Transmitting messages in the most efficient way as possible has always been one of politicians’ main concerns during electoral processes. Due to the rapidly growing number of users, online social networks have become ideal platforms for politicians to interact with their potential voters. Exploiting the available potential of these tools to maximize their influence over voters is one of politicians’ actual challenges. To step in this direction, we have analyzed the user activity in the online social network Twitter, during the 2011 Spanish Presidential electoral process, and found that such activity is correlated with the election results. We introduce a new measure to study political sentiment in Twitter, which we call the relative support. We have also characterized user behavior by analyzing the structural and dynamical patterns of the complex networks emergent from the mention and retweet networks. Our results suggest that the collective attention is driven by a very small fraction of users. Furthermore, we have analyzed the interactions taking place among politicians, observing a lack of debate. Finally, we develop a network growth model to reproduce the interactions taking place among politicians.

1.
C.
Honeycutt
and
S. C.
Herring
, in
HICSS
(
IEEE Computer Society
,
2009
), pp.
1
10
.
2.
D. M.
Romero
,
W.
Galuba
,
S.
Asur
, and
B. A.
Huberman
, “
Influence and passivity in social media
,” in
WWW’11
,
2010
.
3.
B. J.
Jansen
,
M.
Zhang
,
K.
Sobel
, and
A.
Chowdury
,
J. Am. Soc. Inform. Sci. Technol.
60
,
2169
(
2009
).
4.
See http://www.pewglobal.org/files/2011/12/Pew-Global-Attitudes-Technology-Report-FINAL-December-20-20111.pdf for Pew Research Center, Global Digital Communication: Texting, Social Networking Popular Worldwide (
2011
).
5.
A.
Tumasjan
,
T. O.
Sprenger
,
P. G.
Sandner
, and
I. M.
Welpe
, “
Predicting elections with Twitter: What 140 characters reveal about political sentiment
,” in
ICWSM
(
AAAI
,
2010
).
6.
M.
Conover
 et al, “
Political polarization on Twitter
,” in
ICWSM
(
AAAI
,
2011
).
7.
A.
Livne
,
M. P.
Simmons
,
E.
Adar
, and
L. A.
Adamic
, “
The party is over here: Structure and content in the 2010 election
,” in
ICWSM
(
AAAI
,
2011
).
8.
S.
Bocaletti
,
V.
Latora
,
Y.
Moreno
,
M.
Chavez
, and
D.-U.
Hwang
,
Phys. Rep.
424
,
175
(
2006
).
9.
R.
Albert
and
A.-L.
Barabasi
,
Rev. Mod. Phys.
74
,
47
97
(
2002
).
10.
M. E. J.
Newman
,
SIAM Rev.
45
(
2
),
167
256
(
2003
).
11.
A.
Santiago
and
R. M.
Benito
,
Europhys. Lett.
82
,
58004
(
2008
).
12.
H.
Kwak
,
C.
Lee
,
H.
Park
, and
S.
Moon
, in
WWW’10
(
ACM
,
2010
), pp.
591
600
.
13.
D.
Boyd
,
S.
Golder
, and
G.
Lotan
, in
HICSS
(
IEEE Computer Society
,
2010
), pp.
1
10
.
15.
M. E. J.
Newman
,
Contemp. Phys.
46
,
323
(
2005
).
16.
R.
Koop
and
H. J.
Jansen
,
Social Sci. Comput. Rev.
27
,
155
(
2009
).
17.
A.
Barrat
,
M.
Barthlemy
,
R.
Pastor-Satorras
, and
A.
Vespignani
,
Proc. Natl. Acad. Sci. U.S.A.
101
,
3747
(
2004
).
18.
M. E. J.
Newman
,
Phys. Rev. E
67
,
026126
(
2003
).
19.
J. G.
Foster
,
D. V.
Foster
,
P.
Grassberger
, and
M.
Paczuski
,
Proc. Natl. Acad. Sci. U.S.A.
107
,
10815
(
2010
).
20.
K. A.
Wojciech Galuba
,
D.
Chakraborty
, and
Z.
Despotovic
, “
Outtweeting the Twitterers—Predicting information cascades in microblogs
,” in
Microblogs 3rd Workshop on Online Social Networks, WOSN
,
2010
.
21.
H.-B.
Hu
and
X.-F.
Wang
,
Europhys. Lett.
86
,
18003
(
2009
).
22.
M.
Rosvall
and
C. T.
Bergstrom
,
Proc. Natl. Acad. Sci. U.S.A.
105
,
1118
(
2008
).
23.
H. Y.
Yoon
and
H. W.
Park
, Social media information flow and public representation: A case of S. Korean politicians on Twitter, in
9th International Triple Helix Conference
,
2011
.
24.
A.-L.
Barabasi
,
R.
Albert
, and
H.
Jeong
,
Physica A
272
,
173
(
1999
).
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