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Quantifying Cultural Histories via Person Networks in Wikipedia

Doron Goldfarb1,2,3, Dieter Merkl3, Maximilian Schich1,2 1 School of Arts, Technology, and Emerging Communication The University of Texas at Dallas, TX, USA

2 Edith O’Donnell Institute of Art History The University of Texas at Dallas, TX, USA

3 Institute of Software Technology and Interactive Systems Vienna University of Technology, Austria [email protected] [email protected] [email protected]

1 Introduction

At least since Priestley’s 1765 Chart of Biography [1], large numbers of individual person records have been used to illustrate aggregate patterns of cultural history. Wikidata [2], the structured database sister of Wikipedia, currently contains about 2.7 million explicit person records, across all language versions of the encyclopedia. These individuals, notable according to Wikipedia editing criteria, are connected via millions of hyperlinks between their respective Wikipedia arti- cles. This situation provides us with the chance to go beyond the illustration of an idiosyncratic subset of individuals, as in the case of Priestly.

In this work we summarize the overlap of nationalities and occupations, based on their co- occurrence in Wikidata individuals. We construct networks of co-occurring nationalities and occupations, provide insights into their respective community structure, and apply the results to select and color chronologically structured subsets of a large network of individuals, con- nected by Wikipedia hyperlinks. While the imagined communities [3] of nationality are much more discrete in terms of co-occurrence than occupations, our quantifications reveal the exist- arXiv:1506.06580v1 [cs.SI] 22 Jun 2015 ing overlap of nationality as much less clear-cut than in case of occupational domains. Our work contributes to a growing body of research using biographies of notable persons to analyze cultural processes [4]- [9]

2 Method

In our processing pipeline (cf. Figure 1), we use the Wikidata Toolkit [10] to extract 2.7 million records about humans (instances of class Q5), in the form of person – property – value triples, from a downloaded Wikidata json dump (09/02/2015). We focus on the properties country of cit- izenship (P27) and occupation (P106) (numbers see Table 1A), restricting our analysis to nation- alities with at least 10 and occupations with at least 100 occurrences. We construct and project

1 the bipartite person-value affiliation matrices to uni-partite matrices of value-co-occurrence. To identify relevant co-occurrences, of nationalities or occupations respectively, the projected ma- trices are compared against a null model. Applying an established approach [11] [12], we derive expected co-occurrence weights from an ensemble of 10,000 degree-preserving random affiliation matrices. Co-occurrences with positive Pearson residuals are considered for further analysis (numbers see Table 1B).

The resulting co-occurrence networks, with residuals as edge weights, are subsequently examined for community structure using the Louvain method [13] [14]. Detecting communities at different granularities, we perform modularity optimization at different resolutions [15], resulting in mul- tiple partitions with varying numbers of communities. Using these partitions we can replace the plain co-occurrence weights in the original value-matrices with the probabilities of two values mutually co-occurring in the same community. The resulting mutual community matrix (Fig- ures 2 and 3) is then hierarchically clustered, with the resulting tree cut into a preset number of clusters (Figures 4 and 5). The preset number – 28 for nationalities, and 24 for occupations – is based on visual inspection of repeated clusterings.

Visualizations of the backbones of the co-occurrence networks (Figures 6 and 7) show the result- ing community structure in context. The network backbones are created by iteratively adding edges with the largest residuals until the maximal giant connected components (GCC) of the original networks are restored. For comparison, we plot the occurrence of nationalities and occupations over time, ordered by their first occurrence while disregarding outliers in terms of ordering (Figures 8 and 9).

Next, the clusters of nationalities and occupations are used to partition Wikipedia biographies into national community and domain specific sub-sets. Hyperlinks connecting Wikipedia arti- cles about individuals are obtained from DBpedia [16] and filtered to approximate contemporary relationships by excluding links between individuals with birth dates more than 75 years apart. Using hyperlinks from the English Wikipedia, we visualize the giant connected component of the partition of individuals connected to occupations in the community of ”arts, architecture, crafts, and design” (Figure 10). Colored by nationality cluster (cf. Figures 2,4,6), the visualiza- tion connects 22,825 nodes with 78,447 edges. We also visualize the giant connected component of the partition of individuals connected to nationalities in the community of ”predominantly English speaking countries” (Figure 11). Colored by occupational domain (cf. Figures 3,5,7) the visualization connects 160,913 nodes with 1,004,415 edges. While the arts domain (Figure 10) seems to reflect the established narrative of art history where a sequence of nationalities dominates at different points of time, the predominantly English speaking partition (Figure 11) is clearly characterized by a more complex structure that excludes the construction of a simple narrative.

2 3 Conclusion

In sum, we characterize networks of co-occurring nationalities and occupations related to Wiki- data individuals. Our quantifications indicate that communities of nations derived from co- occurrence are much more complex than the rather clear-cut communities of occupational do- . This may be due to substantially more complex social processes leading to co-citizenship, as we observe in (post)colonial ties, due to the potentially vague concept of citizenship/nationality itself [3], as found in references to bygone and transient national constructs, or due to the con- siderable difference in the amount of available data (93,661 citizenship vs. 585,407 occupation co-references). Our approach can be used to group synonyms and attributions of differing gran- ularity, occurring due to the free nature of Wikidata.

Algorithmically mining occupational domains from a large set of individuals, we create an al- ternative to manually curated meta-domains of occupation, as used in multiple strains of recent research [5] [8]. Deriving domain specific groups of individuals directly from a crowd-sourced ecosystem, such as Wikipedia, we also provide a useful alternative (Figure 10) to using expert curated datasets, such as the Getty Union List of Artist Names [17] as used to analyze the domain of art history in previous work [9]. Visualizing the Wikipedia hyperlink sub-networks of such domain specific groups of individuals reveals network patterns that would be obscured when using the network as a whole.

3 References [1] J. A. Priestley: Chart of Biography. (London: J. Johnson, 1765) [2] D. Vrandeˇci´c, M. Kr¨otzsch: Wikidata: A Free Collaborative Knowledgebase. Communica- tions of the ACM 57,10 (2014) 78-85 [3] B. R. O. G. Anderson: Imagined communities: Reflections on the origin and spread of nationalism. (London: Verso, 1991) [4] S. Ronen, B. Gon¸calves, K.Z. Hu, A. Vespignani, S. Pinker, C.A. Hidalgo: Links that speak: the global language network and its association with global fame. Proc. Natl. Acad. Sci. 111,52 (2014) E5616-E5622 [5] A. Z. Yu, S. Ronen, K. Hu, T. Lu, C. A. Hidalgo: Pantheon: A Dataset for the Study of Global Cultural Production. ArXiv preprint, arXiv:1502.07310v1 (2015) [6] M. Klein, P. Konieczny: Gender Gap Through Time and Space: A Journey Through Wikipedia Biographies and the ”WIGI” Index. ArXiv preprint, arXiv:1502.03086v1 (2015) [7] Y.-H. Eom, P. Aragon, D. Laniado, A. Kaltenbrunner, S. Gigna and D. L. Shepelyansky: Interactions of culture and top people of wikipedia from ranking 24 language editions. Plos ONE, (2014) [8] M. Schich, C. Song, Y.-Y. Ahn, A. Mirsky, M. Martino, A.-L. Barab´asi,D. Helbing: A network framework of cultural history. Science 345, 6196 (2014) 558-562 [9] D. Goldfarb, M. Arends, J. Froschauer, D. Merkl: Art History on Wikipedia, a Macroscopic Observation, Proceedings of the 3rd Annual ACM Web Science Conference, (2012) 163-168 [10] M. Kr¨otzsch, F. Erxleben, M. G¨unther, J. Mendez: Wikidata Toolkit: A Java library for working with Wikidata. http://korrekt.org/talks/2014/wikimania-wikidata-toolkit.pdf, accessed May 20th, 2015 [11] K. A. Zweig, M. Kaufmann: A systematic approach to the one-mode projection of bipartite graphs. Social Network Analysis and Mining 1,3 (2011) 187-218 [12] Y. Gu: Ein neues Empfehlungssystem mit FDSM-basierter einseitiger Projektion und Link Community Clustering. (Thesis: University, 2013) [13] V. D. Blondel, J.-L. Guillaume, R. Lambiotte, E. Lefebvre: Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment 2008,10 (2008) 10008 [14] V.A. Traag: Implementation of the Louvain algorithm for various methods for use with igraph in python. https://github.com/vtraag/louvain-igraph, accessed May 20th, 2015 [15] J. Reichardt, S. Bornholdt: Partitioning and modularity of graphs with arbitrary degree distribution. Physical Review E 76, 1 (2007) 015102 [16] S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, Z. Ives: DBpedia: A nucleus for a web of open data. Proceedings of the 6th International Semantic Web Conference (2007) 722-735 [17] Getty Vocabulary Program: Union List of Artist Names (The J. Paul Getty Trust, Los An- geles, 2010) http://www.getty.edu/research/tools/vocabularies/ulan/, accessed May 20th, 2015

4 Visualization of semantic co-occurrences

Network Backbone

Repeated Extraction Triples Table Fixed Degree community detection Hierarchical of person to tables to bipartite alue 1 alue 2 alue 3 alue 4 alue 5 Sequence Model at dierent

. v . v . v . v . v clustering tt r tt r tt r tt r tt r properties matrix A A A A A comparison Person 1 1 0 1 0 0 resolutions

Person 2 0 1 0 0 0

Person 3 0 1 0 1 0

Person 4 0 0 1 0 0

Person 5 0 0 0 1 1

Person 6 1 1 0 0 0 JSON Dump Triples Person to A liation Residual Mutual community Community Occupation/Citizenship Matrix Matrix Matrix structure

Wikidata / DBpedia ID mapping

Basic node information / Hyperlinks Wikidata / DBpedia hybrid attribute / hyperlink Visualization of Wikipedia dataset hyperlink network

Figure 1: Data processing pipeline

Table 1: Person links to Nation/Occupation (A) and Nation/Occupation Co-occurrences (B) Nationalities Occupations A #persons #P27 links #nationalities #persons #P106 links #occupations Raw data 1,318,484 1,366,777 833 1,363,032 1,706,766 3,419 Reduced data 1,317,676 1,365,600 282 1,352,909 1,685,000 431 1:1 References 1,271,939 1,271,939 282 1,099,593 1,099,593 431 1:n References 45,737 93,661 282 253,316 585,407 430 B #co-occurrences #nodes #co-occurrences #nodes All 2,100 282 13,846 430 Positive 1,565 282 7,641 430 Backbone 996 282 2,964 430

5 Figure 2: Louvain communities of co-occurring nationalities at different resolutions

Figure 3: Louvain communities of co-occurring occupations at different resolutions

6 Dutch Republic

Luxembourg Kingdom of the United Arab Emirates Netherlands

Southern Netherlands Burkina Faso Flanders Bahrain

Morocco Somalia Senegal

Kenya

Angola Poland Chad

Tunisia Vietnam Benin

Suriname Qatar Central African Republic Burundi Comoros Republic of the Congo Grenada Democratic Republic of the Congo Djibouti Switzerland Vanuatu Mali Cambodia East Germany Kingdom of France Moldova Romania Hungary Austria MonacoAlgeria Haiti Saint Lucia Seychelles Nigeria French Niger MadagascarMauritaniaFrance Rwanda Cote d'Ivoire Puerto Rico Canada Gabon England Guinea Scotland Great Britain JamaicaGhana Wales San Marino Northern Ireland Equatorial Guinea Ireland Vatican City Italy United States of America Namibia Congo Nauru Cameroon Philippines Malta LithuaniaLiberia Lesotho SouthLithuanian South Africa Australia Faroe Islands New Zealand Ecuador Tonga Samoa NorthPortugal Korea Fiji Burma British Empire Korea Mozambique Zimbabwe Guinea−BissauBrazil Botswana Trinidad and Tobago Cape Verde Barbados Taiwan NicaraguaMexico Indonesia Panama Singapore Uruguay Timor−Leste Bolivia India Colombia Saint Vincent and the Grenadines Paraguay Saint Kitts and Nevis Venezuela Kuwait Catalonia Laos Maldives Peru Malaysia Argentina Nepal Chile Pakistan Spain Sri Lanka Lübeck Thailand Andorra Bangladesh Cuba Tanzania Costa Rica United Kingdom of Great Britain and Ireland El Salvador Kingdom of Great Britain Kingdom of England Dominican Republic Abbasid caliphate Dominica Rashidun Caliphate Guatemala Umayyad Caliphate Honduras Zambia Ashikaga shogunate Transnistria Tajikistan Kyrgyzstan The Bahamas Ancient Ancient Egypt Byzantine Empire Uzbekistan Roman Republic Ancient Rome Byelorussian Soviet Socialist RepublicAbkhazia Roman Empire Kazakhstan Republic of Venice Ukrainian People's Republic Egypt Soviet GeorgiaRussia Ethiopia Gambia Ukraine Kingdom of Aksum Latvia Iceland Estonia Belarus Norway Russia Finland Tsardom of Russia Sweden Russian Soviet Federative Socialist RepublicSoviet Union Grand of Finland Eritrea Turkey Kosovo Russian RepublicGreece Slovenia Classical Athens Macedonia Armenia Croatia Cyprus Bosnia and Herzegovina Montenegro Ukrainian Soviet Socialist Republic Bulgaria Yugoslavia Serbia and Montenegro Yemen Macedonia Serbia Israel of Serbia Socialist Federal Republic of Yugoslavia Albania Kosovo North China German Confederation Confederation of the Rhine Hong Kong Weimar Republic Turkish Republic of Northern CyprusMandatory Palestine SudanLibya Nazi Germany Republic of China German Empire Kingdom of Syria Kingdom of South Sudan Kingdom of Prussia Electorate of Brunswick−L neburg of Lithuania PolishLithuanian Commonwealth Iraq Armenian Soviet Socialist Republic Iran Second Polish Republic SierraAfghanistan Leone Kingdom of LombardyVenetia Jordan Arab Lebanon Turkmenistan

Saudi Arabia Togo People's Republic of China Mongolia

Persian Empire Palestine Azerbaijan

Slovakia

Papal States

Czechoslovakia

Czech Republic

Austria−Hungary Kingdom of Naples

Republic of Florence

Kingdom of Bohemia

Figure 4: Hierarchical clustering of communities of co-occurring nationalities

7 landscape architect botanical illustrator graphic designer

copperplate engraver

draughtsman

comics artist

photographer

scenographer art director costume designer draughtsperson caricaturist affichiste illustrator Restaurator designer architect performance artist woodcarver engraver lithographer urban planner goldsmith potter mangaka

artist medalist television presenter choreographer ballet dancer cartoonist

illuminator club DJ choir director clarinetist violinist saxophonist disc jockey sculptor cellist musicologist conductor jazz musician oboist trumpeter banjoist television producer singer make−up artist animator painter record producer talent agent organ maker pornographic actor rapper matador vocalist opera singer child actor music executive churchcomposer musician sports commentator dancer drummer pianist singer−songwriter film editor bassist musician songwriter street artist film producer luthier organist bandleader seiyu guitarist news presenterscreenwriter sports journalist model rakugoka beauty pageant contestant professional wrestler program maker mixed martial artist radio host actor rikishi judoka puppeteer beach volleyball player cinematographerfilm director volleyball player television director dentist boxer comedian field hockey player voice actor tennis player swimmer baseball player ice hockey player cabaret artist badminton player golfer handball player lecturer handball coach announcermagician weightlifter artistic gymnast presenter fencer columnist archer television actor table tennis player film actor taekwondo athlete radio DJ canoer gridiron football player diver dramaturgeintendantblogger squash player contributingtheatre director editor sport shooter curler director water polo player lacrosse player radio producer futsal player reporter baseball umpire war correspondent darts player journalist pesaepallo player film critic bandy player calligrapher goalkeeper referee sportsperson typographerprinter head coach basketball player musicpublisher critic coach basketball coach lyricist association football manager impresario association football referee Esperantist association football player long−distance runner librettist athletics competitor novelist middle−distance runner children's writerfaculty marathon runner poet javelin thrower sprinter (short−distance runner) literaryauthor critic surfer bobsledder publicist luger woman ofart letters critic skeleton racer Australian−rules footballer cricketer translatorwriter rugby player playwright rugby union player autobiographer rugby league player troubadour Gaelic football player netballer literary cricket umpire specialisttheatre in literature critic Nordic combined skier ski jumper publicist cross−country skier short story writer biathlete lexicographer freestyle skier linguist alpine skier philologist musher essayist cultural historian chansonnier military historian economic historian salon−holder regional historian Lady−in−waiting historian of the Middle Ages literary historian historian of modern age editor librarian general officer numismatist politician historian barrister legal historian archivist soldier architectural historian magistrate egyptologist Member of the Legislative Assemblylawyer prehistorian art historian statesman archaeologist anthropologist civil servant canon diplomat abbot rancher muhaddith high−ranking civil servant in Francejurist theologian civil law notary canon minister judge political commissarsenator hagiographer admiral church historian farmer clergy lobbyist Vicar spy missionary Catholic priest ambassador bishop priest emperorNobile preacher cardinal military personnelking archbishop condottiero Catholic bishop monk sovereignbanker presbyter parson inventor watchmaker physicist businesspersonstockbrokermanager astronomer merchant mathematician chief executive officerfinancier historian of mathematics topologist art dealer statistician astrophysicist civil engineer manufacturer audio engineer philanthropistpolo player cryptographer aerospace engineer art collectormidwifenurse metallurgist mining engineer entrepreneurjockey programmer engineer computer scientist police officer rally driver equestrian Formula One driver test pilot racecar driver aviator NASCAR team owner horse trainer motorcycle racer fighter pilotofficerchef racing driver cook member of parliament astronaut educationist medical historian teacher teacher classical philologist philosopher scientist ufologist educator restaurateur rabbi figure skater activist accountant chemist sailor agronomist economist geopolitician epidemiologist political scientist meteorologist criminologist pharmacistprofessor sociologist docent biologist university professor go player chess player surgeon poker player snooker player bridge player draughts player neurologist chess composer pharmacologist rower speed skater neurosurgeon physician track cyclist cyclo−cross cyclist bicycle racer motivational speaker geneticist ethnologist explorer cartographer oceanographer geographer mountain guide gardener mountaineer winemaker horticulturist biochemist ornithologist neuroscientist nutritionist

psychologistpsychiatrist veterinarian oncologist virologist curator

medical writer anatomist botanist geologist zoologist psychotherapist cardiologist immunologist beekeeper naturalist

physiologist bryologist bioinformatician mycologist

speleologist entomologist

pteridologist mineralogist ophthalmologist molecular biologistmilitary physician

paleontologist

Figure 5: Hierarchical clustering of communities of co-occurring occupations

8 Burma Kingdom of England British Empire Kingdom of Great Britain United Kingdom of Great Britain and Ireland Zimbabwe Nauru Lesotho Malawi Botswana Uganda

South Africa Tonga Wales Samoa Fiji Northern Ireland New Zealand Macedonia Trinidad and Tobago Scotland Barbados Serbia and Montenegro Great Britain Serbia England Bosnia and Herzegovina United Kingdom Socialist Federal Republic of Yugoslavia Ireland Montenegro Congo Australia Yugoslavia Kingdom of Yugoslavia Taiwan Singapore Kosovo Principality of Serbia Kuwait Slovenia Croatia Maldives South Sudan Kingdom of Serbia Kingdom of France Saint Kitts and Nevis Guyana Libya Macedonia Hong Kong German Empire Malta Pakistan Sierra Leone Sudan Saint Vincent and the Grenadines British Raj Electorate of Brunswick-L_neburg Republic of China Sri Lanka Kosovo Kingdom of Saxony Malaysia Bangladesh Cyprus Qing dynasty Canada Puerto Rico Thailand Tanzania People's Republic of China Mauritius Albania Prussia North German Confederation India Nepal Greece Bulgaria German Empire China Laos Indonesia Turkish Republic of Northern Cyprus West Germany German Confederation Jamaica Timor-Leste East Germany Weimar Republic Confederation of the Rhine Denmark Holy Roman Empire Saint Lucia Nazi Germany Lübeck Germany Empire of Japan Kingdom of Bohemia The Bahamas Haiti NigeriaUnited States of AmericaKingdom of Aksum Korea Kingdom of Hungary Austrian Empire Ashikaga shogunate Niger South Korea Eritrea Hungary Turkey Austria-Hungary Japan North Korea Philippines Ethiopia Slovakia Tokugawa shogunate Nicaragua Finland Kingdom of LombardyVenetia Grand Duchy of Tuscany Grand Duchy of Finland Kingdom of Italy Rwanda Mongolia Iceland Norway Ottoman Empire Czechoslovakia Ecuador Ghana Sweden Chile Gambia Dominican Republic Austria Czech Republic PolishLithuanian Commonwealth Vietnam Dominica Yemen Grand Duchy of Lithuania Argentina Liechtenstein Bolivia Switzerland San Marino Kingdom of Naples Paraguay Zambia Ukrainian People's Republic Namibia Republic of Florence Cuba Brazil Vatican City Italy Costa Rica Uruguay Egypt Estonia Second Polish Republic Mandatory Palestine Mexico Venezuela Somalia Poland Togo Republic of Venice El Salvador Armenian Soviet Socialist Republic Andorra Colombia Liberia Ancient Egypt Romania Peru Spain Faroe Islands Benin Byzantine Empire Ukrainian Soviet Socialist Republic Guatemala Catalonia Ancient Greece Israel Roman Empire Honduras Cameroon Ancient Rome Djibouti Roman Republic Panama Equatorial Guinea Jordan Armenia Comoros Iran Lithuanian Tsardom of Russia Portugal Qatar Iraq Lebanon Lithuania Mozambique Angola Bahrain Latvia Cape Verde Suriname Afghanistan Classical Athens Russian Empire Palestine Moldova Guinea-Bissau Chad Morocco Byelorussian Soviet Socialist Republic Syria Azerbaijan Democratic Republic of the Congo France Arab Belarus Republic of the Congo Netherlands Russian Soviet Federative Socialist Republic Belgium Saudi Arabia Ukraine Russian Republic Senegal Georgia Uzbekistan Soviet Russia Central African Republic Kingdom of Romania Soviet Union Algeria Monaco Persian Empire Flanders Gabon French Russia Mali Southern Netherlands Burkina Faso Dutch Republic Cote d'Ivoire Turkmenistan Tajikistan Tunisia United Arab Emirates Abkhazia Kazakhstan Kyrgyzstan Guinea Abbasid caliphate Transnistria Burundi Cambodia Umayyad Caliphate Vanuatu Rashidun Caliphate Madagascar Seychelles Grenada Kingdom of the Netherlands

Mauritania

Figure 6: Network of national overlap through co-occurrence, colored by community

9 afchiste cartoonist potter comics artist mangaka lithographer illustrator woodcarver caricaturist art director graphic designer copperplate engraver artistpainter illuminator bandleader choir director costume designer oboist animator conductor scenographer engraver saxophonisttrumpeter church musician sculptor draughtsman clarinetist cellist organist musicologist medalist jazz musician pianist lyricist director printer draughtsperson vocalist composer typographer intendant performance artist canon violinist music critic calligrapher archbishop guitarist puppeteer goldsmith canon musician flm editor chansonnier parson bishopcardinal singer-songwriter theatre director designer bassist street artistchoreographer Catholic bishop songwriter ballet dancer cinematographerdramaturgelibrettistphotographer botanical illustrator Catholic priest banjoist television director troubadour children's writer publisher Vicar drummer luthier flm director theatre critic pastor singer dancer television producerscreenwriter publicist art critic monk abbot matador opera singer flm producer poetspecialist in literature hagiographer rapper television actor playwright literary flm actor literary critic minister presbyter voice actor radio producer flm critic short story writer editor preacher priest comedian impresario translator lexicographer theologian club DJ publicist disc jockey philologist cabaret artist essayist clergy child actor record produceractor novelist linguist librarian church historian music executive make-up artist writer magicianwar correspondent architect columnist urban planner literary historian seiyu program maker numismatist radio DJ art dealer cultural historian missionary beauty pageant contestantradio host woman of letters Restauratorjournalist landscape architect historian archivist model television presenterorgan maker faculty architectural historian regional historian presenter educator art historian announcer talent agent reporter author muhaddithhistorian of the Middle Ages news presenter Lady-in-waiting rabbi historian of modern age salon-holder teacher egyptologist autobiographer military historian archaeologist blogger lecturer Esperantist pornographic actor classical philologist economic historian prehistorian chef educationist teacher philosopher anthropologist rakugoka cook art collector activist legal historian ufologist emperor surfer contributing editor political scientist accountant sociologist curator restaurateur ethnologist sports commentator chess composer sailor barrister docent geopolitician watchmaker merchant cartographer professional wrestler condottiero mountaineer horticulturist gardener chess player philanthropist magistrate speleologist manager economist rikishi audio engineer general ofcer mountain guide member of parliament diplomat poker player fnancier statesman diver Nobile jurist geographer banker ambassador political commissar university professorprofessor polo player entrepreneurmilitary personnel civil law notary criminologist mixed martial artist civil servant judoka canoer businessperson civil engineer judge winemaker medical historian bridge player go player spy lawyer historian of mathematics chief executive opoliticianfcer farmer explorer manufacturer paleontologist motivational speaker programmer high-ranking civil servant in France sports journalist Member of the Legislative Assembly water polo player engineer lobbyist psychotherapist geologist pteridologist stockbroker soldier admiral horse trainer police ofcer rancher fgure skater psychologist botanist draughts player equestrian mining engineer agronomist naturalist mycologist boxer mathematician mineralogist bryologist referee swimmer jockey aerospace engineer cryptographer astronomer oceanographer table tennis player snooker player rally driver inventor senator meteorologist ornithologist computer scientist topologist beekeeper entomologist association football referee squash player statistician psychiatrist baseball playercoach badminton player Formula One driver metallurgist astrophysicist zoologist feld hockey player racing driver ofcer physicist association footballartistic gymnast player NASCAR team owner test pilot neurologist baseball umpire lacrosse player motorcycle racer ophthalmologist astronaut midwife scientist ice hockey player basketball coachhead coachtennis player racecar driver aviator nurse physician Gaelic football player fghter pilot bioinformatician futsal playerbasketball player golfer pharmacist surgeon anatomist association football manager gridiron football playerAustralian-rules footballer biologist bandy player sportsperson rugby league player dentist chemist pharmacologist goalkeeper netballer rugby union playercricketer epidemiologistneuroscientist handball player pesaepallo player rugby player veterinarian neurosurgeon geneticist handball coach darts player weightlifter cricket umpire cardiologistbiochemist molecular biologist volleyball player archer freestyle skier sport shooter medical writer beach volleyball player fencer cyclo-cross cyclist musher military physician physiologist sprinter (short-distance runner) taekwondo athlete lugeralpine skier bicycle racer nutritionist virologist javelin thrower bobsledder curler immunologist middle-distance runner skeleton racer track cyclist athletics competitor ski jumper speed skater oncologist long-distance runner biathlete marathon runner Nordic combined skier cross-country skier rower

Figure 7: Network of co-occurring occupations, colored by community

10 Figure 8: Nationalities over time based on person life-spans

11 Figure 9: Occupations over time based on person life-spans

12 Figure 10: Hyperlink network of English Wikipedia biographies having occupations in ”arts, architecture, crafts and design”, colored by nationality community corresponding to the colors in figures 2,4,6

13 Figure 11: Hyperlink network of English Wikipedia biographies with a nationality in the ”pre- dominantly english speaking” community, colored by occupation community corresponding to the colors in figures 3,5,7

14