Media Bias in German Online Newspapers

Media Bias in German Online Newspapers

Alexander DallmannDMIR – University of Würzburg

Florian Lemmerich (GESIS – Leibniz Institute for the Social Sciences)

Daniel Zoller (DMIR – University of Würzburg)

Andreas Hotho (DMIR – University of Würzburg)

Bias in Media

• Different types of bias:

– coverage bias

• count mentions of parties or representatives

– statement bias

• analyze similarity in vocabulary between newspapersand party manifestos

• perform sentiment analysis towards parties orrepresentatives

03.09.2015 Alexander Dallmann - Media Bias in German Online Newspapers 2

Motivation

– Analyze online news sites with regards to political bias• large number of articles available

• access to different news sites

• articles contain meta-information

– Articles contain information, they… • mention parties (SPD, CDU, …)

• mention representatives

• may express sentiment

• may use ideological terms similar to a party


The Dataset

Timeframe: 2009-10-27 - 2013-10-22

Sections: politics, economics


Site #articles 𝐥𝐞𝐧𝐠𝐭𝐡 party rep either title meta

faz.net 40 209 513.5 30.5% 24.5% 35.1% 4.1% 20.1%

spiegel.de 51 560 472.1 31.7% 30.6% 37.5% 6.0% 10.0%

taz.de 23 610 477.5 35.9% 27.6% 40.0% 2.5% 2.9%

zeit.de 17 926 445.5 36.6% 35.7% 43.2% 6.8% 32.3%

Average: 33 326 477.2 33.7% 29.6% 39.0% 4.9% 16.3%

• ~130 000 articles• up to 43% contain a reference to either a party or a representative

mentions

Coverage BiasStreit über Schulpflicht von Flüchtlingskindern: Gabriel bremst Bausewein

[…] Bausewein, der auch SPD-Chef in Thüringen ist, hatte in einem offenen Brief an Bundeskanzlerin Angela Merkel (CDU) und Ministerpräsident Bodo Ramelow (Linke) gefordert […]

Flüchtlingspolitik: Merkels wahre Bewärungsprobe[…] Die Kanzlerin hielt sich lange raus, überließ das Thema ihrem Innenminister Thomas de Maiziere(CDU). […]Am Sonntagabend wollte Merkel mit anderen Spiezenleuten von CDU und CSU im Kanzleramt beraten, wie es weitergehen soll. […]


CDU CSU SPD LINKE GRÜNE FDP

1 0 1 1 0 0


1 1 0 0 0 0


2 1 1 1 0 0

ExampleSite CDU CSU FDP Grüne Linke SPD 𝚺

faz.net 315 167 481 213 57 543 1776

spiegel.de 605 296 848 355 266 1007 3377

taz.de 104 28 120 127 99 146 624

zeit.de 224 118 381 147 90 369 1329


Site CDU CSU FDP Grüne Linke SPD

faz.net 17.7% 9.4% 27.1% 12.0% 3.2% 30.6%

spiegel.de 17.9% 8.8% 25.1% 10.5% 7.9% 29.8%

taz.de 16.7% 4.5% 19.2% 20.4% 15.9% 23.4%

zeit.de 16.9% 8.9% 28.7% 11.1% 6.8% 27.8%

Average 17.3% 7.9% 25.0% 13.5% 8.5% 27.9%

Articles with party acronym in title:

Normalized by row:

Results


Deviations from average:

Site CDU CSU FDP Grüne Linke SPD

faz.net +0.4 % +1.5 % +2.1 % -1.5 % -5.2 % +2.7 %

spiegel.de +0.6 % +0.9 % +0.1 % -3.0 % -0.6 % +1.9 %

taz.de -0.6 % -3.4 % -5.8 % +6.9 % +7.4 % -4.5 %

zeit.de -0.4 % +1.0 % +3.6 % -2.4 % -1.7 % -0.1 %

-8 0 8 16

faz.net

spiegel.de

taz.de

zeit.de

Acronyms in titles

SPD Linke Grüne FDP CSU CDU

• Observable differences in coverage whenlooking at articles that focus on a party

Results

-8 0 8

faz.net

spiegel.de

taz.de

zeit.de

Acronyms in full text



-8 0 8

faz.net

spiegel.de

taz.de

zeit.de

Representatives in full text


Statement Bias

• Vocabulary similarity

– Compare manifestos with newspapers

– Count occurences of ideological terms

• freedom, solidarity, … (Pappi, Seher and Kurella, 2011)

– Compare using cosine similarity


ResultsSite CDU FDP Grüne Linke SPD

faz.net 0.863 0.853 0.731 0.794 0.838

spiegel.de 0.808 0.802 0.756 0.831 0.833

taz.de 0.756 0.774 0.759 0.835 0.802

zeit.de 0.846 0.842 0.787 0.845 0.864


• taz.de • favours keywords from left manifestos

• faz.net • favours keywords from more conservative and liberal manifestos

Summary


• Dataset– 4 major german news sites– ~130.000 articles (4 year period)

• Coverage bias– observable through counting:

• party acronyms• representatives

– titles, text, keywords

• Statement bias– observable similarities in usage of ideological terms

• party manifestos• newspaper articles

Media Bias in German Online Newspapers

Alexander DallmannDMIR – University of Würzburg

[email protected]

Florian Lemmerich (GESIS – Leibniz Institute for the Social Sciences)

Daniel Zoller (DMIR – University of Würzburg)

Andreas Hotho (DMIR – University of Würzburg)

Coverage Bias

Articles that contain party acronym P:

𝑀𝑎𝑐𝑟 𝑃,𝑁 = | 𝑑 ∈ 𝑁: 𝑎𝑐𝑟 𝑃 ⊑ 𝐹(𝑑) |

Articles that contain representatives of Party P:

𝑀𝑚𝑒𝑚 𝑃,𝑁 = | 𝑑 ∈ 𝑁: (∃𝑚𝑃,𝑖 ∈ 𝑀 𝑃 :𝑚𝑃,𝑖 ⊑ 𝐹 𝑑 ) |


Summary

• Dataset:– 4 major german news sites– 4 year period– ~130 000 articles

• Coverage bias– Compare mentions of

• parties• representatives

– in:• title• text• keywords


• Statement bias: count keywords

• social, economics, …

compare counts of• party manifestos• news sites

Media Bias in German Online Newspapers

Data & Analytics

Transcript of Media Bias in German Online Newspapers