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NAMSOR DEEP LEARNING FOR MIGRATION ANALYTICS : DECRYPTING IDENTITY IN SPACE AND TIME THROUGH PERSONAL NAMES, GEOGRAPHIC, SEMANTIC, SOCIAL GRAPH

2018-01 Elian CARSENAT, NamSor Founder Bio

2 Elian CARSENAT, a computer scientist trained at ENSIIE/INRIA, started his career at JP Morgan in Paris in 1997. He later worked as consultant and managed business & IT projects in London, Paris, Moscow and Shanghai.

In 2012, Elian created NamSor, a piece of sociolinguistics software to mine the 'Big Data' and better understand international flows of money, ideas and people.

http://fr.linkedin.com/in/eliancarsenat/en NamSor sorts Names

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 Classification with various taxonomies

 Gender (female/ male / unknown)

 Script (LATIN, ARABIC, GUJARATI,...)

 Origine (Country ex. France vs. Inde)

 Region (ex. Gujarat vs. Andhra Pradesh)

 Diaspora (ex. Indian Diaspora in US vs Indian Diaspora in Mauricius)  Sorting according to a numerical score, allowing combining NamSor with other algorithm (graph, semantics, predictive …)

 Flexibility to learn new taxonomies (machine learn.)

 Ease of integration (NamSor API, Java/Python SDK, ESRI, RapidMiner, NationBuilder …) A global coverage -142+ countries

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DIMENSION CURRENT COVERAGE SCRIPT (22) LATIN, ARABIC, CYRILLIC, ARMENIAN, BENGALI, DEVANAGARI, GEORGIAN, GREEK, GUJARATI, GURMUKHI, HAN, HANGUL, HEBREW, HIRAGANA, KANNADA, KATAKANA, MALAYALAM, MYANMAR, ORIYA, TAMIL, TELUGU, THAI

COUNTRY (142+) AE, AF, AL, AM, AO, AR, AT, AZ, BA, BD, BE, BF, BG, BH, BI, BJ, BN, BR, BT, BW, BY, CA, CD, CF, CG, CH, CI, CL, CM, CN, CO, CR, CV, CY, CZ, DE, DK, DZ, EE, EG, ER, ES, ET, FI, FJ, FR, GA, GB, GE, GH, GM, GN, GR, HK, HR, HT, HU, ID, IE, IL, IN, IQ, IR, IS, IT, JO, JP, KE, KG, KH, KM, KP, KR, KW, KZ, LA, LB, LK, LR, LS, LT, LU, LV, LY, MA, MD, ME, MG, MK, ML, MM, MN, MR, MU, MV, MW, MX, MY, MZ, NA, NE, NG, NL, NO, NP, OM, PE, PH, PK, PL, PS, PT, QA, RO, RS, RU, RW, SA, SD, SE, SI, SK, SN, SO, SR, SY, TD, TG, TH, TJ, TM, TN, TO, TR, TT, TW, TZ, UA, UG, US, UZ, VE, VN, YE, ZA, ZM, ZW COUNTRY/ RU (80), IN (~30), FR (22), IT (17), LB (14), BF (13), CD (8), TR (7), ID (7), GB (4), ES REGION (15) (17), ML (50), GN (8), CI (34), AF(16)

COUNTRY/ US, CA, SG, GB, (EU) DIASPORA NamSor can enrich any nominative data

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Data Mining/ Predictive analytics Watch Lists/ Social Networks 1.Classifica- 2.Translitera- Anti-Fraud/ tion & Counter-Terrorism tion Identification Geo-demographics/ GEOINT

NamSor 3. Named Entity Extraction

Indexing & Text Mining Two complementary approaches

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NamSor CORE (Origin, Diaspora) NamSor ML

 Optimized for global  Deep-learning capability to coverage : coding names to a re-train models towards a large multi-class taxonomy focused research or a (all countries / regions customized taxonomy (binary /ethnicities) classifier, or just a few classes)

 The only input is NAMES :  Name information is not other information is combined with other data required (geographic, behavioural, semantic …) NamSor Core : Mapping Tunisian Diaspora NamSor ML : Native Hawaiian Names - A Binary Classifier Example

8 Multi-cultural names : NHawaiian, Filipino, Japanese, Anglo-Saxon … MITCHELL KEANULUAIKALANI KALUHIWA SHANNON LOKAHI YURONG ESTOCADO DUSTIN MASAO KEOLA IWABUCHI …

Nov 20, 2017 9:49:39 AM com.namsor.namsorml.us_hi.MLPNamSorHawaiiTrainer main INFO: Examples labeled as 0 classified by model as 0: 21857 times Examples labeled as 0 classified by model as 1: 7731 times Examples labeled as 1 classified by model as 0: 2194 times Examples labeled as 1 classified by model as 1: 221318 times

======Scores======# of classes: 2 Accuracy: 0.9608 Precision: 0.9375 Recall: 0.8644 F1 Score: 0.9781 ======Nov 20, 2017 9:49:39 AM com.namsor.namsorml.us_hi.MLPNamSorHawaiiTrainer main INFO: ****************Example finished******************** 9

 NamSor use cases Mining 3M twitter names to map Diasporas Who are they, where are they and what are they doing? 10

Source: Twitter Visualization : CartoDB Data Mining:Source: NamSor Twitter Flow view – who travels where?

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Source Target Type Id Onoma Weight United Kingdom France Directed 16 Great Britain 37 Spain France Directed 55 Spain 14 United States France Directed 75 Great Britain 12 Turkey France Directed 79 Turkey 11 Brazil France Directed 87 Portugal 10 United Kingdom France Directed 112 Ireland 9 Italy France Directed 152 Italy 7 Switzerland France Directed 226 France 5 Belgium France Directed 247 France 5 United Kingdom France Directed 258 France 5 Mexico France Directed 287 Spain 4 Ireland France Directed 317 Great Britain 4 United Kingdom France Directed 333 Italy 4 United States France Directed 375 France 4

Source: Twitter Visualization : Gephi Data Mining: NamSor Mapping Talents in Cancer Research (in collaboration with French INSERM)

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Thomson Reuters WebOfScience (6 countries, 250k scientists, 50k papers) “Analysts uncovered amazing patterns in the way scientists’ names correlate with whom they publish, and who they cite in their papers - not just in case of a particular country, but globally. Tania Vichnevskaia of the French National Institute for Health (INSERM) presented the paper ‘Applying onomastics to scientometrics‘ at IREG International symposium 2015 organised by University of Maribor and Shanghai Jiao Tong University. The paper was prepared jointly with NamSor, a private start-up company specialized in mapping international Diasporas.” Source: WoS; Data Mining: INSERM with NamSor Cancer Research in Poland and Slovenia Examining the ‘brain drain’

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In the Polish Corpus, we look at co- In the Slovenian Corpus, we look at co- authors with Polish names, affiliated authors with Slovenian names, abroad. affiliated abroad.

Top countries: Top countries: 1. US, 1. Great-Britain, 2. Great-Britain, 2. US, 3. Germany. 3. Germany. Source: WoS; Data Mining: INSERM with NamSor “Incredible India” – 1.2 BN People Indian onomastics by State/Union Territory 14 Names in LATIN, BENGALI, DEVANAGARI, GUJARATI, GURMUKHI, KANNADA, MALAYALAM, ORIYA, TAMIL, TELUGU, ARABIC ASSAM: Karbi Anglong, within district Inter-caste marriages ? 15

output Input Input ASSAM: Karbi Anlong district names clustered L116370:3612 clusterId clusterParentId Firstname LastName parent is FirstParentLastParent L23643:669 L151415:3559 L47490:1593 L25354:253L64958:2797 A¡à[\ ¹ ¹}[ššã husband ¤àl¡ü[W¡³ [W¡}>๠L28582:1209 L54332:2031 L184096:2297 L47490:1593L64958:2797 father L168871:1819 ¤àK[¹ [W¡}>๠¤àl¡ü[W¡³ [W¡}>๠L9839:442 L135664:4438 L28582:1209L47490:1593 husband L87032:1210 [³>à Òü}[t¡šã ¤àK[¹ [W¡}>๠L90333:3644 L35593:510 L23643:669L35593:510 father L51271:837 ™åKƒ}à [W¡}>๚㠤ài¡[W¡³ [W¡}>๠L63724:1422 L154797:1168 L23643:669L35593:510 father L64959:1796 ³à>àÒü [W¡}>๚㠤ài¡[W¡³ [W¡}>๠L23642:141 L87031:697 L6536:295 L47490:1593L35593:510 W¡àì=¢ [W¡}>๠father Wå¡ì¤ [W¡}>๠L98994:891 L25354:253 L64958:2797 L23643:669L35593:510 A¡àì¹ t¡àì¹ïšã husband Wå¡ì¤ [W¡}>๠L30570:2614 L90334:1189 L95839:287 L35593:510L47490:1593 [ƒ[º š [W¡}>๠father W¡àì¤ [W¡}>๠L100510:366 L121390:783 L23643:669L47490:1593 [¹>à [W¡}>๚ã father W¡àì¤ [W¡}>๠Other parent is husband

Count of se ria l Column La be ls Row La be ls L47490:1593 L116370:3612 L54332:2031 L184096:2297 L35593:510 L168871:1819 L135664:4438 L51271:837 L23643:669 6931 84 5099 15 2069 28 791 1924 L151415:3559 18 212 11 6446 19 1217 55 6 L28582:1209 5132 68 3565 10 1494 17 592 1323 L116370:3612 66 10283 38 72 40 321 137 29 L9839:442 2491 60 1851 9 774 11 321 660 L168871:1819 7 263 6 361 8 2730 24 4 L23642:141 1198 8 822 2 375 4 156 332 L25354:253 1181 12 932 375 7 100 323 L135664:4438 20 154 5 22 19 44 2212 3 L87032:1210 11 315 13 51 14 141 37 9 L90333:3644 3 204 2 31 190 5 L184096:2297 13 1735 3 84 11 1 L87031:697 4 136 4 12 3 137 4 5 L14495:131 614 10 432 167 4 68 163 L63724:1422 17 83 10 34 34 28 96 6 L98994:891 31 161 46 21 19 59 21 5 Source: Voters List; Data Mining: NamSor Boston geo-demographics 1/2

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Source: Boston Voters List ; Visualization : ESRI ; Data Mining: NamSor Boston geo-demographics 2/2

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Source: Boston Voters List Visualization : ESRI Data Mining: NamSor Breaking down ‘White’ and ‘Asian’ into Portuguese, Spanish, Italian, India, Pakistan, China, ...

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Source: Boston Voters List Visualization : ESRI Data Mining: NamSor PATENT DATABASES

19 US AID PROJECT

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seedname https://ca.linkedin.com/in/yuriy-diakunchak-6a3bb6[...]_-1035308383.linkedin Explanations datetime 2016-02-07T12:49+0000 dateextract 07/02/2016 linkedinurl https://ca.linkedin.com/in/yuriy-diakunchak-6a3bb61 LinkedIn URL and Profile data parentseed - fullname Yuriy Diakunchak - titlename Director of Marketing at Ukrainian Credit Union Limited - orgname Ukrainian Credit Union Limited - locality Toronto, Canada Area - languages English,Ukrainian, - connections 500+ connections - descriptor Toronto, Canada Area - profilesummary Summary Experienced marketing manager. Focused on branding and brand management, executing programs and campaigns targeted at building brand- exposure. More recently, have been immersing myself in various aspects of on-line and social media marketing and Google AdWord marketing. Learning a lot about how to improve both the number and quality of visitors to our web site as well as how to tie it all back to our sales funnel. experience Experience Director of Marketing Ukrainian Credit Union Limited August 2010 – Present (5 years 7 months) Heading up the marketing department. Reporting- to the COO Manager, Web and Creative Services Platform Computing October 2009 – July 2010 (10 months) Manage team consisting of web master and graphic designer as well as contractors supplying design, writing and multi-media services. the team develops and produces marketing collateral, web content and implements online marketing initiatives including social media and Google advertising. Marketing Writer Platform Computing 2007 – April 2010 (3 years) Owner Creative Quotient Inc. April 2003 – November 2007 (4 years 8 months) Led a boutique design studio. Developed strategic branding and communications material for clients. Acted as chief evangelist and sales person. Manager, Public Relations / Manager Customer Relations Hummingbird Ltd. December 2000 – April 2003 (2 years 5 months) Marketing Writer Hummingbird July 2000 – April 2003 (2 years 10 months) First po organizations Organizations KUMF Art Gallery Director Starting March 2013 Member of Board of Directors of KUMF Art Gallery (Ukrainian Canadian Art Foundation),- currently responsible for member communications. Ukrainian Canadian Professional and Business Assocation - Toronto Branch Director Starting January 2014 UCPBA is an organization that brings together businesses and professionals of Ukrainian background in Toronto for various networking events including IT Networking, Small Business Networking and Student Mentorship/Networking. Ukrainian Canadian Social Services - Toronto Branch Director Starting March 2015 The organization provides services for immigrants, the elderly and those needing support in the community. volunteering Volunteer Experience & Causes Causes Yuriy cares about: Arts and Culture Civil Rights and Social Action Politics - projects - education Education M.M. Robinson McMaster University BComm, Marketing, Finance Pragmatic Marketing , Product Marketing Course Ryerson University Bachelor- of Journalism (Post-Graduate - Equivalent of MA), Journalism awards - skills Skills Product Management Marketing Automation Brand Management Product Marketing Demand Generation Multi-channel Marketing Marketing SEO- Social Media Marketing Program Management Competitive Analysis Analytics Corporate Communications Cloud Computing Leadership See 9+ Public Relations Strategy Social Media Team Leadership Management Online Marketing Strategic Planning Marketing Strategy Advertising See less recommandations Recommendations A preview of what LinkedIn members have to say about Yuriy: I had the pleasure of working with Yuriy since 2006 on various video- projects for Ukrainian Credit Union and Platform Computing. Yuriy is very professional, fair, clear in communicating his ideas and always enjoyable to work with. I strongly recommend Yuriy to anyone who needs a capable, creative and experienced marketing professional.See moreSee less I had the pleasure of working with Yuriy for the past 2 years. He developed several piece of content for partner marketing. He was quick, efficient, creative and had a complete understanding of the technology which is quite complex. He never hesitated to roll up his sleeves to get a job done. It is an asset to any organization.See moreSee lessSign up to see who recommended Yuriy groups Groups Markian Silecky Real Estate - Babiak Team Royal LePage Real Estate Services Ltd, Brokerage Cloud Computing Taxonomy & Information Management- John4Ward3 Marketing And Research: Need of the hour UCPBA Toronto View Yuriy’s full profile to... See who you know in common Get introduced Contact Yuriy directlyView Yuriy's Full Profile publications - score 2.368793324 < how much Ukrainian the nams sounds count 7 < how many Ukrainian connections (max :10) titlename2 0 orgname3 0 locality2 0 languages3 1 < Ukrainian appears in Languages connections4 0 descriptor5 0 profilesummary6 0 experience7 1 organizations8 0 volunteering9 0 projects10 1 education11 0 awards12 0 skills13 0 recommandations14 0 groups15 1 < Ukraine appears in Goups publications16 0 TOT 13.98341639 < Overall score taking into account factors from L26-43 Indian diaspora names - a global airline use case

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Liberia - a regional onomastics 'mille-feuille' Thank you !

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Elian CARSENAT, [email protected] Phone : +33 6 52 77 99 07

Juillet 2013, Ambassade de Lituanie à Paris