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SOCIALMEDIA.ORG/SUMMIT2013 ORLANDO Social media intelligence WENDY MOE UNIVERSITY OF MARYLAND DECEMBER 9–11, 2013
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SOCIALMEDIA.ORG/SUMMIT2013ORLANDO
Social media intelligence
WENDY MOEUNIVERSITY OF MARYLAND
DECEMBER 9–11, 2013
Current practices
What’s wrong with these practices?
• Scalability
• Analyst bias
• Venue effects
• Selection effects that favor buzz-worthy topics
• Social dynamics that favor the extreme
• What exactly does the of number of mentions or average
sentiment mean? (correlation with offline survey = .008)
1. Understand the behavior
2. Implications for observed metrics and trends
3. Integrating social media with traditional sources of market intelligence
Social Media Intelligence
Breaking down the behavior
WHO?
WHAT?
WHERE? ON
LIN
E O
PIN
ION
• Posters versus lurkers • Behavioral biases in posting
decision
• Expressed sentiment (versus true underlying opinion)
• Topics vary in terms of their “buzz-worthiness”
• Venue differences lead to venue effects
Behavioral Biases
Pre-Purchase
Evaluation
Purchase Decision and
Product Experience
Post-Purchase
Evaluation
Incidence
Decision
Evaluation
Decision
Posted Product Ratings
EXP
ERIE
NC
E M
OD
EL
INC
IDEN
CE
& E
VA
LUA
TIO
N M
OD
ELS
SELECTION
EFFECT
ADJUSTMENT
EFFECT
What influences posting behavior? • Opinion formation vs. opinion
expression
• Opinion formation, in theory, is a function of satisfaction
• Opinion expression is subject to a variety of biases and dynamics – Expert effects – Multiple audience effects – Bandwagon vs. differentiation
• Example: Opinion polls and voter
turnout
How does dynamics affect what we observe?
Variance
Average
Activists
Post frequently Attracted by lack of consensus More negative Variance and volume make them more negative
Low Involvements
Post infrequently Deterred by lack of consensus More positive Variance and volume make them more positive
Brand Tracking
0%
20%
40%
60%
80%
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Pro
po
rtio
n o
f P
osi
tive
Co
mm
en
ts
Observation Month
Blog
Forum
Microblog
Aggregate
0%
20%
40%
60%
80%
100%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Dis
trib
uti
on
of
Co
mm
en
ts
Observation Month
Blog
Forum
Microblog
Other
Venue Correlation
Blogs .197
Forums -.231
Microblogs -394
Average .008
Correlation with offline brand tracking survey
What influenced expressed sentiment?
General Brand Impression (GBI)
Venue Venue-specific dynamics Message topic
Product and Attribute Effects
How much variance exists across focal topics related to the brand?
GBI and Offline Brand Tracking Surveys
• Potential for GBI as a lead indicator
• Correlation with survey (t) – GBI = .376
– Avg sentiment =.008
– Blogs = .197
– Forums = -.231
– Microblogs = .394
• Correlation with survey (t-1)
– GBI = .881
– Avg sentiment = .169
– Blogs = .529
– Forums = .213
– Microblogs = .722
8.75
8.8
8.85
8.9
8.95
9
9.05
9.1
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
1 2 3 4 5 6 7 8 9 10
Ave
rage
Su
rve
y R
esp
on
se
GB
I
Month of Overlap Period (t)
GBI in month t-1 Survey in month t
GBI and Stock Price (DV=monthly close)
Coeff StdErr p-val
Constant -69.045 34.044 0.070
S&P* 0.104 0.031 0.008
GBI(t) -16.695 10.324 0.137
GBI(t-1) 30.693 10.375 0.014
Adj R-sq .475
* Closing price in month
S&P Index
GBI
Lagged GBI
Using Social Media Intelligence for Brand Tracking
• Significant social dynamics exist • Encourage a variety of opinions to include the moderate majority.
This encourages discussion and insulates impact on sales.
• Social media behavior varies across venue formats • Monitor multiple sources of SM data • Account for source effects in SM data • Neglecting to account for venue can bias sentiment inferences • Prevalence of attributes mentioned in social media depends on
venues monitored
• Potential to use social media for market research • Adjusted measure (GBI) can serve as lead indicator
• Model-based measure vs. disaggregate metrics
Questions?
www.BuildYourSMI.com Coming in January 2014
@wendymoe
www.wendymoe.com
SOCIALMEDIA.ORG/SUMMIT2013ORLANDO
Learn more about past andupcoming events
DECEMBER 9–11, 2013
SOCIALMEDIA.ORG/EVENTS
