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Covert network data: a typology of effects, processes, practices and structures

Covert network data: a typology of effects, processes, practices and structures. Kathryn Oliver, Gemma Edwards, Nick Crossley, Johan Koskinen, Martin Everett. Covert network project. 3 year project Aim to collect covert network data (freely available, in-house) Collate and test theories

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Covert network data: a typology of effects, processes, practices and structures

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  1. Covert network data: a typology of effects, processes, practices and structures Kathryn Oliver, Gemma Edwards, Nick Crossley, Johan Koskinen, Martin Everett

  2. Covert network project • 3 year project • Aim to collect covert network data (freely available, in-house) • Collate and test theories • Develop new metrics and theories • Thus far: • 200 hypotheses • 50 datasets (freely available)

  3. Application of SNA to secret networks • Secret communities amenable to study through relational methods • Data on communications, attendance at events, pre-existing ties often available • Focused primarily on criminal and terrorist networks • Concepts such as ‘resilience’, ‘disruption’, ‘capacity • Methodological work on boundary definition & missing data

  4. Covert populations Heroin users Clubbers Men who have sex with men Swingers Terrorists Clients of sex workers Youth gangs Illegal immigrants Corrupt policemen Criminals Persecuted Jews Online fraudsters Drug dealers Child pornographers People with infectious diseases Suffragettes Militants Ravers Freemasons Cyclists Armed robbers Child sex offenders

  5. Types of covert tie or ties in covert networks Knowing them Being related Exchanging money Being in the same gang Selling/buying sex or drugs Talking to Being arrested with Being abused by Sharing resources with (drugs, money, child porn etc) Committed fraud against Planning events with Being in the same place at the same time Communicating with Living near Sharing needles or sex partners Reporting to/managing Friends with Sexual contact Works with Migrated with Same genetic BBV Grassed on

  6. What do we know about covert networks? • Multiplicity of theories • But little consensus • Examples: density, centralisation

  7. Theories

  8. Covert networks are sparse Red indicates empirically tested Frame of reference? Compared with overt networks?

  9. Density

  10. Centralisation

  11. Centralisation Author’s interpretation

  12. What do we know about covert networks? • Multiplicity of theories • But little consensus • Examples: density, centralisation • Are comparisons valid? • Outstanding questions • test theories on empirical datasets • Explore differences – role of context, network aim, interaction type etc • Compare with overt networks of similar characteristics

  13. Types of covert networks Full-time activist Takes up most of ones life Goes to sex parties every once in a while Takes up little of ones life

  14. Types of covert networks Segregated from wider networks of whatever type of tie Takes up most of ones life Militant factions Freemasons part of business communities Takes up little of ones life Integrated into wider networks of whatever type of tie

  15. Types of covert networks Segregated from wider networks of whatever type of tie Takes up most of ones life Seeking out marital affair Tasked as suicide bomber Actions controlled by individuals Actions controlled by network Takes up little of ones life Integrated into wider networks of whatever type of tie

  16. Types of covert networks Segregated from wider networks of whatever type of tie Takes up most of ones life Getting high e.g. votes for women Individual aims Network aims Actions controlled by individuals Actions controlled by network Takes up little of ones life Integrated into wider networks of whatever type of tie

  17. Types of covert networks Segregated from wider networks of whatever type of tie Takes up most of ones life Individual aims Network aims Actions controlled by individuals Actions controlled by network Individual consequences Arrest of all union members Network consequences Being jailed Takes up little of ones life Integrated into wider networks of whatever type of tie

  18. Types of covert networks Segregated from wider networks of whatever type of tie Takes up most of ones life Individual aims Network aims Actions controlled by individuals Actions controlled by network Individual consequences Network consequences …Wherever you are on these axes affects network structure…. Takes up little of ones life Integrated into wider networks of whatever type of tie

  19. Types of covert networks Segregated from wider networks of whatever type of tie Takes up most of ones life e.g. Being in a closed order Individual aims Network aims Actions controlled by individuals Actions controlled by network Individual consequences Network consequences …Wherever you are on these axes affects network structure…. HOWEVER all of these are also factors affecting overt networks Takes up little of ones life Integrated into wider networks of whatever type of tie

  20. Therefore secrecy is the key characteristic of these networks

  21. Where might secrecy happen? • Covert aims (political, ideological, illegal) • Covert identities (mafia boss, spies) • Types of actions within covert network (e.g. communication) • etc

  22. Aim: to develop set of covertness variables and use to build hypotheses

  23. e.g. predicting centralisation And can compare with….

  24. Covert networks project@ Mitchell Centre • We aim to: • Collect covert network data and make freely available where possible • Compare and test theories • Develop concept of covertness as variable/set of variables? • Recruitment, segregation, formation, dissolution as qualitative case studies • Contact me: kathryn.oliver@manchester.ac.uk

  25. Thanks Mitchell Centre for Social Network Analysis http://www.ccsr.ac.uk/mitchell/

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