Presentation at Data on the Mind workshop, Berkeley CA USA

1. Exploring Social Theory through
Enterprise Social Media
Michael Muller*
Cognitive User Experience
IBM Research, CCaammbbrriiddggee MMAA UUSSAA
With thanks to:
Joan DiMicco1, Kate Ehrlich*, Rosta Farzan2, Werner Geyer*,
Tara Matthews3, MikhilMasli*, David Millen*, Sadat Shami*, JennThom4,
Steve Daniel*, Wendy Kellogg*, Todd Soule*, John Wafer*, RajanVaish5,
Li-Te Cheng3, Jonathan Feinberg3
*IBM unless:
1. Forrester. 2. University of Pittsburgh 3. Google 4. University CA Santa Cruz
© IBM Research 2014 1

2. Context: Broader Approaches to Social Media Studies
• Ways of Knowing in HCI (ed. Judy Olson & Wendy Kellogg)
– Loren Terveen: Study, build, repeat:… online communities…
– Katie Siek: Field deployments: Knowing from using in context
• David Millen, IBM
– Identify important phenomenon on Internet
– Build our own version, “behind the firewall”
Authentication trust + accountability
Confidentiality of own aanndd ccuussttoommeerr’’ss ddaattaa
– Werner Geyer: ActivityExplorer Activities
– Dogear – social bookmarking Bookmarks
– Cattail – social file-sharing Files
– Beehive SocialBlue – social-networking Profiles
– Discover online communities Communities
– Tara Matthews: Tools for community learders Community Insights
– Muller et al.: “1x5” for enterprise crowdfunding iFundIT
• Jill Drury, Laurie Damianos, et al., MITRE
– Enterprise social media Handshake
© IBM Research 2014 2

3. Context: Broader Approaches to Social Media Studies
• Ways of Knowing in HCI (ed. Judy Olson Wendy Kellogg)
– Loren Terveen: Study, build, repeat:… online communities…
– Katie Siek: Field deployments: Knowing from using in context
• David Millen, IBM
– Identify important phenomenon on Internet
– Build our own version, “behind the firewall”
Authentication trust + accountability
Confidentiality of own aanndd ccuussttoommeerr’’ss ddaattaa
– Werner Geyer: ActivityExplorer Activities
– Dogear – social bookmarking Bookmarks
– Cattail – social file-sharing Files
– Beehive SocialBlue – social-networking Profiles
– Discover online communities Communities
– Tara Matthews: Tools for community learders Community Insights
– Muller et al.: “1x5” for enterprise crowdfunding iFundIT
• Jill Drury, Laurie Damianos, et al., MITRE
– Enterprise social media Handshake
© IBM Research 2014 3

4. Context: Broader Approaches to Social Media Studies
• Ways of Knowing in HCI (ed. Judy Olson Wendy Kellogg)
– Loren Terveen: Study, build, repeat:… online communities…
– Katie Siek: Field deployments: Knowing from using in context
• David Millen, IBM
– Identify important phenomenon on Internet
– Build our own version, “behind the firewall”
Authentication trust + accountability
Confidentiality of own aanndd ccuussttoommeerr’’ss ddaattaa
– Werner Geyer: ActivityExplorer Activities
– Dogear – social bookmarking Bookmarks
– Cattail – social file-sharing Files
– Beehive SocialBlue – social-networking Profiles
– Discover online communities Communities
– Tara Matthews: Tools for community learders Community Insights
– Muller et al.: “1x5” for enterprise crowdfunding iFundIT
• Jill Drury, Laurie Damianos, et al., MITRE
– Enterprise social media Handshake
© IBM Research 2014 4

5. Context: Broader Approaches to Social Media Studies
• Ways of Knowing in HCI (ed. Judy Olson Wendy Kellogg)
– Loren Terveen: Study, build, repeat:… online communities…
– Katie Siek: Field deployments: Knowing from using in context
• David Millen, IBM
– Identify important phenomenon on Internet
– Build our own version, “behind the firewall”
Authentication trust + accountability
Confidentiality of own aanndd ccuussttoommeerr’’ss ddaattaa
– Werner Geyer: ActivityExplorer Activities
– Dogear – social bookmarking Bookmarks
– Cattail – social file-sharing Files
– Beehive SocialBlue – social-networking Profiles
– Discover online communities Communities
– Tara Matthews: Tools for community learders Community Insights
– Muller et al.: “1x5” for enterprise crowdfunding iFundIT
• Jill Drury, Laurie Damianos, et al., MITRE
– Enterprise social media Handshake
© IBM Research 2014 5

6. Strategy
• Build something of value… where people do things of value
– Criteria: Lots of people use it
… to do important things for companies, clients, and careers
• Generate data
– With full and legal consent (international standards)
– Authenticated via corporate LDAP
– Supplement each person’s data with organizational ddeemmooggrraapphhiiccss
• Country, division, [group name], [job-category name]
– Supplement each person’s data with social network information
• Other people in the same group
• Collaboration partners
• Limited social network data (friending)
• Test questions from theory
– … and provide value to the enterprise
• Observe and “harvest” user innovations (appropriation)
© IBM Research 2014 6

7. “Build Something of Value…”
• Research prototypes, “fielded” to all of IBM
– 423,000 potential participants
– Internal publicity
– Some ideas succeed
– Some ideas fail
• IBM Connection number of multi-user instances
–– BBllooggss 1144,,554433**
– Wikis 65,529*
– Profiles (social networking) 423,000 potential
– Activities (collaborative task-management) 31,562*
– Online communities 135,238*
• iFundIT (enterprise crowdfunding) 7 campaigns / 489 projects**
* count is for public instances
** on-going campaign
© IBM Research 2014 7

8. “… Where People Do Things of Value”
• Snapshot 1: Tagging for audiences
• Snapshot 2: Text-based analysis of Employee Engagement
• Snapshot 3: Social Identity Theory in enterprise crowdfunding
© IBM Research 2014 8

9. Snapshot 1: Audiences in Social Bookmarking
• Context: 2007, when “bookmarking for an audience” was
heretical
• Jenn Thom (Thom-Santelli)
– “Big data”
• Track frequency of tag inscriptions
• Track frequency of tag searches
– Contextualized, individual, qualitative data
Combining “big data”
and local,
contextualized
people and places:
On-going methods
• Find “interesting” people and interview them
• Major findings: Tagging for audiences
– Community leaders – try to choose obvious tags to recruit people
– Team leaders – try to choose unobvious tags to limit to team members
– Individuals creating their reputations – try to focus on a single,
characteristic, popular tag to establish self as company-wide expert
9
research
© IBM Research 2014

10. Snapshot 1: Audiences in Social Bookmarking
• Context: 2007, when “bookmarking for an audience” was
heretical
• Jenn Thom (Thom-Santelli)
– “Big data”
• Track frequency of tag inscriptions
• Track frequency of tag searches
– Contextualized, individual, qualitative data
Combining “big data”
and local,
contextualized
people and places:
On-going methods
• Find “interesting” people and interview them
• Major findings: Tagging for audiences
– Community leaders – try to choose obvious tags to recruit people
– Team leaders – try to choose unobvious tags to limit to team members
– Individuals creating their reputations – try to focus on a single,
characteristic, popular tag to establish self as company-wide expert
10
research
© IBM Research 2014

11. Snapshot 2: Text-based analysis of Employee Engagement
• “Employee engagement” considered desirable by executives
– Discerned by surveys
• Expensive
• Annual
– Can we find “engagement signals” in employee social media?
– 263 thematic dictionaries
•• MMaajjoorr rreessuullttss
– Data quality:
Requires about 15
postings for clear
characterization
– State vs. Trait:
Engagement is a
state
– Themes: +PositiveAffect, +Try, +Social, +Wellbeing
- Decrease, - Vice, - 1st-person-singular, - Future
11
Data Quality
© IBM Research 2014

12. Snapshot 3: Social Identity Theory in Crowdfunding (1)
• Enterprise crowdfunding
– Like Kickstarter, Indiegogo, Rockethub…, but behind the firewall
– Executive gives each employee in her/his organization a budget to
spend on proposals by colleagues
• Research question: Geographical boundaries to investing?
– Homophily theory: “Birds of a feather flock together”
– Social Identity theory: Quantify homophily in terms ooff ““ttrraaiittss iinn
common”
– Dimensions of difference (“traits in common” or not in common):
• Country geographical boundaries
• Global working groups team/work-content boundaries
• Division (~job requirements) organizational boundaries
© IBM Research 2014 12

13. Snapshot 3: Social Identity Theory in Crowdfunding (2)
• Compute expected % contribution; Plot deviations from expected
Main effects for Country, Working-Group, and Division
300.00%
0.00%
same different
C=C Country
C=/C G=G G=/G
300.00%
0.00%
same different
D=D Division
D=/D
300.00%
0.00%
same different
Group
Percent of
Expected Value
Percent of
Expected Value
Percent of
Expected Value
C=C C≠C G=G G≠G D=D D≠D
300%
100%
0%
% Expected Value
300%
100%
0%
% Expected Value
300%
100%
0%
% Expected Value
Country
Group Division
Two-way interactions of Identity Facets
13
600%
600.00%
% Expected Value
Percent of
Expected Value
600%
100%
600%
100%
% Expected Value
100%
100.00% 100.00% 100.00%
0%
• Conclusions
600.00%
0%
0.00%
sameCountry
sameDivision
sameCountry
differentDivision
differentCountry
sameDivision
600.00%
0%
• People easily invest across obstacles of country, working-group, division
• Social identity facets in common give an added boost to investment
differentCountry
differentDivision
Country*Division interaction
0.00%
sameCountry
sameGroup
sameCountry
differentGroup
differentCountry
sameGroup
differentCountry
differentGroup
Country*Group Interaction
0.00%
sameGroup
sameDivision
sameGroup
differentDivision
differentGroup-sameDivision
differentGroup
differentDivision
Group*Division interaction
C=C
G=G
C=C
G≠G
C≠C
G=G
C≠C
G≠G
C=C
D=D
C=C
D≠D
C≠C
D=D
C≠C
D≠D
G=G
D=D
G=G
D≠D
G≠G
D
G≠G
D≠D
Country*Group interaction Group*Division interaction Country*Division interaction
% Expected Value
C=C C=C C=/C C=/C
G=G G=/G G=G G=/G
G=G G=G G=/G G=/G
D=D D=/D D=D D=/D
C=C C=C C=/C C=/C
D=D D=/D D=D D=/D
© IBM Research 2014

14. Summary and Conclusion
• Build something of value… where people do things of value
• Generate data
– With full and legal consent (international standards)
– Authenticated via corporate LDAP
– Supplement each person’s data with organizational demographics
– Supplement each person’s data with social network information
• Test questions ffrroomm tthheeoorryy
• Put methods into dialogue: Shift analyses back and forth
– Big data / quantitative analyses
– Contextual data / qualitative analysis
• Deliver value in areas of theory, method, and business
© IBM Research 2014 14