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Pizza Talk III: Online-Firestorms - Negative Dynamics in Social Media Networks
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Pizza Talk III:
Online-Firestorms
Negative Dynamics in Social
Media Networks!
Sunbelt XXXIV
Thomas Zorbach & Jürgen Pfeffer
February 21st 2014, St. Pete Beach, FL!
Center
for
Computa-onal
Analysis
of
Social
and
Organiza-onal
Systems
2. Thomas
Zorbach,
Jürgen
Pfeffer
Agenda
Online-‐Firestorms
–
The
dark
side
of
word
of
mouth
– What
is
it?
– How
does
it
work?
– What
can
we
do?
Online-Firestorms. Negative Dynamics in Social Media Networks!
3. Thomas
Zorbach,
Jürgen
Pfeffer
A
German
problem?
→
Poli%cians,
celebri%es,
companies
under
heavy
fire
Online-Firestorms. Negative Dynamics in Social Media Networks!
3
4. Thomas
Zorbach,
Jürgen
Pfeffer
Unse3ledness
in
Poli6cs
and
Business
“Let’s
be;er
not
say
anything.
Otherwise,
we’ll
have
an
online
firestorm
tomorrow!”
(Angela
Merkel,
Bundeskanzlerin)
→ Sign of the participatory culture (Jenkins, 2006)
Online-Firestorms. Negative Dynamics in Social Media Networks!
4
5. Thomas
Zorbach,
Jürgen
Pfeffer
Anglicism
of
the
Year
2011
in
Germany
„Shitstorm
fills
the
gap
in
German
vocabulary
that
was
opened
up
by
changes
in
the
public
debate
culture.“
→ Kick off for research project
Online-Firestorms. Negative Dynamics in Social Media Networks!
5
6. Thomas
Zorbach,
Jürgen
Pfeffer
Intercultural
Differences
“Shitstorm”
vs.
“Online-‐Firestorm”
→ “Title is not appropriate”
Online-Firestorms. Negative Dynamics in Social Media Networks!
7. Thomas
Zorbach,
Jürgen
Pfeffer
Defini6on
“An
Online-‐Firestorm
is
a
phenomenon
that
describes
the
sudden
discharge
of
large
quan%%es
of
nega%ve
word
of
mouth
and
complaint
behavior
against
a
person,
company,
or
group
in
social
media
networks,
oHen
paired
with
intense
indigna%on
that
has
shiHed
its
focus
from
an
actual
point
of
cri%cism.“
Pfeffer,
J.
&
Zorbach,
T.
&
Carley,
K.M.
(2013).
Understanding
online
firestorms:
Nega%ve
word
of
mouth
dynamics
in
social
media
networks.
Journal
of
Marke%ng
Communica%ons
Online-Firestorms. Negative Dynamics in Social Media Networks!
7
8. Thomas
Zorbach,
Jürgen
Pfeffer
Case
Study:
Rolling
Stone
Magazine
→
Cover
showing
Dzhokhar
Tsarnaev
Online-Firestorms. Negative Dynamics in Social Media Networks!
8
9. Thomas
Zorbach,
Jürgen
Pfeffer
Rolling
Stone
Firestorm
-‐
Analysis
TwiVer
data
used:
– ~1.5%
of
all
tweets
are
geo-‐tagged
– Long-‐term
collec-on
of
US
geo-‐Tweets
– “rollingstone”
or
“rolling
stone”
Online-Firestorms. Negative Dynamics in Social Media Networks!
10. Thomas
Zorbach,
Jürgen
Pfeffer
Empirical
Observa6ons/Factors
Constant
flow
of
informa6on,
short
informa6on
half-‐life
• Real-‐-me
messages
in
social
media
create
a
constant
flow
of
communica-on
• Many
people
can
be
reached
within
a
short
period
of
-me
• Result:
Temporal
dominance
of
a
single
topic
• Communica-on/reac-on
cycle
– Tradi-onal
newspaper:
1
day
– Social
media:
hours
or
minutes
• Half-‐Life
(Burton
and
Kebler,
1960)
of
social
media
informa-on:
– Hours
or
even
minutes
(Fang,
2007).
• TwiVer:
Cri-cal
role
in
the
propaga-on
of
all
online
firestorms
→
Speed
and
volume
Online-Firestorms. Negative Dynamics in Social Media Networks!
10
11. Thomas
Zorbach,
Jürgen
Pfeffer
Tweets/Day
Online-Firestorms. Negative Dynamics in Social Media Networks!
12. Thomas
Zorbach,
Jürgen
Pfeffer
Rolling
Stone
Firestorm
-‐
Numbers
• Peak:
7/17
+
7/18
• 5,836
tweets,
4,571
different
users
• 60
users
with
min.
5
tweets
(=473
tweets)
Online-Firestorms. Negative Dynamics in Social Media Networks!
13. Thomas
Zorbach,
Jürgen
Pfeffer
Empirical
Observa6ons/Factors
No
gradualist
opinions,
absence
of
discursive
interac6ons
• Opinion-‐forming
systems
without
sophis-cated
or
gradualist
opinions
• Re-‐tweet,
‘like’,
or
‘+1’
• Decision-‐making
process
as
binary
choices
(Schelling,
1973)
• ”either-‐or
situa-ons”
→
Binary
choices
Online-Firestorms. Negative Dynamics in Social Media Networks!
13
14. Thomas
Zorbach,
Jürgen
Pfeffer
Rolling
Stone
Firestorm
-‐
Retweets
RT @LisaLampanelli: Poll: 65% of
Americans thought Rolling Stone cover
w Boston Bomber was inappropriate.
Other 35% thought John Mayer
grew…
Online-Firestorms. Negative Dynamics in Social Media Networks!
15. Thomas
Zorbach,
Jürgen
Pfeffer
Empirical
Observa6ons/Factors
Friends
act
as
informa6on
source
and
as
filter
• Connec-ons
tend
to
be
based
on
homophily
(McPherson
et
al.,
2001)
– similar
in
age,
gender,
and
socio-‐economic
status
• Plus:
Technology
filters
informa-on
based
on
interests
• Filter
bubble
(Pariser,
2011)
is
a
concept
which
refers
to
over-‐
emphasizing
the
importance
of
single
topics
or
opinions
→
Lack
of
diversity
Online-Firestorms. Negative Dynamics in Social Media Networks!
15
16. Thomas
Zorbach,
Jürgen
Pfeffer
Rolling
Stone
Firestorm
-‐
Top
users?
• Top
10
user
and
their
number
of
geo-‐tweets
in
July
2013:
–
–
–
–
–
–
–
–
–
–
trendinaliaUS
Boston_CP
ChelseaKrost
IndianapolisCP
Logan_Rosalez
JDawgMadden
LisaG_325
MaVhewKeysLive
TimothyODonnel2
GlutenFreeDog
9,741
7,612
7,314
6,873
3,377
3,301
3,266
2,784
2,645
1,848
• Spammers,
bots?
Online-Firestorms. Negative Dynamics in Social Media Networks!
17. Thomas
Zorbach,
Jürgen
Pfeffer
Empirical
Observa6ons/Factors
Amplified
epidemic
spreading,
network
clusters
• Transi-ve
link
crea-ons
(Heider,
1946)
C
A
B
• Social
media
systems
intensify
this
effect
with
link
sugges-ons
→
Network
clusters
&
echo
chambers
Online-Firestorms. Negative Dynamics in Social Media Networks!
17
18. Thomas
Zorbach,
Jürgen
Pfeffer
Empirical
Observa6ons/Factors
Offline
and
online
media
reinforce
one
another
• Social
media
are
an
important
informa-on
source
for
tradi-onal
media
(Diakopoulos
et
al.,
2012).
• TwiVer
is
used
as
“radar”
• “Sharability”
triggers
prolifera-on
in
social
media
Tradi-onal
Social
Media
Media
→
Cross
media
dynamics
Online-Firestorms. Negative Dynamics in Social Media Networks!
18
19. Thomas
Zorbach,
Jürgen
Pfeffer
Rolling
Stone
Firestorm
–
Media
Dynamics
• 702
re-‐tweets:
–
–
–
–
RT @nytimes: CVS and Walgreens
35%
RT
@ny-mes
Ban an Issue of Rolling Stone http://
24%
RT
@OpieRadio
t.co/6mSRHuT671
30%
RTs
from
5
journalists
Almost
all
are
re-‐tweets
from
media
outlets
RT @OpieRadio: The news shows outrage for
the Rolling Stone cover by SHOWING THE
ROLLING STONE COVER. #Dopes
Online-Firestorms. Negative Dynamics in Social Media Networks!
20. Thomas
Zorbach,
Jürgen
Pfeffer
Empirical
Observa6ons/Factors
Modified
opinion
adop6on
process,
dominant
network
effects
Diffusion
and
adop-on
process
(Rogers,
1995):
• Knowledge
Filter
Bubble
– The
agent
gets
in
contact
with
a
new
opinion
or
belief.
• Persuasion
Echo
Chamber
– The
agent
starts
to
have
a
posi-ve
or
nega-ve
stance.
Re-‐infec-on.
• Decision
– The
opinion
or
belief
is
accepted
or
rejected.
• Propaga%on
– The
agent
starts
to
ac-vely
propagate
the
opinion
or
belief.
Infec-on.
• Affirma%on
Echo
Chamber
– Posi-ve
feedback
encourages,
nega-ve
feedback
destabilizes.
→
Cogni%ve
processes
get
replaced
by
network
effects!
Online-Firestorms. Negative Dynamics in Social Media Networks!
20
21. Thomas
Zorbach,
Jürgen
Pfeffer
“Our mission is to go forward, and it has only just begun.
There's still much to do, still so much to learn. Engage!”
Jean-Luc Picard, TNG Season 1 Ep. 26
Thomas
Zorbach
t.zorbach@vm-‐people.de
@vmpeople
Jürgen
Pfeffer
jpfeffer@cs.cmu.edu
@JurgenPfeffer
Online-Firestorms. Negative Dynamics in Social Media Networks!