1. Using
Social
Media
To
Inform
Policy
Making:
To
whom
are
we
listening?
Miriam
Fernandez
Elisabeth
Cano
Harith
Alani
Beccy
Alen
Timo
Wandhoefer

2. Outline
• Introduc;on
• Related
Work
• Data
collec;on
• Data
Analysis
• Conclusions
2

3. Introduc@on
• Social
media
– A
revolu;onary
opportunity
for
governments
to
learn
about
the
ci;zens
and
to
engage
with
them
more
effec;vely
but,
– When
using
social
media
to
inform
Policy
Making…
• To
whom
are
we
listening?
– What
are
the
characteris+cs
of
those
ci+zens
discussing
policy
topics
in
social
media?
– What
are
the
characteris+cs
of
their
discussions?
3

4. Related
Work
(I)
• Three
main
lines
of
work
– Sta;s;cs
about
the
ci;zens’
par;cipa;on
on
ePlaMorms
• Not
social
media
par;cipa;on
– Sta;s;cs
about
users
par;cipa;ng
in
social
media
• Not
narrowed
to
ePar;cipa;on
/
poli;cal
discussions
– Studies
of
poli;cal
discussions
in
social
media
•
In
the
context
of
poli;cal
events
(elec;ons,
revolu;ons,
etc.),
not
focused
on
relevant
topics
for
policy
making
4
Par;cipa;on
in
policy
making
Par;cipa;on
in
social
media

5. Related
Work
(II)
• Ci;zen’s
par;cipa;on
in
ePlaMorms
– There
is
a
need
of
using
social
media
to
improve
public
services,
reduce
costs
and
increase
transparency
– Par;cipa;on
via
specific
online
government
services
is
generally
low
• Within
the
27
EU
countries,
only
32%
of
individuals
aged
16
to
74
have
used
the
Internet
for
interac;ng
with
public
authori;es
• Social
media
par;cipa;on
– There
is
6%
more
of
women
than
men
in
Twi[er
– 75%
of
users
fall
between
15
to
25
years
of
age
– The
average
Twi[er
user
follows
102
users,
is
followed
by
50
users
and
post
307
;mes
during
her
Twi[er
life
5

6. Data
Collec@on
• Data
– Policy
topics:
76
policy
topics
collected
from
16
PMs
• German
Bundestag,
the
State
Parliament
North
Rhine-­‐Westphalia,
the
state
Chancellery
of
the
Saarland
and
the
ci;es
Cologne
and
Kempten
– Generic
topics
(such
as
women)
were
filtered
to
avoid
collec;ng
noisy
data
-­‐>
42
remaining
topics
• Betreuungsgeld
(Care
Benefit
)
• Bildungspoli;k
(Educa;on
Policy)
• Bürgerrechte
(Civil
Rights)
• Datenschutz
(Privacy
Policy)
– Topics
were
monitored
in
Twi[er
for
a
week
6
Init
Date
Final
Date
Num
Posts
Num
Users
04/01/2014
12/01/2014
17,790
8,296

7. Data
Analysis
(I)
• Top
contributors
– Less
than
6%
of
the
users
are
responsible
for
36%
of
the
content
– 73.4%
of
top-­‐contributors
are
NOT
ci;zens
but
news
agencies
and
other
organisa;ons
• The
average
contributor
to
policy
discussions
– Is
more
ac;ve,
popular
and
engaged
than
the
average
Twi[er
User
• (Average
user
discussing
policy
in
our
dataset)
follows
630,
is
followed
by
1365
and
has
posted
9578
;mes
during
her
life
on
Twi[er
• (Beevolve,
2012)
Avg
Twi[er
User:
follows
102,
is
followed
by
50,
posts
307
7
Names
of
the
top
contributors

8. Data
Analysis
(II)
• Geographic
Distribu@on
of
Users
– Higher
concentra;on
of
users
occurs
in
cons;tuencies
of
high
popula;on
density
– Users
engaged
in
social
media
conversa;ons
around
policy
topics
tend
to
be
geographically
concentrated
in
the
same
regions
than
users
engaged
in
ePar;cipa;on
plaMorms
8
(a) Distribution of eParticipation projects (b) Distribution of Twitter users
Figure 1: (a) Distribution of eParticipation projects in Germany (http://www.politik.de/politik-
de/projekte_entdecken/beteiligungskarte) (b) Distribution of Twiter users: yellow are locations with less than 10
users, pink are locations with 10 to 50 users, red are locations with more than 50 users

9. Data
Analysis
(III)
• Topic
Distribu;on
– Few
topics
are
extensively
discussed
during
the
analysed
period
• Privacy,
Network
Policy,
Minimum
Wage,
Copyright,
etc.
–
The
majority
of
topics
are
underrepresented
9
0
500
1000
1500
2000
2500
3000
3500
4000

10. Data
Analysis
(IV)
• Sen;ment
Distribu;on
– Top
Nega;ve
topics
• Gene;c
Engineering
• Immigra;on
• Dona;ons
to
poli;cal
par;es
– Top
Controversial
topics
(High
percentage
of
posi;ve
and
nega;ve
posts)
• Privacy
• Fracking
10
Use
Sen;Wordnet
German
lexicon
to
compute
sen;ment

11. Limita@ons
of
the
data/analysis
• Data
available
at:
– h[p://kmi.open.ac.uk/people/miriam/ECSM2014/dataset.zip
• This
is
a
confined
study
– Data
collected
only
for
one
social
media
plaMorm
(Twi[er)
– Data
collected
only
for
the
German
language
– Data
collected
only
for
a
limited
period
of
;me
– Tweets
with
geo-­‐coordinates
are
very
scarce
• Users
geolocated
by
using
their
profile
informa;on
+
Google
services
– Concrete
sta;s;cs
about
the
geographical
distribu;on
of
users
engaged
in
ePar;cipa;on
plaMorms
in
Germany
not
available
•
Assump;on:
regions
with
high
number
of
ePar;cipa;on
ini;a;ves
are
also
those
ones
where
more
users
are
engaged
in
ePar;cipa;on
11

12. Conclusions
• Understanding
who
are
the
users
discussing
policy
in
social
media
and
how
policy
topics
are
debated
could
help
PMs
assessing
how
their
views
and
opinions
should
be
weighted
and
considered
to
inform
policy
making
• Main
highlights
of
this
study
– A
high
volume
of
conversa;ons
around
policy
topics
does
not
come
from
ci;zens,
but
from
news
agencies
and
other
organisa;ons
– Users
discussing
policy
topics
in
Twi[er
are
more
ac;ve,
popular
and
engaged
than
the
average
twi[er
user
12