal wi h lines o inqui y ha we e di icul i no impossible o pu sue be o e. (Lombo g e al. 2020: 207) In his sense, da a-based go e nance can also os e a mo e collabo a i e and inclusi e app oach o go e nance, whe e a ne wo k o ac o s wo k oge he o iden i y and add ess complex socie al challenges. By p o iding and analysing da a ha a e o in e es o u ban go e nance, hese non- go e nmen ac o s hus, di ec ly o indi ec ly, engage in expanding ne wo ks o da a-based go e nance. 2.2 ONTOLOGY OF DATA SOURCES OF DATA-BASED GOVERNANCE Be o e digi alising public adminis a ion, economic and social ac i i ies, da a-based go e nance elied p ima ily on pu posely collec ed da a, such as s uc u ed su eys and obse a ion da a. This ype o da a sou ce includes da a delibe a ely p oduced by go e nmen ins i u ions (e.g. da a om census and s a is ics o ices) o non-go e nmen o ganisa ions suppo ing da a-based go e nance wi h hei da a. Fo ins ance, da a-based go e nance o en d aws on specialised su ey ins i u es o uni e si ies o collec da a wi h di e se o mal me hods (online su eys, in-pe son in e iews, online acking, e c.). A ai o hese pu posely collec ed da a o su ey- ype da a is, howe e , ha i s con olled collec ion p ocesses educe he da a’s ‘scope, empo ali y, and size, and a e qui e in lexible in hei adminis a ion and gene a ion’ (Ki chin & McA dle 2016: 2). 372Mello Rose and Chang Buildings and Ci ies DOI: 10.5334/bc.300 Digi alising social, economic and go e nmen al ac i i ies has enabled he collec ion o usable da a as a by-p oduc . As public adminis a ions become mo e digi ised, mo e da a a e p ocessed digi ally in go e nmen bu eauc acies and become a po en ial new da a sou ce (Ki chin & McA dle 2016). This ype o da a, which a e ga he ed as a by-p oduc , is ei he obse ed (i.e. as a esul o people using echnology) o in e ed (i.e. consolida ed in o ma ion om exis ing da a sou ces) (Taylo & Rich e 2015). Da a ha o igina e as a by-p oduc o go e nmen ac i i ies also include eco ds, such as budge s and spending da a, and da a on asse s as well as om egis ies (e.g. egis a ion o esidences, inancial ac i i ies o ehicles). C ucially, his da a sou ce ype is no limi ed o any ex-an e speci ica ion o pu pose in da a-based go e nance, as he possible knowledge gains a e de ined a e he da a a e collec ed du ing da a p epa a ion (Ki chin & McA dle 2016) (Table 1). All da a (sou ces) ha e na u al epis emological limi s. Pu posely collec ed da a a e limi ed o add essing socie al p oblems known be o e he da a collec ion based on scien i ic heo y (Ki chin 2014). While mos ly ee o sampling and s a is ical e o s, his da a ype has a low po en ial o ul il unan icipa ed usages (Ki chin & McA dle 2016). Uns uc u ed da a collec ed as a by-p oduc , in con as , a e p one o sampling and s a is ical e o s and biases o igina ing om unequal uses o a se ice o p oduc bu allow explo a o y esea ch. T adi ional da a sou ces in u ban go e nance gene ally elied on he accessibili y o pu posely collec ed da a, such as su eys and censuses. As pu posely collec ed da a equi e an ex-an e de ini ion o esea ch p oblems (i.e. be o e da a collec ion), da a-based go e nance mus also conside da a sou ces allowing g ea e explo a o y esea ch o iden i y new esea ch p oblems. 2.3 SUBJECTIVE AND SOCIOCULTURAL DATA Sociocul u al da a depic ‘socie y and hei habi s, adi ions, and belie s’ (Camb idge Uni e si y P ess n.d.). They ea u e s uc u ed and s a is ical cul u al, e hnic, eligious o demog aphic in o ma ion, as well as (mo e subjec i e) da a on cul u al p ac ices, day- o-day ac i i ies and ou ines, and belie s. In his a icle, sociocul u al da a a e essen ially da a ha allow one o unde s and be e a gi en a ea’s social and cul u al ab ic. Da a-based go e nance p ima ily d aws on supposedly ‘objec i e’ da a as impe sonal and neu al ‘ aw in o ma ion’ ha a e bes collec ed wi h he leas ‘subjec i e’ human in ol emen possible (Riede & Simon 2016). This applies o sociocul u al da a ha a e o en educed o a iables o e hnic, eligious o class iden i ica ion which can be assessed somewha objec i ely. Subjec i e da a, in con as , signi ican ly and explici ly in ol e human judgmen in i s p oduc ion. Despi e a g ea e isk o biases, his da a ype is used as pu posely collec ed da a o measu e social phenomena such as happiness, a ec ion o wellbeing (e.g. Kahneman & K uege 2006; Macků e al. 2020). Subjec i e measu es a e ele an o wo main easons. Fi s , in he absence o (mo e) objec i e measu es, subjec i e ones can (a leas pa ially) depic social phenomena on which da a a e sca ce. Second, subjec i e measu emen s allow one o: cap u e changes in bo h he explici and he implici componen s o he a iable being measu ed and, he e o e, […] can be be e sui ed o he s udy o b oadly de ined concep s. (Jahedi & Méndez 2014: 3) GOVERNMENT DATA NEW DATA-PRODUCERS IN DATA- BASED GOVERNANCE Pu posely collec ed da a (S uc u ed) Pe iodically collec ed da a on he poli y, e.g. census da a, su eys o s a is ics adminis a ions Da a om non-s a e da a collec ion companies and esea ch ins i u es, i.e. ma ke esea ch, uni e si y esea ch Da a as a collec ed as a by-p oduc (Uns uc u ed) Da a collec ed as a by-p oduc o go e nmen adminis a ions, e.g. pe mi da a, da a om public companies (i.e. heal h insu ance, unemploymen insu ance, public anspo ), budge da a Da a collec ed as a by-p oduc o o dina y economic and social ac i i ies, e.g. social media companies, a ge ed ad e isemen s, cus ome e iews Table 1: Concep ualisa ion o di e en da a sou ces and collec ion o ms. 373Mello Rose and Chang Buildings and Ci ies DOI: 10.5334/bc.300 Da a on he sociocul u al aspec s o u ban li e mee bo h easons o using subjec i e measu es. Fo one, sociocul u al ac o s o u ban li e o e ew al e na i e ‘objec i e’ measu es. Mos u ban in e ac ions and p ac ical, angible uses o places a e di icul o quan i y objec i ely wi hou using (some imes a - e ched) p oxy measu es. Fo ano he , he sociocul u al aspec s o u ban li e a e a b oadly de ined concep ha e e s o he in angible aspec s, such as he di e se social and cul u al in e ac ions en iching u ban li e. Allowing di e en ac o s o de e mine he ele an social and cul u al in e ac ions will likely be e depic he local u ban social and cul u al ab ic. Mo eo e , while s a is ical and sys ema ically quan i ied sociocul u al da a allow la ge-scale analyses, small- scale subjec i e da a can help planne s o be e unde s and he social condi ions shaping an a ea’s u ban (sociocul u al) ab ic. U ban sociocul u al da a depic day- o-day ac i i ies, ou ines, alues and public spaces’ p ac ical, angible uses. In his sense, his a icle unde s ands subjec i e sociocul u al da a as collec ions o desc ip ions o social in e ac ions and cul u al li e in an a ea. This includes accoun s o cul u al and ci ic e en s, he uses o public spaces, o popula meanings o places (e.g. he impo ance o adi ional co ne shops o ba s o a communi y) ele an o unde s anding he local u ban ab ic. Combining di e en ypes o da a sou ces allows o iangula ing in o ma ion and complemen ing analyses wi h di e en pe spec i es. In his sense, adding da a ga he ed as a by-p oduc o da a- based go e nance eases explo a o y, unexpec ed lines o enqui y, while subjec i e sociocul u al da a expand da a-based go e nance o be e accoun o a gi en a ea’s social and cul u al ab ic. 2.4 LOCAL JOURNALISM AS A DATA SOURCE FOR URBAN GOVERNANCE This s udy concep ualises and empi ically es s he use o local p ess a icles as a sou ce o subjec i e sociocul u al u ban da a. In doing so, i d aws on mul iple s udies in which p ess a icles se e as an explici ly subjec i e sou ce o geog aphical and sociocul u al da a. Fo ins ance, Voukela ou e al. (2021: 300) ind ha ‘news da a a e a new p omising da a sou ce o he u he explo a ion o subjec i e well-being’. Ba is ini e al. (2013: 157) use online news eeds as da a sou ces o e icien ly map geohaza ds (i.e. ea hquakes, landslides and loods) unde he assump ion ha whene e geohaza ds ha e ‘ ele an consequences, news is epo ed on he In e ne ’. G ego y & Pa e son (2020) elabo a e on his p ac ice unde he i le o geog aphical ex analysis, o which he schola s geo-pa se his o ical p ess a icles o map his o ical po e y in he UK. The schola s’ s udy on his o ical po e y demons a es how analysing ex ual da a can p o ide insigh s in o geog aphical pa e ns (G ego y & Pa e son 2020). Ozgun & B oekel (2021) use egional newspape s o enqui e abou he egional di e ence in a i udes o inno a ion by quan i ying he men ions and sen imen s o di e en egional newspape a icles. Howe e , while mos s udies ocus on he na ional o a leas egional le el, Pa e son (2020: 66) poin s ou ha : e e ences o place, especially a mo e local le els, can make he impac (s) o abs ac concep s […] appea mo e conc e e by si ua ing hem wi hin de inable geog aphical bounda ies. O he s udies ha e used simila me hodologies o mobilise social media da a o da a analysis in en i onmen al (Ghe mandi & Sinclai 2019) and ou ism esea ch (Chen e al. 2021). Howe e , in con as o social media da a, p ess a icles ha e a leas a minimal deg ee o quali y con ol. Mo eo e , while in e ac ions on social media a e highly di e se and equen ly use colloquial o g oup-speci ic language, newspape a icles a e ypically w i en o b oade audiences and equi e less con ex -speci ic language o knowledge abou he au ho s o be in elligible. In his spi i , applying geog aphical ex analysis o local p ess a icles appea s as an auspicious way o in oducing new sou ces o subjec i e sociocul u al da a o da a-based u ban go e nance. The use o newspape a icles as a sou ce o sociocul u al da a is g ounded on he assump ion ha he con en p oduced by newspape s a leas gene ally depic s cul u al p ac ices, day- o-day ac i i ies and ou ines, and belie s o a gi en place. The way media ou le s ‘ ame an issue shapes how people unde s and and emembe i ’ (Ozgun & B oekel 2021: 3). Mo eo e , media ou le s 374Mello Rose and Chang Buildings and Ci ies DOI: 10.5334/bc.300 ha e nes ed in e es s ha in luence hei aming and ca ego isa ions o wha is ‘newswo hy’. Howe e , while he p ess migh ad ance speci ic agendas, ‘ hey do no do so independen o hei audience’ (3). As mos media o ganisa ions a e comme cially d i en, he choice o newswo hiness and he one o epo ing news is s ongly linked wi h a emp s o gain and e ain he la ges possible audiences (Scheu ele 1999; Gen zkow & Shapi o 2010; Agi das 2015). As people seem o ‘selec i ely expose hemsel es o a i ude-consis en in o ma ion’ (Ea le & Hodson 2022: 9), aligning o he poli ical o ien a ion and epo ing p io i ies o a a ge eade ship is a comme cial necessi y and a esponse o public demand (Gen zkow & Shapi o 2010). While na ional news ou le s end o become inc easingly pa isan o win audience loyal y in a poli ically di ided ma ke (Gen zkow & Shapi o 2010), his is no he case o local newspape s due o hei limi ed geog aphic compe i ion (Agi das 2015). 3. EMPIRICAL PILOT APPLICATION: SOURCING LOCAL JOURNALISM FOR URBAN GOVERNANCE In he ollowing, his s udy desc ibes and discusses an empi ical pilo applica ion o he possible uses and sou ces o sociocul u al da a o da a-based go e nance concep ualised abo e. While his pilo applica ion has been de eloped in pa ne ship wi h a s a e-owned company o a speci ic case (i.e. o imp o e da a-based go e nance o public eal-es a e asse s), he me hodology (including he used algo i hms) is a ailable as open-sou ce code on Gi Hub. This way, he p ac ical implemen a ion o sou cing local jou nalism o u ban go e nance can be es ed and imp o ed in o he con ex s. 3.1 CONTEXT OF THE EMPIRICAL PILOT APPLICATION This s udy is si ua ed wi hin a b oade esea ch p ojec ha in es iga es new modes o da a-based planning conduc ed wi h Hambu g’s s a e-owned company o eal es a e managemen and land asse s, he LIG. The Ge man ci y o Hambu g is no excep ion o he end o da a ica ion o u ban go e nance, and he LIG aims o imp o e i s go e nance ac i i ies wi h new digi al ools o spa ial analysis. To de elop a me hod o digi al da a-based eal es a e and land managemen in he ci y-s a e, a collabo a ion be ween he LIG and Ha enCi y Uni e si y has engaged in he c ea ion o a digi al pla o m o he e alua ion o land pa cels. This pla o m will consolida e a ious da a sou ces and in o m decisions ega ding he acquisi ion and sale o land by public adminis a ions. Mo e p ecisely, he digi al ool allows he compa ison o land pa cels based on hei su oundings (i.e. he p oximi y o a ious u ban ameni ies) and hei connec i i y (i.e. isoch ones in he ci y) in he ‘LIG-Finde ’ module. In addi ion, he ‘geo-pa sing’ module p o ides a spa ial o e iew o geocoded ex s. This geo-pa sing module displays geocoded documen s om he s a e pa liamen and mul iple egional and local newspape s. This includes he Elbe Wochenbla , a hype local ee newspape ha his s udy uses as a pilo applica ion. Elbe Wochenbla is a hype local ad e isemen -based newspape om Hambu g. I s a icles a e dissemina ed online and in se en weekly neighbou hood-le el p in edi ions, dis ibu ed ee o cha ge o all households (unless hey op ou ) wi hin a speci ic deli e y zone (Figu e 1). As an ad e isemen -based newspape , i p o ides a pla o m o and depends on local businesses o ad e ise hei p oduc s and se ices. Elbe Wochenbla ea u es sho a icles using colloquial language on local poli ics, spo s, ci ic li e, cul u al e en s and businesses. Nex o Hambu ge Wochenbla , Elbe Wochenbla is he second la ges ee newspape in Hambu g wi h app oxima ely 300,000 weekly p in ed copies.1 Howe e , he media landscape in Hambu g is also—and p obably mo e subs an ially—shaped by egional and Hambu g-based na ional newspape s, such as MOPO/ BILD, Hambu ge Abendbla and Zei .2 Elbe Wochenbla ’s accessibili y and high olume o publica ions om 2018 o 2021 make i a aluable es case o he pilo applica ion o he LIG-Finde ’s geo-pa sing module. Du ing ha pe iod, he newspape was majo i i ely owned by Madsack Medieng uppe, wi h a mino i y s ake held by Funke Medieng uppe. In 2021, he newspape was ully acqui ed by Funke Medieng uppe, which in eg a ed he p e iously independen edi o ial o ice wi h o he local newspape s om 375Mello Rose and Chang Buildings and Ci ies DOI: 10.5334/bc.300 Hambu g (no ably wi h Hambu ge Wochenbla ) in Janua y 2023. While Madsack Medieng uppe is egionally ocused on no he n Ge many, Funke Medieng uppe is he 10 h la ges media g oup in Ge many (Ins i u ü Medien- und Kommunika ionspoli ik 2022). This s udy uses all 3511 newspape a icles published online (and in a leas one o he se en neighbou hood p in edi ions) om 2018 o 2021. The ime ame was selec ed due o he newspape ’s abo e-a e age publishing ac i i y. The ocus is on a icles au ho ed by he newspape ’s edi o ial s a o sa egua d a consis en o ma and ocus on he newspape ’s a ge a eas. This excludes submissions and commen a ies om eade s ha a y as ly in o ma , making an au oma ed co pus analysis di icul a his pilo ing s age. Elbe Wochenbla was selec ed o his pilo applica ion because o (1) i s hype local ocus and desc ip ions o neighbou hood li e in hei epo ing and (2) he a ailabili y o a la ge co pus o a icles. A he ime o da a collec ion, mos o he neighbou hood newspape s in Hambu g co e ed smalle a eas. In his sense, using local jou nalism as sociocul u al da a is exempli ied using Elbe Wochenbla as a pa adigma ic case (Fly bje g 2006: 232). This s udy does no aim o discuss he media p ac ices o he newspape beyond a necessa y con ex ualisa ion. 3.2 NATURAL LANGUAGE PROCESSING (NLP) OF LOCAL JOURNALISM As uns uc u ed da a and a by-p oduc o economic and social ac i i ies, local newspape a icles equi e signi ican and me iculous p epa a ion o p o ide angible bene i s o u ban decision- make s as sociocul u al da a. The p epa a ion and cu a ion o he uns uc u ed da a d aw on he p ac ices o he eme ging ield o NLP, ad ancing i s use in da a-based u ban go e nance (e.g. Cai 2021). NLP is an algo i hmically enabled analy ical p ac ice ha combines linguis ics, compu e science and a i icial in elligence o ‘s uc u e la ge olumes o uns uc u ed da a’ (Cai 2021: 1). This s udy uses wo p ima y me hods o NLP o ans o m uns uc u ed newspape da a in o a sou ce o subjec i e sociocul u al u ban da a: geo-pa sing and opic modelling. 3.2.1 Geo-pa sing The geo-pa sing p ocess allows he ex ac ion o loca ion names and coo dina es om he newspape a icles’ uns uc u ed ex ual da a. The ‘pa sing’ p ocess sepa a ed ex s in o a compu e - eadable o ma o de ec e ms ha can be linked o geog aphical iden i ie s. In o he wo ds, geo-pa sing in ol es wo subp ocesses ha i s ex ac loca ion iden i ie s (i.e. place names) and hen geocodes hem (Wang e al. 2020). Fi s , oponym ecogni ion and geo agging iden i y names o geog aphical loca ions in he ex based on name en i y ecogni ion. This ask loca es and classi ies ‘named en i ies’ in uns uc u ed ex in o p ede ined ca ego ies (e.g. pe son names, o ganisa ions, loca ions, ime exp essions, quan i ies, mone a y alues and pe cen ages). A e compa ing mul iple name en i y ecogni ion classi ica ion lib a ies, his s udy used spaCy, an open-sou ce so wa e lib a y a ailable o o e 70 languages.3 Second, his s udy uses Nomina im4—an open-sou ce geocode o con e place names in o geocoo dina es— o geocode he geog aphical en i ies iden i ied in he p e ious s ep. The algo i hm builds a s a is ical model es ima ing he p obabili y o a named en i y e e ing speci ic geoloca ed place (Middle on e al. 2018). En ies wi h a sco e below a p obabili y o 0.95 we e checked manually. The geocoding o he 3511 newspape a icles iden i ied 10,320 men ions o 1718 places in Hambu g. A e he geo-pa sing p ocess, he da abase o newspape a icles equi ed u he p epa a ion and da a cleaning. A signi ican po ion o place men ions e e s o en i ies linked o a eas ac oss mul iple neighbou hoods (i.e. dis ic s, egions o Hambu g as a whole). As hese place names a e somewha a bi a ily geocoded o a poin wi hin he a ea hey ep esen , hese place men ions clu e neighbou hood-le el analysis wi h in o ma ion ela ed o a eas ou side he neighbou hoods.5 Fo his eason, he s udy excludes all men ions o place names e e ing o geog aphical a eas abo e he neighbou hood le el. This s ep excludes 1665 men ions o ‘Hambu g’, 356 men ions o he gene al pa s o Hambu g (e.g. Wes Hambu g, Sou h Hambu g) and 845 men ions o one o he se en dis ic s. This il e ing educes he da abase o 7903 men ions o 1689 places. 376Mello Rose and Chang Buildings and Ci ies DOI: 10.5334/bc.300 Elbe Wochenbla is dis ibu ed in an a ea ha co e s he en i e wes and sou h o Hambu g, including 34 o 104 o icial neighbou hoods (Figu e 1). This a ea accoun s o 41% o Hambu g’s o al a ea and 35.3% o Hambu g’s popula ion. The neighbou hoods se iced by he newspape a e highly di e se ac oss a ious me ics anging om popula ion densi y o employmen . Fo ins ance, he a ea o deli e y includes he h ee weal hies and he h ee poo es neighbou hoods o he ci y. The geocoding con i ms he hype local ocus o he newspape ’s epo ing, as o e 89.5% o all place men ions in he da abase a e in he deli e y zone. Mo eo e , he as majo i y (2539 a icles, o 72.3%) o all 3511 analysed a icles men ion a leas one place ha can be loca ed wi hin a neighbou hood whe e he newspape ’s p in edi ion is deli e ed. The e o e, he ollowing s udy ocuses on he a eas in which he newspape ’s p in e sion is dis ibu ed. The ‘cleaned’ co pus o newspape a icles hus includes 2539 a icles men ioning 1424 di e en u ban places in he deli e y a ea a o al o 6665 imes. Tes s o he ex co pus and he pa sed and geocoded places indica e ha he numbe o imes places in each neighbou hood a e men ioned signi ican ly co ela es o ha neighbou hood’s popula ion (Pea son co ela ion = 0.667; p < 0.01) and a ea (Pea son co ela ion = 0.546; p < 0.01). No signi ican s a is ical ela ionship exis s be ween he numbe o place men ions in an a ea and he a ea’s median income, housing p ices o o he es ed socioeconomic ac o s (i.e. sha e o mig an s, sha e o highe educa ion deg ees). 3.2.2 Topic modelling Topic modelling is an impo an s ep in NLP ha allows he iden i ica ion o di e en opics and opic dis ibu ions in la ge co po a o ex . While he e a e se e al opic modelling me hods, he mos popula a e la en di ichle alloca ion (LDA) (Blei e al. 2003) and s uc u ed opic modelling (STM) (Robe s e al. 2019). The p ocess ollows he gene al p ocedu e o clus e ing co-occu ing lis s o keywo ds in o a p ede ined numbe o opics in he i s s ep wi hou needing any p elabelled da a. To imp o e he ce ain y o iden i ying he co ec opic, his s udy used bo h me hods o iden i y 10 opics (i.e. co-occu ing lis s o keywo ds) in he ex co pus o local newspape a icles. While bo h majo opic modelling me hods p oduce sensible esul s, a close analysis o he esul ing 10 keywo d lis s o ming each opic sugges ed he use o STM, as i allows he inclusion o addi ional Figu e 1: Spa ial dis ibu ion o he place men ions in he local newspape . 377Mello Rose and Chang Buildings and Ci ies DOI: 10.5334/bc.300 in o ma ion. In he case o his s udy, sen imen sco es ega ding he a icle’s s yle and one we e added o he analysis. These sen imen sco es es on ‘Tex BlobDE’6 and he ‘Valence Awa e Dic iona y and Sen imen Reasone ’.7 In he second s ep, he opic modelling algo i hm calcula es he likelihood o an indi idual a icle being linked o each o he 10 opics (i.e. ‘ opic sco e’). This analysis was based on he en i e y o each a icle. As he sum o he 10 opic sco es is equal o 1, he a icles ha ing a opic sco e > 0.5 (mo e han all o he nine opics combined) in any gi en opic a e conside ed o be signi ican ly ela ed o ha opic. A icles wi hou a opic sco e > 0.5 a e unde s ood no o be signi ican ly linked o any o he 10 opics (e.g. combining mul iple opics). Table 2 shows he opics iden i ied in he opic modelling, he numbe o a icles (wi h a espec i e opic sco e o a leas 0.5) and he numbe o places men ioned in a icles conce ned wi h ha opic. The numbe o place men ions a ies signi ican ly ac oss di e en opics. Fo example, while opic 1, ‘pandemic’, was he mos equen opic in he co pus, a icles clea ly linked o opic 4, ‘mobili y’, ha e he mos place men ions. Due o he high h eshold o be conside ed ela ed o a pa icula opic, abou 45% o a icles a e no linked o any opic. 3.3 EXEMPLAR USE CASES OF SOURCING LOCAL JOURNALISM FOR URBAN GOVERNANCE The ollowing h ee use cases illus a e how he applica ion o NLP o local newspape a icles can gene a e da a o be e comp ehend a gi en a ea’s social and cul u al ab ic. While he i s use case ocuses on geo-pa sing, he second demons a es he applica ion o opic modelling ID TOPIC LABEL ARTICLES PLACE MENTIONS KEYWORDS IN ORDER OF LIKELIHOOD (ROOT WORDS) 1 Pandemic 325 416 co ona; accine; i us; es ; pool; in ec ; cen e; o e ; hygiene; ship; ip; numbe ; mask; pandemic; dis ance 2 Heal h and social ca e 275 1,318 heal h; hospi al; help; also; ca e; wo k; homeless; employee; o ice; need; suppo ; se ice; cen e; con ac ; will 3 Mobili y 233 1,515 a ic; b idge; pa k; s a ion; ailway; cons uc ; ca ; oad; plan; s ee ; ee; esidence; wo k; a ea; can 4 Spo s 231 960 eam; club; spo ; game; league; will; oo ball; championship; playe ; play; ime; coach; goal; poin ; s a 5 Poli ics 223 638 dis ic ; g een; SPD; o ice; CDU; ci izen; membe ; elec ; ini ial; boa d; ede al; poli ic; associa ion; pa liamen ; le 6 Schools and educa ion 183 531 school; s uden ; child en; wo k; young; elemen a y; p ojec ; class; lesson; pa en ; eache ; educa e; dis ic ; young; lea n 7 Housing 151 391 build; new; plan; a ea; dis ic ; house; enan ; de elop; en ; apa men ; cen e; eu o; p ope y; cons uc ; o ice 8 Conce s and e en s 134 385 music; icke ; a is ; hea e; pe o m; s age; a is ; play; conce ; show; band; musician; ilm; choi 9 Po ai s o neighbou hood igu es 93 277 like; a he ; pho o; ime; wi e; iend; emembe ; e en; s ill; jus ; now; always; li e; wan ; know 10 Ci ic li e 79 234 es i al; museum; o’clock; child en; o e ; ca é; o gan; chu ch; e en ; open; ma ke ; cul u e; place; isi o ; ake 0No clea opic 1,588 2,671 Table 2: Resul s o he opic modelling. 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