22-25 September Mexico City

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1 Integrating GIS and Textual Data Mining to Create Security Intelligence Latin America Geospatial Forum September Mexico City César A. Cisneros Puebla Professor at Department of Sociology. UAM Iztapalapa. México Director of Qualitative Computing Consultancy, México

2 Collaboration with Arturo Arango Durán Iberoamerican Society of Crime and Security Analyst (SIADS in Spanish) Public Security in Mexico (http://www.seguridadpublicaenmexico.org.mx/) Proximity police, communicty police, police intelligence, criminal cartography, human rights, solve problems oriented policies, situational management of delinquency.

3 Outline: I. Introductiontothecollaboration: needsand questions II. Exemplarprojects: CrimeIncidence and Video Surveillance III. Obstacles and challenges

4 I. Introductiontothecollaboration: needsand questions

5 Crimeanalysis Identifying trends, patterns and series

6 Examples

7 5 primaryattributesforanalysis: time, space, behaviour, agressorand victim

8 DASHBOARD CONTROL PANEL: CRIME INCIDENCE

9 DASHBOARD CONTROL: NUEVO LEÓN

10 II. Exemplarprojects: Crime Incidenceand Video Surveillance

11 The first project on crime incidence is based on an imported Excel file with 62,864 cases and 29 variables, including geographical coordinates. The focus on such project in on the brief police or public prosecutor reports on such number of cases. Mexico City.

12 Variables: month, week, day, hour, type of act, impact type, modality, date, time, streets, neighborhood, municipality, geographicalcoordinates, victimsand so on.

13 The Landscape of Text Analysis Tools Qualitative Analysis Atlas.ti, Nvivo, MaxQDA, Qualrus, Ethnograph, HyperResearch, QDA Miner Content Analysis General Inquirer, Diction, LIWC, Tabari, TextQuest, TextPack, Yoshikoder, WordStat Text Mining Alceste, Clarabridge, SAS Text Miner, Catpac, Leximancer, T-Lab, Lexiquest, WordStat

14 THREE TYPES OF TEXT ANALYSIS QUALITATIVE ANALYSIS QUANTITATIVE CONTENT ANALYSIS TEXT MINING METHOD Manual reading and coding of documents Dictionaries of words, phrases, patterns, rules Statistical analysis and data mining techniques TIME REQUIREMENT Very High (weeks / months) Medium (days) Decreasing Low (seconds / minutes) VALIDITY Potentially High (high subjectivity) Medium to High Medium to High (sometimes low) RELIABILITY (REPEATABILITY) May be problematic Perfect Perfect (most of the time) SOME SOFTWARE Atlas.ti, Nvivo, MaxQDA, Qualrus, Ethnograph, HyperResearch QDA Miner General Inquirer, Diction, LIWC, Tabari, TextQuest, TextPack, Yoshikoder, WordStat Catpac, AutoMap, T-Lab Leximancer, Semio, Alceste, Clarabridge, SAS Text Miner, SPSS Lexiquest, WordStat

15 Text miningusingqdaminer+ WordStat Coding scheme by meaningful keywords: Actions: «withviolence», «withno violence», «sexual» (vagina, vaginal, sexual, penis), «byhitting», «moral violence», «physical violence». Weapons: «gun», «knifes». Stolen objects: «car», «mobile phone», wallet Accusergenre: «male», «man», «female», «women»

16 «Moral violence» bymunicipality

17 Municipality: Magdalena Contreras. ELEMENTOS S.S.P., PRESENTARON ANTE ESTE M.P., A CUATRO SUJETOS DEL SEXO MASCULINO, UNO DE ELLOS MENOR DE EDAD (16 AÑOS), POR EL DELITO ANTES SEÑALADO EN AGRAVIO DE DOS USUARIOS DE MICROBUS DEL SEXO MASCULINO, DE 24 Y 45 AÑOS, QUIENES REFIRIERON QUE EL DIA 4 DE OCTUBRE, A LAS 17:00 HORAS, CIRCULABAN EN UN MICROBUS Y AL LLEGAR AL LUGAR DE LOS HECHOS, SUBIERON CUATRO SUJETOS QUIENES POR MEDIO DE LA VIOLENCIA MORAL FINGIENDO ESTAR ARMADOS, LES DESAPODERARON DE SUS PERTENENCIAS, PERCATANDOSE DE LA PRESENCIA DE LOS PREVENTIVOS, SOLICITANDOLES EL APOYO,QUIENES LOS ASEGURARON. MONTO INDETERMINADO.

18 «Moral violence» byfelony

19 «Moral violence», «Physicalviolence» and «Moral and Physicalviolence» byfelony

20 The second project on video surveillance has 55,817 cases and 53 variables. Our focus is on the comments the policemen wrote in each case. Such project uses text mining to find patterns as well as the third one that has 97,834 cases and 52 variables and is also on video surveillance but belongs to other level of city video surveillance. Both projects include also geographical coordinates. I am focusing once again on the comments the policemen has written describing the situation. More than 14 thousand video cameras around the city.

21

22

23 Observing

24 Suspiciousattitudeorperson

25 Reportonsuspicious

26 Monitoringand civicculture

27 Reportonmonitoring

28 Informal market

29 Phrasesbymunicipality

30 Zoom in oneof them

31 III. Obstaclesand challenges

32 Control panels

33 Databases and Google Earth

34 Integratinggeographicalcoordinatesintotextual data mining Using GIS software and textual analytics in the big data arena is a very promising new frontier in applied social sciences Security Intelligence demanding new approaches and integral solutions Interoperability as a computational limits for new developments

35 Thanksa lotforyourattention!

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