Presentation given at the Communities Technologies conference on June 27 2009, describing study of Pathable, an online social networking and community development tool for events. We found at a BarCamp Seattle that Pathable had a meaningful impact on sense of community at the event. We review lessons learned in creating temporary communities over many events.

1. Leveraging Social Software for Social Networking and Community Development at Events Shelly D. Farnham, Ph.D. Founder, Research Consultant Waggle Labs / Pathable Communities and Technologies, 2009 Partners and coauthors: Peter T. Brown, Jordan Schwartz

2. Core Problem People go to events to meet others Professional events are increasingly technology enabled How to best leverage advances in social software to improve face-to-face networking at professional events

3. Agenda Background Pathable Questionnaire field study Lessons learned over 17 deployments at events

6. Social Networking at Events World wide over 1.2 million professional events each year, adding up to a hundred billion dollar industry Why? Learning Meeting people! Forming connections with clients and colleagues Face-to-face for developing trust face-to-face for informal idea and knowledge sharing via conversation

7. Building Community at Events In early interviews with conference organizers, they listed building community as a primary goal Why do event attendees and event hosts at professional events care about building community?

9. Powerfully increase social capital through simple act of joining community

11. Who is here? Who do I want to meet?

12. Social Networks Social Scientist Media Startup Research SocialTech Community RealityAllStar BlogHer Blogger startup community social technology blogger

13. Creating Semantic Layer to Social Space Our Approach: minimal profiles, based on tagging Add tags or keywords to self E.g. “research, social computing, art” Optimize design for converging on terms Across people, important terms emerge Tags used as search and browse pivots Tags used as conversation groups Clustering, abstraction, and match-making based on co-occurrence Tagging provides semantic layer to social space!

14. Early Exploration at Seattle Mind Camp 3 75 people provided tags for self, organization, related people, related events

15. Pathable Community and social networking tools for conferences Community Dashboard  Profiles Attendee directory Match-making Messaging Feeds (blog, twitter) Wiki Schedule

16. Attendee Directory

17. Profile

18. Edit Profile

19. Host Manager -- Dashboard

20. Host Manager -- Attendees

21. Face to Face Integration Using existing technologies: Mobile Badges Printable calendar Visualization

22. Personalized Badge

23. Match-making Best matches possible, with minimal effort in profiles Based on predictors of successful matches: Common interests Same roles Job title Host provided categories Co-location By geography By events Existing shared groups and communities Weighted sum to produce ordered list

24. Design Themes The event host is a connector and community moderator Coauthor profiles Communication broker, event defining access Social tags are used as pivots of awareness, connection, and communication Professional match matching based on tags for improved people finding Incorporate communication back channels Face to face integration

26. Online networks for events, less emphasis on face to face integration, no recommendations

27. IntroNetworks

28. Online network for event, recommendations, extremely heavy weight

29. Ntag,Spotme

30. Mobile devices, expensive, no pre- and post- online network

31. Proactive displays, e.g. Neighborhood Window

32. Expensive equipment, required proximity to screen

33. Pathable:

34. Online directory/community, host as community moderator

35. Online and face to face integration, for pre- during and post- networking

37. Self-report Measurements Networking behaviors Goal in coming to event How many new people met Number of friends and colleagues Perceived professional social support received from people at event Pathable usage Psychological sense of community [Wilkinson, 2007] adapted for events “A feeling of fellowship runs deep between me and others at BarCamp” “I feel loyal to the people at BarCamp” “My friendships and associations with others at BarCamp mean a lot” Event attachment Satisfaction with event

38. Measurement Cont’d Event attachment Adapted from Rosenbaum et al. study of a suburban diner People who experienced social support and community through diner, developed place attachment – bond between person and place Expected similar transfer of affect for events: Three factors: dependency, commitment, identification Sense of Community Place Attachment Sense of Community Event Attachment

39. Primary Goal in Coming to Event

40. Correlations between Event Features and Intention to Return Sense of community and event attachment highly correlation r = .81 Bolded items are statistically significant at p < .05.

41. Pathable Usage Everyone registered through Pathable, about half actively used the system 60% actively browsed directory 47% actively browsed messages 19% actively sent messages 43% intended to use directory after event 55% intended to use communication features after event If they said they came to event only to learn, less likely to use Pathable(t = 2.6, p < .02) The higher the usage, the more they said it helped them meet people (r = .65, p < .001) No correlation between usage and count of people met Usage correlated with count of professional friends at event (r = .36, p < .01) **percentages for those who indicated at least somewhat or quite a bit

42. Impact on Professional Network

43. Impact on Attachment and Sense of Community

44. Impact of Usage by Feature Pathablehelped attendees meet others the more they browsed the attendee directory (r = .37, p < .005) the more they browsed attendee messages (r = .43, p < .005) the more they sent messages (r =.54, p < .005) the more they used the match-making feature (r = .66, p < .005)

45. Lessons Learned Across Events Seventeen deployments over five months Evening mixers One to three day conferences Review of what worked, what did not

47. Can create an active community with minimal effort

48. Two emails

49. Seeded initial profiles

51. Pathable Group Messages

52. Searching Attendee Directory Average total number of directory searches per event: 6882

53. Seeding the Community Ensure the community feels full from the start Model the desired behavior Invite the organizers, speakers, volunteers to complete a profile first Author the speaker/high status profiles Seed representative tags Seed type of conversation hoped for Send personal invitations

54. Leveraging Match-making Features Nurturing tags Use badges Use color coded categories Provides overview Easy point of conversation Examples Job types: developer, designer, marketer Interests: blogging, podcasting, and mobile Person types: creative vs. geek Personality: introvert, extrovert Integrate with face to face Introductions Birds of a feather meetings

55. People Loved Badges and blogged about them!

56. Conclusions Networking and community development primary goal Professional networking and sense of community strong predictors of event satisfaction, event attachment, and intention to return Pathable helped Features helped attendees meet others, especially use of match-making feature Usage had positive impact on sense of community, event attachment It is quality, not quantity, that matters counts of people met had little impact on satisfaction quality of conversation, usage of matching-making tool, and count of professional connections had an impact

57. Issues Requirements for success of Pathable Event organizers must actively adopt role of community organizers Important to seed community profiles and conversation Important to have seamless integration with registration system Event duration must be long enough, and desire to meet others strong enough to motivate people to complete profiles Study issues Correlation is not causation Perhaps people with stronger sense of community more likely to use Pathable Did find usage is correlated with desire to meet new people, and users reportedit helped them meet new people Generalizability to other types of events Features Tagging still a new idea for many people Profile fatigue

58. Next Steps Personalized scheduling Twitter integration Matching based on complementary interests Custom profile questions

59. Twitter