1. Technology-Mediated Social Participation: An Interdisciplinary Lecture Series http://www.cs.umd.edu/hcil/tmsp Jointly sponsored by Dept of Computer Science (Larry Davis, Chair) Dept of Sociology (Reeve Vanneman, Chair) UM Institute for Advanced Computer Studies (Amitabh Varshney, Director) College of Information Studies, Maryland ’s iSchool (Jennifer Preece, Dean) Human-Computer Interaction Lab (Allison Druin, Director, Jen Golbeck, Co-Director) Organized by Ben Shneiderman, Dept of Computer Science, UMIACS & HCIL ( [email_address] )
12. Technology-Mediated Social Participation: An Interdisciplinary Lecture Series February 14, 2011, 4pm, AVW 2460 Nation of Neighbors: Design and Network Evolution for Internet Community Safety Systems February 21, 2011, 4pm, Art/Sociology 1101 Theorizing Web 2.0: The Role of Prosumers March 7, 2011, 4pm, Hornbake 2119 Encyclopedia of Life: Motivating Public Enthusiasts and Expert Scientists to Document the World ’s Species March 14, 2011, 4pm, AVW 2460 1) Probabilistic Soft Logic: A Data-driven Toolkit for Analyzing, Utilizing & Decision Making using Social Information 2) Social Network Optimization Problems, 3) Building the B(r)and: The Use of Social Media to Monitor and Manage Conversations http://www.cs.umd.edu/hcil/tmsp
13. Nation of Neighbors: Design and Network Evolution for Internet Community Safety Systems Ben Shneiderman (CS & UMIACS), Alan Neustadtl (SOCY), Catherine Plaisant (UMIACS, HCIL), Jae-wook Ahn (CS, HCIL), PJ Rey (SOCY grad student), Nick Violi (CS grad student) Supported by NSF Social Computational Systems grant http://www.cs.umd.edu/hcil/NON
15. NoN Report: Promotes Community Safety Break-In/Burglary Theft-Other Than from Home Vandalism/Graffiti/Destruction Suspicious Activity Threat Assault Accident-Motor Vehicle Drug Activity Fire Public Nuisance Reckless Endangerment Animal Problem ATV Complaint Litter/Garbage Dumping Quality of Life Issue Other
29. User Survey (n = 152) Research Directions 1. Determine factors that predict successful community development. 2. Find common characteristics of key players in successful community networks.
30. User Survey (n = 152) Sections 1. Recruitment 2. Neighborhoods 3. Demographics 4. Perceptions of Crime 5. Competing Sources of Info 6. Motivations for Use 7. User Response to NoN 8. Ego Net Data 9. Technical Proficiency 10. Social Isolation
31. User Survey (n = 152) Sections 1. Recruitment 2. Neighborhoods 3. Demographics 4. Perceptions of Crime 5. Competing Sources of Info 6. Motivations for Use 7. User Response to NoN 8. Ego Net Data 9. Technical Proficiency 10. Social Isolation
32. User Survey (n = 152) Sections 1. Recruitment 2. Neighborhoods 3. Demographics 4. Perceptions of Crime 5. Competing Sources of Info 6. Motivations for Use 7. User Response to NoN 8. Ego Net Data 9. Technical Proficiency 10. Social Isolation
33. User Survey (n = 152) Sections 1. Recruitment 2. Neighborhoods 3. Demographics 4. Perceptions of Crime 5. Competing Sources of Info 6. Motivations for Use 7. User Response to NoN 8. Ego Net Data 9. Technical Proficiency 10. Social Isolation
34.
35. User Survey (n = 152) Sections 1. Recruitment 2. Neighborhoods 3. Demographics 4. Perceptions of Crime 5. Competing Sources of Info 6. Motivations for Use 7. User Response to NoN 8. Ego Net Data 9. Technical Proficiency 10. Social Isolation
41. TempoVis: Color Code for Changes Added activities “now” Aging activities of “past” Marquee selection of groups Time Slider Graph attributes
42. Nation of Neighbors: Design and Network Evolution for Internet Community Safety Systems Ben Shneiderman (CS & UMIACS), Alan Neustadtl (SOCY), Catherine Plaisant (UMIACS, HCIL), Jae-wook Ahn (CS, HCIL), PJ Rey (SOCY grad student), Nick Violi (CS grad student) Supported by NSF Social Computational Systems grant http://www.cs.umd.edu/hcil/NON