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Reality Mining Capturing Detailed Data on Human Networks  and  Mapping the Organizational Cognitive Infrastructure Nathan Eagle Digital Anthropology The MIT Media Lab February 21, 2003
From User to Group-Centric To unobtrusively glean a detailed map of an organization’s cognitive infrastructure Who influences results?  Who is helping whom?  Who are the gatekeepers?  Which people work well together? Where is the expert?  Who knows what?  Who should connect with whom?  How will communication change after the merger?   What is the optimum organizational structure?
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical
Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical Current Topic:  Structural Intergrity of the Widget  Expertise:  Mechanical ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Physical to Cognitive Infrastructure 20 th  Century Organization 21 st  Century Organization Physical Infrastructure Cognitive Infrastructure flexibility, adaptation, robustness, speed – guided and tied together by ideas, by their knowledge of themselves, and by what they do and can accomplish slowly changing environment – development of infrastructures to carry out well described processes.
Simulations vs. Surveys ,[object Object],[object Object],[object Object],Survey-Based Analysis Allen, Cummings, Wellman, Faust, Carley, Krackhart - Sparse real data From Sugarscape:  http://www.brook.edu/sugarscape Allen, T.,  Architecture and Communication Among Product Development Engineers . 1997, Sloan School of Management, MIT: Cambridge, p 33.
Bridging Simulations and Surveys with Sensors ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],(Bluetooth) Microphone / Headset Sharp Zaurus                                                                  
Why F2F Networks? Allen, T.,  Architecture and Communication Among Product Development Engineers . 1997, Sloan School of Management, MIT: Cambridge, p 33.
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Inference on Individuals : Previous Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
OverHear : Data Collection ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
OverHear : Classifier ,[object Object],[object Object]
OverHear : Initial Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Relationship Inference : Previous Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Allen’s Studies in the 20 th  Century [AH87] [A97] [A97] [A84]
Future Organizational Studies? ?
Individuals : Reality Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],wlan0  IEEE 802.11-DS  ESSID:"media lab 802.11"  Nickname:"zaurus" Mode:Managed  Frequency:2.437GHz  Access Point:  00:60:1D:1D:21:7E Link Quality: 42/92   Signal level:- 62  dBm  Noise level:- 78  dBm (HASABILITY "microphone" "record sound") (HASREQUIREMENT "record something" "have microphone") (HASUSE "microphone" "amplify voice") Audio Spectrogram Computer Transcription Common Sense Topic Spotting Wireless Network Information
Social Network Mapping - 802.11b Access Point Check - Waveform Segment Correlation High Energy Low Energy Exact Matches First-Order Proximity Second Order Proximity
Social Network Mapping Pairwise Conversation - Mutual Information [B02] - Non-Correlation + Speaker Transition Interruption Detection
Sample Data Group Pairwise
Networks Models Conversation Finite State Machine Variable-duration (semi-Markov) HMMs [Mu02] J N S The Influence Model with Hidden States [BCC01]
Initial Study : Project-based Class ,[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Reality Mining : The Applications ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Organizations
Social Network Analysis
Knowledge Management
Collaboration & Expertise  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Organizational Modeling ,[object Object],[object Object],[object Object],B A D C
Privacy Concerns ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Anticipations for Reality Mining ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Conclusions ,[object Object],[object Object],[BCC01]  Sumit Basu, Tanzeem Choudhury, Brian Clarkson and Alex Pentland.  Learning Human Interactions with the Influence Model . MIT  Media Lab  Vision and Modeling TR#539, June 2001.  [Mu02]  Murphy, K.  Modeling Sequential Data using Graphical Models.  Working Paper, MIT AI Lab, 2002 [AH87]  Allen, T.J. and O. Hauptman.  The Influence of Communication Technologies on Organization Structure: A Conceptual Model for Future  Research . Communication Research 14, 5, 1987, 575-587.   [A97]  Allen, T.,  A rchitecture and Communication Among Product Development Engineers . Sloan School of Management, MIT: Cambridge, 1997,  p 33. [A84]  Allen, T.J., 1984 (1st edition in 1977),  Managing the Flow of Technology: Technology Transfer and the Dissemination of Technological I nformation within the R&D Organization , MIT Press, Mass.
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Reality Mining (Nathan Eagle)

  • 1. Reality Mining Capturing Detailed Data on Human Networks and Mapping the Organizational Cognitive Infrastructure Nathan Eagle Digital Anthropology The MIT Media Lab February 21, 2003
  • 2. From User to Group-Centric To unobtrusively glean a detailed map of an organization’s cognitive infrastructure Who influences results? Who is helping whom? Who are the gatekeepers? Which people work well together? Where is the expert? Who knows what? Who should connect with whom? How will communication change after the merger? What is the optimum organizational structure?
  • 3.
  • 4.
  • 5.
  • 6. Physical to Cognitive Infrastructure 20 th Century Organization 21 st Century Organization Physical Infrastructure Cognitive Infrastructure flexibility, adaptation, robustness, speed – guided and tied together by ideas, by their knowledge of themselves, and by what they do and can accomplish slowly changing environment – development of infrastructures to carry out well described processes.
  • 7.
  • 8.
  • 9. Why F2F Networks? Allen, T., Architecture and Communication Among Product Development Engineers . 1997, Sloan School of Management, MIT: Cambridge, p 33.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16. Allen’s Studies in the 20 th Century [AH87] [A97] [A97] [A84]
  • 18.
  • 19. Social Network Mapping - 802.11b Access Point Check - Waveform Segment Correlation High Energy Low Energy Exact Matches First-Order Proximity Second Order Proximity
  • 20. Social Network Mapping Pairwise Conversation - Mutual Information [B02] - Non-Correlation + Speaker Transition Interruption Detection
  • 21. Sample Data Group Pairwise
  • 22. Networks Models Conversation Finite State Machine Variable-duration (semi-Markov) HMMs [Mu02] J N S The Influence Model with Hidden States [BCC01]
  • 23.
  • 24.
  • 25.
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.