presented at the ECREA Conference in Istanbul, October 2012

1. #ECREA2012 27.10.2012
Katrin Jungnickel, TU Ilmenau
Axel Maireder, Universität Wien
Links to News on Facebook
Is There a Multi-Step Flow
of Communication?
Katrin Jungnickel
Axel Maireder 1

2. 30% of online Americans receive news via SNS,
6% via Twitter (Purcell et al., 2010)
71% of Canadian SNS users use it
to keep up with the news (Hermida et al., 2012)
28% of German SNS users get informed
about the news on SNS (BITKOM, 2011)
34% of German tweets with link
connect to news sites (Maireder, 2011)
Katrin Jungnickel
Axel Maireder 2

3. Two Twitter user groups: Intermediaries receive from
news media, others from intermediaries (Wu et al., 2011)
46% of media tweets reach users via intermediaries
(Wu et al., 2011)
Every media tweet gets retweeted 15 times (An et al., 2011)
Katrin Jungnickel
Axel Maireder 3

4. Two-Step-Flow online
The Impact of Strong and Weak Ties on the communication process
Discussion of politics often in homophilous
groups of strong ties (Schenk, 1995)
In SNS people are increasingly connected
to weak ties (deZuniga & Valenzuela, 2011)
Bridges important for diffusion of ideas (Granovetter, 1973)
Katrin Jungnickel
Axel Maireder 4

5. Is there a multi-step-flow of
communication on Facebook?
If yes, are weak or strong ties
more relevant?
Difference in interest dependent on
content, producer, transmitter?
Katrin Jungnickel
Axel Maireder 5

6. Snowball sample for
online survey: N=745
We asked respondents to
copy the last 5 links
received on Facebook, and
answer questions
connected (e.g interest in
content)
Katrin Jungnickel
Axel Maireder 6

7. Respondent Sample
75% of respondents (total: 745) copied links
n= 557
Facebook usage 67% several times daily
Gender 52% women
Country of origin 82% Germany
16% Austria
Education 62% Abitur/Matura
(Highschool degree)
36% University degree
Students 78%
Occupation related to media 42%
Mean age (18-55) 25
Mean number of Facebook friends (8-2769) 249
Katrin Jungnickel
Axel Maireder 7

8. 2653 Links,
2 coders
Variables:
- Data type
- Language
- Producer
- Content political?
- Content public issue?
Inter-coder-reliability (Holsti coefficient): >.70 for all variables
Katrin Jungnickel
Axel Maireder 8

9. Link Sample
Exclusion
n percent
Number of copied links 2635 100%
Link was not external/ just text -186 -7%
Link was dead -308 -12%
Link destination was in a language -71 -2%
other than German or English
Total amount of analyzed links 2070 79%
Katrin Jungnickel
Axel Maireder 9

10. Link Sample
Transmitters, Producers, Content
Katrin Jungnickel
Axel Maireder 10

11. Multi-Step-Flow?
Producers and transmitters of links
Producers
Transmitters
Katrin Jungnickel
Axel Maireder 11

12. Link Content
Transmitters and content of links
Transmitters
Content
Katrin Jungnickel
Axel Maireder 12

13. Interest in Links
Main effects on interest in links
Independent Variables F-Value Significance
Political content *** Interest higher in 28.433 .000
poltical content
Product information .721 .396
Public issue 1.553 .213
Producer 2.290 .058
Interest higher in
Transmitter *** 41.054 .000
links from strong ties
Language 1.496 .221
Additional information by transmitter 2.010 .156
Interest higher in text and pictures than in
Data type ** video/audio/apps and homepages 5.366 .001
Multi-factorial ANOVA, Model significant (p<.001), corrected R²= .135
Katrin Jungnickel
Axel Maireder 13

14. Interest in Links
Interest in links depends on transmitter and political content
High
interest
Transmitters
Low
interest
Significant interaction effect (p< .001) of content and transmitters
Katrin Jungnickel
Axel Maireder 14

15. Is there a multi-step-flow of
communication on Facebook?
Yes!
Katrin Jungnickel
Axel Maireder 15

16. Are weak or strong ties
more relevant?
Strong ties!
at least in terms of interest in the
content shared
Katrin Jungnickel
Axel Maireder 16

17. Difference in interest dependent on
content, producer, transmitter?
Transmitter
and political
content
Katrin Jungnickel
Axel Maireder 17

18. Thanks!
katrin.jungnickel@tu-ilmenau.de
axel.maireder@univie.ac.at
Katrin Jungnickel
Axel Maireder 18

19. References
An, J., Cha, M., Gummadi, K. P., & Crowcroft, J. (2011). Media landscape in Twitter: A world of new
conventions and political diversity. Association for the Advancement of Artificial Intelligence. Retrieved
from http://www.cl.cam.ac.uk/~jac22/out/twitter-diverse.pdf
BITKOM (2011). Soziale Netzwerk werden zum Informationskanal. Bundesverband Informationswirtschaft,
Telekommunikation und neue Medien e.V., November 28, 2011.
http://www.bitkom.org/70397_70419.aspx.
de Zuniga, H. G., & Valenzuela, S. (2011). The Mediating Path to a Stronger Citizenship: Online and Offline
Networks, Weak Ties, and Civic Engagement. Communication Research, 38(3), 397–421.
Granovetter, M. S. (1973). The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360–1380.
Hermida, A., Fletcher, F., Korell, D. & Logan, D. (2012). Share, Like, Recommend: Decoding the Social
Media News Consumer. Journalism Studies,13, 815-824.
Maireder, A. (2011). Links auf Twitter - Wie verweisen deutschsprachige Tweets auf Medieninhalte?
Retrieved from https://fedora.phaidra.univie.ac.at/fedora/get/o:64004/bdef:Content/get
Purcell, K., Rainie, L., Mitchell, A., Rosenstiel, T., Olmstead, K. (2010). Understanding the participatory
news consumer. How internet and cell phone users have turned news into social experience. Pew Internet
& American Life Project. Washington, D.C. Retrieved from:
http://infousa.state.gov/media/internet/docs/participatory-news-consumer.pdf
Schenk, M. (1995). Soziale Netzwerke und Massenmedien. Tübingen: Mohr Siebeck.
Wu, S., Hofman, J. M., Mason, W. A., & Watts, D. J. (2011). Who Says What to Whom on Twitter. WWW
'11, Hyderabad, India. Retrieved from http://research.yahoo.com/files/twitter-flow.pdf
Katrin Jungnickel
Axel Maireder 19