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Web 2.0 4.1.09


Beyond Buzz: On
measuring a conversation

Kate Niederhoffer, Ph.D   Marc A. Smith, Ph.D
Dachis Corporation        Telligent Systems
                            Proprietary & Confidential — © 2008 DachisCorporation
Why us?




                                       Marc Smith
Kate Niederhoffer
                                       •  Ph.D UCLA Sociology
•  Ph.D UT Social Psychology
                                       •  Microsoft Research, Community
•  BuzzMetrics/Nielsen Online,
                                       Technologies Group
Measurement Science
                                       •  Telligent Systems – “Harvest” reporting
•  Dachis Corporation - Methodology,
                                       and analysis tools for social media platforms
Social Business Design
                                       and systems

Note: This is a conceptual address. We’re talking about ideas; each of our
companies have distinct methodologies in place related to these concepts.
  2
Why are we here?

                1. Demonstrating the depth
                   of buzz; ways to think
                   about signal within vast
                   universe.




                2. Going beyond buzz;
                   learning more about
                   individuals.


3
Why are we here?

                3. Highlighting the unique
                   roles individuals play in
                   communities that afford
                   the conversation.




                4. Illustrating that
                    aggregated relationships
                    are network structures.


4
Why now?


5
Blogs were all the rage
In 2005, clients attracted by novelty:


Simple question: What’s my buzz?
- How much?
- Good or bad?


Incremental improvement: How “important” is it?
- Are “Influencers” talking?
- How many eyeballs exposed?
- Engagement?
       However, all superficially measured;
        limited scope of what’s important: what kind of influence?
  6
Blogs are now features
       •  Today’s “media” enable richer social interaction-- and, leave a path
         of data with more opportunities to capture depth


       •  Buzz levels, page views, followers, in isolation miss big picture


       •  Must take advantage context to tell whole story and capture value




7
Social networks are all the rage, but
rarely do we think about social metrics




We need to stop blackboxing:
       quot;When a machine runs efficiently, when a matter of fact is settled, one need focus
only on its inputs and outputs and not on its internal complexity. Thus, paradoxically, the
more science and technology succeed, the more opaque and obscure they become.quot;
- Bruno Latour

Even if a conversation is running smoothly, we must figure out what makes it tick.
8
Social Network
       Theory
Central tenet:
    Social structure emerges from
       the aggregate of relationships (ties)
       among members of a population


Phenomena of interest:
    Emergence of cliques and clusters                     Source: Richards, W. (1986). The NEGOPY network
      from patterns of relationships                      analysis program. Burnaby, BC: Department of
                                                                                                            
                                                          Communication, Simon Fraser University. pp.7-16
    Centrality (core), periphery (isolates),
      betweenness


Methods:
    Surveys, interviews, observations, log file analysis,
       computational analysis of matrices


                                               (Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)
Context of a conversation


                  Relevance
                           Signal
              Where’s the signal in the noise?

                    Mindset
                           Person
         What else do we know about the individuals?


                       Role
                           Persona
            What is the pattern of connections?


                   Ecosystem
                           Environment
             What is the dynamic, en masse?



10
11
Context of a conversation


              Relevance
           Where’s the signal in the noise?

                 Mindset

                     Role

             Ecosystem

12
Relevance today
•  As a user, easy to relate to issues with pre-determined filters.
•  As an enterprise, complexity increases.




We don’t always know what we want to know!
13
Relevance:
Which filters are in place to strengthen the signal?

                                                                                             •  Identifying your filters can
                                                                                             be inductive:

                                                                                             •  What are people really saying?   


                                                                                             • Which concepts differentiate the
                                                                                             posts that mention you vs. posts
                                                                                             that don't?




                                                                                              * Source: Nielsen Online, 2008

• All terms on your map have a correlation to the central concept; the closer a word appears to the center, the stronger the
association.The groupings of terms indicate the dimensions of discussion: micro-conversations within a broader discussion. 
  14
Relevance is multi-faceted
                        • Rather than looking at
                         associations with, as
                         compared to without,
                         consider discussion this
                         week as compared to
                         discussion over the past
                         year.


                        • Not what’s being said about
                         her in a more recent
                         timeframe, but instead
                         when you control for what’s
                         said about her in general,
                         what pops?


                         * Source: Nielsen Online, 2008

15
Relevance - Summary

      • Information can be visualized in so many different
       ways; don’t take it for granted.
        • Listening can be limited if you’re exclusively looking for
         something in particular; broaden your net. Be inductive.
         Let the data speak for itself.




16
17
Context of a conversation


                  Relevance

                    Mindset
        What else can we know about the individuals?


                       Role

                 Ecosystem


18
Says Who?




19
Mindset
    What else can we know about the person in conversation? 

•  By measuring the types of words used, we can
                                                            Findings
              Linguistic Cues
  tap into how people ‘slice’ their worlds.

•  Linguistic style is closely tied to:
                                                       Are you self-oriented?
    Pronoun use: I and We

     •  Demographics (e.g. age, sex, class)
                                                       Are you living in ‘the
                                                                                 Past, Present, Future tense
     •  Emotion (e.g. depression, deception)                 now’?


     •  Cognitive style (e.g. complex thinking)       What is your emotional
                                                                                    Positive vs. Negative
                                                               tone?
     •  Personality (e.g. Neuroticism)
                                                        Are you abstract or        Articles: “a” vs. “the”
                                                             concrete?
              Nouns vs. verbs




                                                  e.g. Pennebaker, Mehl, Niederhoffer, 2003
   20
When people make
recommendations on blogs, is
there something deeper going on?
       “Got the next three PW/GS games for my
       birthday. And I am one happy gal, there was
       some stuff that I absolutely LOVED and I
       would definitely recommend
       the game to anyone who owns a PS3 regardless
       of its flaws -- which really were at their heart
       personal quibbles of mine so your mileage may
       vary. Plus, I cried like a b*$$ at the end. That's
       got to be saying something.”




21
Getting into the Engaged Mind
•    Recommendations have:

      •    More pronouns: intimacy with both the brand/product/ service being
           recommended, and those to whom they’re recommending.
      •    More verbs: sharing experience more than discussion of concrete features.




                                * all differences significant at p<.01 level
     22
“Invisible” language gives us clues
 about individuals, and groups




23
Changes in work atmosphere,
captured in words



                     Engineers, economists
                     programmers collaborating on
                     economic simulations of disasters

                     •  Complexity of thought (-) 
                     •  Cohesion (-)
                     • Work information (-)
                     •  Negative emotion (+)
                         •  Funding lost

               Tausczik, Scholand, and Pennebaker, 2009
24
“Connected Age”: relationships are
 groundwork of work




Social: niceties (lol), affirmations (cool),   Work: economic (production, supply),
coordination (call), broad communication          analytic (results, problem) 
             (http, thinking) 
   25
Mindset- Summary

      • Language is a good way to go beyond the surface
       and better understand constituents without self-
       report biases (or effort).
        •  Metrics in the hands of users (yourselves) are helpful:
         know thyself, know how you’re perceived.




26
Beyond thoughts and feelings, who comes to roost?




27
Context of a conversation


               Relevance

                  Mindset

                      Role
          What is the pattern of connections?


              Ecosystem


28
Social
Network
Analysis
with
NodeXL:

Identify
different
roles in
social media
spaces
Identify core groups in the
network
Distinguishing attributes:

              • Answer person
               – Outward ties to local isolates
               – Relative absence of triangles
               – Few intense ties


              • Reply Magnet
               – Ties from local isolates often inward
               only
               – Sparse, few triangles
               – Few intense ties

31
Distinguishing attributes:

              • Answer person
               – Outward ties to local isolates
               – Relative absence of triangles
               – Few intense ties


              • Discussion person
               – Ties from local isolates often inward
               only
               – Dense, many triangles
               – Numerous intense ties

32
Answer

  Person

Signatures

Discussion

  People





              33
Discussion


                    Starter

     Spammer





Reply
oriented

  Discussion
          Flame

                      Warrior




                    34
Role – Summary




•  Network awareness, like court vision enables strategic play. Know which positions/
      players are on your team.
      •  Social media behavior is differentiated. Rare (~.5-2%) roles are critical and must
        be cultivated.
      •  E.g. Clear and consistent signatures of an “Answer Person
         •  Light touch to numerous threads initiated by someone else
         •  Most ties are outward to local isolates
         •  Many more ties to small fish than big fish
35
What is the mix in the
        neighborhood?



36
Context of a conversation


              Relevance

                 Mindset

                    Role

             Ecosystem
           What is the dynamic, en masse?



37
38
The Ties that Blind?




     Pajek
without
modifica>on
can


some>mes
reveal
structures
of
great
interest.

Darwin
Bell

   40
41
42
Mapping
Newsgroup
  Social
   Ties




Microsoft.public.windowsxp.server.general
                                                   43
    Two “answer people” with an emerging    3rd.
Research shows social media
spaces vary and roles are present




                  Adamic
et
al.
WWW

                        2008

Ecosystem- Summary

      •  Social media is about collective action.
        •  A balance of roles and strategies is critical for a
        healthy/ successful collective good.

      •  Harvesting the common good takes many forms,
      and is the ultimate goal of social media.




45
Why does this matter?
      •  This is not measurement for the sake of
      measurement; we need to measure conversations in
      order to manage social business.

        •  Measuring conversations is about measuring the
        context in which those conversations arise.

      •  Value is an intermediate step in calculating ROI. Moot
      to bypass it.

        •  Techniques from social science help capture “the
        immeasurable” in social media and the enterprise.

      •  The future of conversations- the enterprise being
      one-- is about cultivating ecologies of the right balance
      of relationships.
46
Thank You

      k.niederhoffer@gmail.com

      marc.smith@telligent.com

            Questions?
47
Additional Resources




48
49
Small
Groups

Individuals
             Uniform
Large
Groups





                                       Heterogeneous


       Variable
Contribu>on

                                    Variable
Contribu>on


           
Large
Groups

       How uniform are social           Large
Groups

      media producing groups?
Social Science Theory and
Method
Interactionist Sociology                        Collective Action Dilemmas
                                                Central tenet
    Central tenet
        Focus on the active effort of                Individual rationality leads to collective
        accomplishing interaction                     disaster

    Phenomena of interest
                                                  Phenomena of interest
        Presentation of self
                                                     Provision and/or sustainable
                                                     consumption of collective resources
        Claims to membership
        Juggling multiple (conflicting) roles        Public Goods, Common Property, quot;Free
                                                     Rider” Problems, Tragedies
        Frontstage/Backstage
        Strategic interaction
                                                  Methods
        Managing one’s own and others’ “face”
                                                     Surveys, interviews, participant
                                                     observation, log file analysis, computer
    Methods                                          modeling
        Ethnography and participant observation
                                                     (Axelrod, 1984; Hess, 1995; Kollock &
                                                      Smith, 1996)
        (Goffman, 1959; Hall, 1990)

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Beyond Buzz - Web 2.0 Expo - K.Niederhoffer & M.Smith

  • 1. Web 2.0 4.1.09 Beyond Buzz: On measuring a conversation Kate Niederhoffer, Ph.D Marc A. Smith, Ph.D Dachis Corporation Telligent Systems Proprietary & Confidential — © 2008 DachisCorporation
  • 2. Why us? Marc Smith Kate Niederhoffer •  Ph.D UCLA Sociology •  Ph.D UT Social Psychology •  Microsoft Research, Community •  BuzzMetrics/Nielsen Online, Technologies Group Measurement Science •  Telligent Systems – “Harvest” reporting •  Dachis Corporation - Methodology, and analysis tools for social media platforms Social Business Design and systems Note: This is a conceptual address. We’re talking about ideas; each of our companies have distinct methodologies in place related to these concepts. 2
  • 3. Why are we here? 1. Demonstrating the depth of buzz; ways to think about signal within vast universe. 2. Going beyond buzz; learning more about individuals. 3
  • 4. Why are we here? 3. Highlighting the unique roles individuals play in communities that afford the conversation. 4. Illustrating that aggregated relationships are network structures. 4
  • 6. Blogs were all the rage In 2005, clients attracted by novelty: Simple question: What’s my buzz? - How much? - Good or bad? Incremental improvement: How “important” is it? - Are “Influencers” talking? - How many eyeballs exposed? - Engagement? However, all superficially measured; limited scope of what’s important: what kind of influence? 6
  • 7. Blogs are now features •  Today’s “media” enable richer social interaction-- and, leave a path of data with more opportunities to capture depth •  Buzz levels, page views, followers, in isolation miss big picture •  Must take advantage context to tell whole story and capture value 7
  • 8. Social networks are all the rage, but rarely do we think about social metrics We need to stop blackboxing: quot;When a machine runs efficiently, when a matter of fact is settled, one need focus only on its inputs and outputs and not on its internal complexity. Thus, paradoxically, the more science and technology succeed, the more opaque and obscure they become.quot; - Bruno Latour Even if a conversation is running smoothly, we must figure out what makes it tick. 8
  • 9. Social Network Theory Central tenet: Social structure emerges from the aggregate of relationships (ties) among members of a population Phenomena of interest: Emergence of cliques and clusters Source: Richards, W. (1986). The NEGOPY network from patterns of relationships analysis program. Burnaby, BC: Department of Communication, Simon Fraser University. pp.7-16 Centrality (core), periphery (isolates), betweenness Methods: Surveys, interviews, observations, log file analysis, computational analysis of matrices (Hampton &Wellman, 1999; Paolillo, 2001; Wellman, 2001)
  • 10. Context of a conversation Relevance Signal Where’s the signal in the noise? Mindset Person What else do we know about the individuals? Role Persona What is the pattern of connections? Ecosystem Environment What is the dynamic, en masse? 10
  • 11. 11
  • 12. Context of a conversation Relevance Where’s the signal in the noise? Mindset Role Ecosystem 12
  • 13. Relevance today •  As a user, easy to relate to issues with pre-determined filters. •  As an enterprise, complexity increases. We don’t always know what we want to know! 13
  • 14. Relevance: Which filters are in place to strengthen the signal? •  Identifying your filters can be inductive: •  What are people really saying? • Which concepts differentiate the posts that mention you vs. posts that don't? * Source: Nielsen Online, 2008 • All terms on your map have a correlation to the central concept; the closer a word appears to the center, the stronger the association.The groupings of terms indicate the dimensions of discussion: micro-conversations within a broader discussion. 14
  • 15. Relevance is multi-faceted • Rather than looking at associations with, as compared to without, consider discussion this week as compared to discussion over the past year. • Not what’s being said about her in a more recent timeframe, but instead when you control for what’s said about her in general, what pops? * Source: Nielsen Online, 2008 15
  • 16. Relevance - Summary • Information can be visualized in so many different ways; don’t take it for granted. • Listening can be limited if you’re exclusively looking for something in particular; broaden your net. Be inductive. Let the data speak for itself. 16
  • 17. 17
  • 18. Context of a conversation Relevance Mindset What else can we know about the individuals? Role Ecosystem 18
  • 20. Mindset What else can we know about the person in conversation? •  By measuring the types of words used, we can Findings Linguistic Cues tap into how people ‘slice’ their worlds. •  Linguistic style is closely tied to: Are you self-oriented? Pronoun use: I and We •  Demographics (e.g. age, sex, class) Are you living in ‘the Past, Present, Future tense •  Emotion (e.g. depression, deception) now’? •  Cognitive style (e.g. complex thinking) What is your emotional Positive vs. Negative tone? •  Personality (e.g. Neuroticism) Are you abstract or Articles: “a” vs. “the” concrete? Nouns vs. verbs e.g. Pennebaker, Mehl, Niederhoffer, 2003 20
  • 21. When people make recommendations on blogs, is there something deeper going on? “Got the next three PW/GS games for my birthday. And I am one happy gal, there was some stuff that I absolutely LOVED and I would definitely recommend the game to anyone who owns a PS3 regardless of its flaws -- which really were at their heart personal quibbles of mine so your mileage may vary. Plus, I cried like a b*$$ at the end. That's got to be saying something.” 21
  • 22. Getting into the Engaged Mind •  Recommendations have: •  More pronouns: intimacy with both the brand/product/ service being recommended, and those to whom they’re recommending. •  More verbs: sharing experience more than discussion of concrete features. * all differences significant at p<.01 level 22
  • 23. “Invisible” language gives us clues about individuals, and groups 23
  • 24. Changes in work atmosphere, captured in words Engineers, economists programmers collaborating on economic simulations of disasters •  Complexity of thought (-) •  Cohesion (-) • Work information (-) •  Negative emotion (+) •  Funding lost Tausczik, Scholand, and Pennebaker, 2009 24
  • 25. “Connected Age”: relationships are groundwork of work Social: niceties (lol), affirmations (cool), Work: economic (production, supply), coordination (call), broad communication analytic (results, problem) (http, thinking) 25
  • 26. Mindset- Summary • Language is a good way to go beyond the surface and better understand constituents without self- report biases (or effort). •  Metrics in the hands of users (yourselves) are helpful: know thyself, know how you’re perceived. 26
  • 27. Beyond thoughts and feelings, who comes to roost? 27
  • 28. Context of a conversation Relevance Mindset Role What is the pattern of connections? Ecosystem 28
  • 30. Identify core groups in the network
  • 31. Distinguishing attributes: • Answer person – Outward ties to local isolates – Relative absence of triangles – Few intense ties • Reply Magnet – Ties from local isolates often inward only – Sparse, few triangles – Few intense ties 31
  • 32. Distinguishing attributes: • Answer person – Outward ties to local isolates – Relative absence of triangles – Few intense ties • Discussion person – Ties from local isolates often inward only – Dense, many triangles – Numerous intense ties 32
  • 34. Discussion

 Starter
 Spammer
 Reply
oriented
 Discussion
 Flame
 Warrior
 34
  • 35. Role – Summary •  Network awareness, like court vision enables strategic play. Know which positions/ players are on your team. •  Social media behavior is differentiated. Rare (~.5-2%) roles are critical and must be cultivated. •  E.g. Clear and consistent signatures of an “Answer Person •  Light touch to numerous threads initiated by someone else •  Most ties are outward to local isolates •  Many more ties to small fish than big fish 35
  • 36. What is the mix in the neighborhood? 36
  • 37. Context of a conversation Relevance Mindset Role Ecosystem What is the dynamic, en masse? 37
  • 38. 38
  • 39. The Ties that Blind? Pajek
without
modifica>on
can

 some>mes
reveal
structures
of
great
interest.

  • 41. 41
  • 42. 42
  • 43. Mapping Newsgroup Social Ties Microsoft.public.windowsxp.server.general 43 Two “answer people” with an emerging 3rd.
  • 44. Research shows social media spaces vary and roles are present Adamic
et
al.
WWW
 2008

  • 45. Ecosystem- Summary •  Social media is about collective action. •  A balance of roles and strategies is critical for a healthy/ successful collective good. •  Harvesting the common good takes many forms, and is the ultimate goal of social media. 45
  • 46. Why does this matter? •  This is not measurement for the sake of measurement; we need to measure conversations in order to manage social business. •  Measuring conversations is about measuring the context in which those conversations arise. •  Value is an intermediate step in calculating ROI. Moot to bypass it. •  Techniques from social science help capture “the immeasurable” in social media and the enterprise. •  The future of conversations- the enterprise being one-- is about cultivating ecologies of the right balance of relationships. 46
  • 47. Thank You k.niederhoffer@gmail.com marc.smith@telligent.com Questions? 47
  • 49. 49
  • 50. Small
Groups
 Individuals
 Uniform
Large
Groups
 Heterogeneous

 Variable
Contribu>on
 Variable
Contribu>on

 
Large
Groups
 How uniform are social Large
Groups
 media producing groups?
  • 51. Social Science Theory and Method Interactionist Sociology Collective Action Dilemmas Central tenet Central tenet Focus on the active effort of Individual rationality leads to collective accomplishing interaction disaster Phenomena of interest Phenomena of interest Presentation of self Provision and/or sustainable consumption of collective resources Claims to membership Juggling multiple (conflicting) roles Public Goods, Common Property, quot;Free Rider” Problems, Tragedies Frontstage/Backstage Strategic interaction Methods Managing one’s own and others’ “face” Surveys, interviews, participant observation, log file analysis, computer Methods modeling Ethnography and participant observation (Axelrod, 1984; Hess, 1995; Kollock & Smith, 1996) (Goffman, 1959; Hall, 1990)