ANALYZING SOCIAL
MEDIA MOMENTUM
Prepared for:
The U.S.
U S Of fice
of South Asia Policy
By:
Sasha Bong
Kenneth Chung
Karen Parkinson
pp
Andrew Peppard
Justin Rabbach
Nicole Thiher
India’s 2011
A ti rr ti
Anticorruption
Movement
RESEARCH QUESTIONS
 Explore role of social media in social movements
 How did India’s anticorruption movement use Facebook?
?
 How is user activity on Facebook related to type of content?
 How do real-world protest events and government actions
affect user activity?
SOCIAL MEDIA IN INDIA AND THE 2011
ANTI-CORRUPTION MOVEMENT
 Lokpal arose as a possible solution to India’s
India s ongoing
corruption problem
 Lokpal would create ombudsman
 Versions proposed since 1968
 Exclusion of key officials (especially Prime Minister) is a lingering
issue
 Key events: April, August, and December
DATA COLLECTION
 Narrowed our focus to Facebook
 India Against Corruption (official page), Anna Hazare (fan page)
 Facebook provides easily identifiable measures of interactions
with post content
 Likes: positive and supportive of content, unique users
 Comments: positive or negative,
negative unique or repeat users
 We used levels of user interaction with post content as a
measurement of social engagement
FACEBOOK INTERACTIONS
250
200
200
150
150
100
100
50
50
0
0
F
M
A
AH + IAC Likes
M
J
J
A
AH + IAC Comments
S
O
N
D
J
F
Times of India + The Hindu
Prin
nt Media A
Articles perr Day
TThousandss
AH + IA
AC Likes, C
Commentss per Day
SOCIAL AND TRADITIONAL MEDIA
COMPARISON
MARCH 25 – APRIL 4
 The movement begins following a failed March 28 th meeting:
 The sub-committee… met colleagues of Hazare "but the interactions
proved fruitless as the activists were insisting on the government
accepting their draft in full.”
Times of India news article, April 4
 “After
After meeting with PM ended inconclusively,
inconclusively there is no point in
meeting more ministers and committees –we demand Jan Lokpal
and we will have it!!!!”
IAC Facebook post, March 25
 “Delhi / NCR Volunteer Meet on Sunday 27th March – to mobilise
maximum people for Anna Hazare’s fast. Lets create a Tahrir Chowk
at Ja
Jantar
ta Mantar.
a ta All Delhi
e
volunteers,
o u tee s, p
please
ease jo
join us
us.”
IAC Facebook post, March 25
DECEMBER 22 – JANUARY 5
 How did the movement end? Where is the movement today?
 “Due to what is happening in the Parliament, the Anshan will finish
today and our aim for now will be voter awareness and the elections
in the five states,” Anna.
IAC Facebook post, December 28, 4:49 a.m. CST
 “The anti-corruption movement is at the crossroads today. Where do
we go from here? …. If we do not go for the tour of election-bound
states, what should we do? Should Anna go for another fast? But the
government has already indicated that if people participating in the
movement don’t translate into votes, they don’t care. Some have
suggested we should form our own party. But we neither have the will
nor the capacity.
capacity.”
IAC Facebook post, January 5, 2012, 9:21 p.m. CST
ANALY TICAL GOALS
 Correlation between Facebook user activity,
activity news media
coverage, and movement activity on the ground
 Used regression analysis to determine the following:
 Which themes were important in what phases?
 Did their importance change over time?
 Are real world events one of the main drivers of Facebook
interaction?
INDEPENDENT VARIABLES
 Real World Events
 Government actions; Protests; Parliamentary Sessions
 Days of the week
 Phases
 Protests (2, 4, 6); Lulls (1, 3, 5, 7)
 Themes
 Corruption, Lokpal, Anna Hazare, Hunger Strike, Demonstration, and
Government
 Theme/Phase Interactions
 Post Characteristics
 Video, Photos, News Articles, Blog Posts
Budget
g
Monsoon
Winter
1
2.0
Parliamen
nt in Sessio
on
x 100000
0
AH + IA
AC Likes, C
Commentss per Day
PARLIAMENTARY SESSIONS
1.5
10
1.0
0.5
0.0
0
F
M
A
M
AH + IAC Likes
J
J
A
S
O
AH + IAC Comments
N
D
ParlSess
J
F
DEPENDENT VARIABLES

BASIC MODEL OUTPUT
Basic Model Explanatory Variables
Hazare
Hunger Strike
RW Protest Event
RW Positive Gov't Act
RW Negative Gov't Act
RW Parliament Session
Video
Wednesday
Th d
Thursday
Friday
Percentage Change in Likes on a Post
Likes on a Post
‐4.3%
4.4%
7.7%
14.1%
21.2%
4.5%
8.8%
13 1%
13.1%
10.9%
Percentage Change in Comments on a Post
‐4.2%
‐8.7%
15.2%
15.0%
7.4%
15.0%
16 5%
16.5%
16.1%
INTERACTION MODEL OUTPUT
Interaction Model
Interaction Model
Explanatory Variables
Percentage Change in Likes on a Post
Corruption Phase 5
Demonstration Phase 4
Percentage Change in Comments on a Post
7.0%
10.0%
Government Phase 6
29.8%
Hazare
‐60.6%
‐56.7%
Hazare Phase 2
‐9.4%
‐0.9%
Hazare Phase 3
‐9.5%
‐5.6%
Hazare Phase 4
Hazare Phase 4
2 7%
2.7%
‐2
2.3%
3%
Hazare Phase 5
3.8%
9.2%
Hazare Phase 6
4.8%
Hazare Phase 7
8.4%
Percentage Change in Explanatory Variables
Likes on a Post
Lokpal Phase 2
9.6%
Lokpal Phase 3
8.8%
Lokpal Phase 6
Percentage Change in Comments on a Post
28.9%
Lokpal Phase 7
Phase 7
10.9%
RW Protest Event
14.4%
RW Positive Gov't Act
13.3%
RW Negative Gov't Act
14.2%
15.0%
RW Parliament Session
7.8%
‐16.0%
Video
5.3%
7.9%
3.1%
Wednesday
9.1%
15.3%
0.1%
Thursdayy
14.0%
17.8%
Friday
11.0%
16.5%
Hunger Strike Phase 5
‐20.9%
Hunger Strike Phase 6
‐34.8%
Perce
entage of P
Posts
Conttaining The
eme
POST THEMES BY PHASE
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
1
2
Corruption
Hunger Strike
3
4
Phase
Lokpal
Demonstration
5
Hazare
Government
6
7
RECOMMENDATIONS AND CONCLUSIONS
 Not able to determine causal relationships between social
media content and effect on “real world action”
 Predictive ability in understanding how a movement may
respond to a specific government action or in a certain
situation
 Implications for the use of social media in movements for
governments or organizers
 Potential for greater real time data collection and broader
source collection to inform conclusions
QUESTIONS?
For further information
Contact the La Follette School’s publications office at
(608)-263-7657 or publications@lafollette.wisc.edu
Or see www.lafollette.wisc.edu/publications/workshops.html
Thank You
Yo
23
2.0
22
1.8
21
1.5
20
1.3
19
1.0
Mon
Tue
Wed
AvgPosts
Thu
Fri
Sat
AvgMostSigPost
Sun
Average number off
Most Significant Possts
Average
e number o
of posts per weekdayy
DAY-OF-THE-WEEK
DAY
OF THE WEEK ACTIVIT Y
1
2.0
Real world p
R
protest eve
ent
x 100000
AH + IA
AC Likes, C
Commentss per day
FACEBOOK VS
VS. REAL WORLD PROTESTS
1.5
1.0
05
0.5
0.0
0
F
M
A
M
AH + IAC Likes
J
J
A
S
AH + IAC Comments
O
N
D
J
ProtestEvent
F
1
2.0
Real world gove
ernment acction (-)
x 100000
0
d Commentts per day
AH, IAC Likes and
FACEBOOK VS
VS. GOVERNMENT ACTION ((-))
1.5
10
1.0
0.5
0.0
0
F
M
A
M
AH + IAC Likes
J
J
A
S
O
AH + IAC Comments
N
D
J
NegGovAct
F
1
2.0
Rea
al world govvernment a
action
x 100000
0
AH + IA
AC Likes, C
Commentss per day
FACEBOOK VS
VS. GOVERNMENT ACTION (+)
1.5
10
1.0
0.5
0.0
0
F
M
A
M
AH + IAC Likes
J
J
A
S
O
AH + IAC Comments
N
D
J
PosGovAct
F