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Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation Fabio Giglietto Università di Urbino Carlo Bo Luca Rossi Università di Urbino Carlo Bo IV STS Italiana National Conference Rovigo 21-23 June 2012

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Presentation delivered during the 4th national STS Italia conference. Rovigo, 22 June 2012.AuthorsFabio Giglietto [[email protected]], Luca Rossi [[email protected]]Department of Communication Studies - University of Urbino Carlo BoAbstractThe public by default nature of Twitter messages, together with the adoption of the #hashtag convention, led during the last few years to the creation of a digital space able to host world-wide conversation on almost every kind of topic (Bruns, 2011; Honeycutt & Herring, 2009; Huberman, Romero, & Wu, 2009; Marwick & boyd, 2010). Beside the adoption of hashtag based conversations as a way to deal with crisis and natural disasters, this practices has been largely adopted as an effective way to share the experience of watching television. So far research on this phenomenon has been focused mainly on large media events (Dayan & Katz, 1994) where Twitter participation occurred as part of the media experience of a single and unique event (Rossi, Magnani, & Iadarola, 2011). These topical discussions take place outside of the standard Twitter network made of follower and followee and represent one of the most interesting recent examples of social shaping of digital media. Hashtag conversations, as well as the idea of the hashtag itself, do not come, in fact, with Twitter’s original feature but instead exploit available affordances of the media (Bruns, 2011; Tumasjan, Sprenger, Sandner, & Welpe, 2010). This paper bring a substantial contribution to the understanding of how Twitter users’ real practices can reshape the experience of contemporary television by focusing on the study of an appointment based TV show: Servizio Pubblico. Servizio Pubblico is a political talk show aired weekly starting from November 3rd 2011 simultaneously, both on Pay-TV, a large number of local broadcasters and streamed online live on several websites. This peculiar airing/streaming strategy, as well as the more traditional weekly appointment schedule, represents an unexplored scenario for Twitter based studies. The paper will focus on the following research questions:RQ1. Is the Twitter conversation network of Servizio Pubblico changing over the several weeks of the show airing? Is it possible to identify a definite set of participants or are they changing every week?RQ2. Is the conversation mainly made of comments on what is happening in the show or the topic addressed by the TV show actually ignite some debate?RQ3. Can the Twitter activity be considered as a good indicator of a TV show success? How can it be compared with more traditional data such as the number of viewer or the audience share?The three RQs will be addressed by analyzing, with a quanti-qualitative methodology, a dataset of over 90,750 Tweet containing the #serviziopubblico hashtag gathered starting from the October 26th 2010.

TRANSCRIPT

Page 1: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Analyzing #serviziopubblico: networked publics, appointment based television

and the structure of Twitter conversation

Fabio Giglietto – Università di Urbino Carlo Bo

Luca Rossi – Università di Urbino Carlo Bo

IV STS Italiana National Conference

Rovigo 21-23 June 2012

Page 2: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

#serviziopubblico:

Political TV show aired from Nov. 3rd

2011 to June 7th 2012 (27 episodes)

Multiplatform: Satellite TV + Local TV +

Streaming

(partially) Crowdfunded: 100k

subscribers rised more than 1M €

Page 3: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

#serviziopubblico:

12.03

10.42 9.7

8.08 8.01

4.99

6.89

7.75

8.88

7.65

6.85

6.11 5.93

6.71 6

5.2

6.3

7.66

6.2 6.2

7.08 7.02 7.5

6.26

0

2

4

6

8

10

12

14

Share (%)

Page 4: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

research questions:

RQ1. Is the Twitter conversation network of Servizio Pubblico changing

over the several weeks of the show airing time? Is it possible to identify a

definite set of participants or are they changing every week?

RQ2. Is the conversation mainly made of comments on what is happening

on the TV show or the topic raised by the TV show are able to ignite some

debate?

RQ3. Can the Twitter activity be considered as a good indicator of a TV

show success? How can it be compared with more traditional data such

as the number of viewer or the audience

share?

Page 5: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

dataset:

Twitter data acquired through

discovertext from Oct. 26th 2011 to

June 1st 2012.

158.240 tweets

31599 users

Subdataset: airing time of 25 episodes

of the show (9.00 pm – 00.30 am)

Page 6: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

0

2000

4000

6000

8000

10000

12000

20

11

-Oct

-26

20

11

-Oct

-31

20

11

-No

v-0

5

20

11

-No

v-1

0

20

11

-No

v-1

5

20

11

-No

v-2

0

20

11

-No

v-2

5

20

11

-No

v-3

0

20

11

-Dec

-05

20

11

-Dec

-10

20

11

-Dec

-18

20

11

-Dec

-23

20

11

-Dec

-28

20

12

-Jan

-02

20

12

-Jan

-07

20

12

-Jan

-12

20

12

-Jan

-17

20

12

-Jan

-22

20

12

-Jan

-27

20

12

-Feb

-01

20

12

-Feb

-06

20

12

-Feb

-11

20

12

-Feb

-16

20

12

-Feb

-21

20

12

-Feb

-26

20

12

-Mar

-02

20

12

-Mar

-07

20

12

-Mar

-23

20

12

-Mar

-28

20

12

-Ap

r-0

2

20

12

-Ap

r-0

7

20

12

-Ap

r-1

2

20

12

-Ap

r-1

7

20

12

-Ap

r-2

2

20

12

-Ap

r-2

7

20

12

-May

-02

20

12

-May

-07

20

12

-May

-12

20

12

-May

-17

20

12

-May

-22

20

12

-May

-27

20

12

-Ju

n-0

1

Twitter activity

Page 7: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

RQ1. Is the Twitter conversation network of Servizio

Pubblico changing over the several weeks of the

show airing time? Is it possible to identify a definite set of participants or are they changing every week?

Page 8: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Users’ activity (whole dataset)

1% of the users made

28% of the tweets while

90% of the users made 36% of the tweets

1%

9%

90%

28%

36%

36%

users tweet

Page 9: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Core group: (> 50% of episodes) 177 users (0,78% of the users)

The average user twitted during almost 2 episodes (1,88) [var 4,15 σ 2,03]

Page 10: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Core group activity:

tweet ReTweet RT/Tweet n

Core Group

22178 (19%)

4139 (14%)

18,6% 177

Main Group

92902 25233 27,1% 21996

Page 11: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

@net (177 core users)

Page 12: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

RQ2. Is the conversation mainly made of comments

on what is happening on the TV show or the topic

raised by the TV show are able to ignite some debate?

Page 13: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

0

1000

2000

3000

4000

5000

6000

0 1000 2000 3000 4000 5000 6000

RT

Tweet originali

Page 14: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Qualitative analysis:

Title: Celentano c’è

Date: 23 Febbraio 2012

Audience: 1.688.000

Share: 6,71 %

Tweet (21:00 – 00:30): 8604 Coded Tweet: 8604

Page 15: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Tweeting about TV: Sharing television viewing experiences via social media message streams by D. Yvette Wohn and Eun–Kyung Na. First Monday, Volume 16, Number 3 - 7 March 2011

Coding Matrix:

Inbound Outbound

subjective Emotion Opinion

objective Att. seeking Information

*ReTweets and @reply have not been coded

Page 16: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Attention Seeking: «Mi sono perso qualche

informazione e/o riflessione indispensabile stasera?

Sempre gli stessi ospiti no? #serviziopubblico » [timoteocarpita – 00:15]

Emotion: «Celentano io ti amo #serviziopubblico»

[dashingdesiree – 22:45]

«Confermo: Celentano è un coglione

#serviziopubblico»

[Geras0ne – 22:44]

Page 17: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Information: « “La RAI sembra una succursale del

Vaticano” Marco Travaglio #serviziopubblico » [beaimpera – 23:35]

Opinion: «#serviziopubblico Sono d’accordo con

Belpietro, cosa sto fumando ? » [memolabile – 22:28]

Page 18: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Coded Tweet created during the show airtime (23/02/2012 21:00-00:30)

0

5

10

15

20

25

30

35

40

45

20

12-0

2-2

3 2

1:0

0

20

12-0

2-2

3 2

1:0

4

20

12-0

2-2

3 2

1:0

8

20

12-0

2-2

3 2

1:1

2

20

12-0

2-2

3 2

1:1

6

20

12-0

2-2

3 2

1:2

0

20

12-0

2-2

3 2

1:2

4

20

12-0

2-2

3 2

1:2

8

20

12-0

2-2

3 2

1:3

2

20

12-0

2-2

3 2

1:3

6

20

12-0

2-2

3 2

1:4

0

20

12-0

2-2

3 2

1:4

4

20

12-0

2-2

3 2

1:4

8

20

12-0

2-2

3 2

1:5

2

20

12-0

2-2

3 2

1:5

6

20

12-0

2-2

3 2

2:0

0

20

12-0

2-2

3 2

2:0

4

20

12-0

2-2

3 2

2:0

8

20

12-0

2-2

3 2

2:1

2

20

12-0

2-2

3 2

2:1

6

20

12-0

2-2

3 2

2:2

0

20

12-0

2-2

3 2

2:2

4

20

12-0

2-2

3 2

2:2

8

20

12-0

2-2

3 2

2:3

2

20

12-0

2-2

3 2

2:3

6

20

12-0

2-2

3 2

2:4

0

20

12-0

2-2

3 2

2:4

4

20

12-0

2-2

3 2

2:4

8

20

12-0

2-2

3 2

2:5

2

20

12-0

2-2

3 2

2:5

6

20

12-0

2-2

3 2

3:0

0

20

12-0

2-2

3 2

3:0

4

20

12-0

2-2

3 2

3:0

8

20

12-0

2-2

3 2

3:1

2

20

12-0

2-2

3 2

3:1

6

20

12-0

2-2

3 2

3:2

0

20

12-0

2-2

3 2

3:2

4

20

12-0

2-2

3 2

3:2

8

20

12-0

2-2

3 2

3:3

2

20

12-0

2-2

3 2

3:3

6

20

12-0

2-2

3 2

3:4

0

20

12-0

2-2

3 2

3:4

4

20

12-0

2-2

3 2

3:4

8

20

12-0

2-2

3 2

3:5

2

20

12-0

2-2

3 2

3:5

6

20

12-0

2-2

4 0

0:0

0

20

12-0

2-2

4 0

0:0

4

20

12-0

2-2

4 0

0:0

8

20

12-0

2-2

4 0

0:1

2

20

12-0

2-2

4 0

0:1

6

20

12-0

2-2

4 0

0:2

0

20

12-0

2-2

4 0

0:2

6

Attention Seeking Emotion Information Opinion

So

nd

ag

gio

we

b

Min

eo

Be

lpie

tro

An

nu

nzia

ta

Be

lpie

tro

Is

ola

se

r p

ub

b

Cele

nta

no

Dari

o F

o

Fra

nca

Ram

e

Be

lpie

tro

A

nn

un

zia

ta

An

nu

nzia

ta / fa

rfa

llin

a

Di P

ietr

o

Page 19: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation
Page 20: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

RQ3. Can the Twitter activity be considered as a

good indicator of a TV show success? How can it be

compared with more traditional data such as the

number of viewer or the audience

share?

Page 21: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Tweet (21:00 – 00:30)

Tweet Originali

RT Url Tweet/RT

viewers - 0,15 - 0,06 - 0,25 - 0,30 0,58

Viewers Tweet activity correlation

Page 22: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

• There is a relativly small and extremly

active part of the audience following the

show on Twitter on a regular basis;

• The topics discussed by Twitter users are

strictly related to the contents of the

show;

• Is not possible to find a significative

correlation between the users activity on

Twitter and the audience of the show;

Conclusions:

Page 23: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Future works:

- Comparative analysis with types of

TV shows and other italian political

shows

- Developing an improved codebook

for Twitter TV viewing

- Evaluating more complex audience

previsional models

Page 24: Analyzing #serviziopubblico: networked publics, appointment based television and the structure of Twitter conversation

Acknowledgements

Thanks to Servizio Pubblico staff for

provinding both the detailed share and

structure of the whole season episodes;

Thanks to Mario Orefice for the help in

coding the data.