Detecting macro-patterns in the EU media sphere

Detecting Macro-patterns in the EU Mediasphere

ISL Seminars

Ilias Flaounas

University of Bristol

June 8, 2010

I. Flaounas (University of Bristol) June 8, 2010 1 / 16

Introduction

Traditionally, content analysis of news-media has been the domain ofresearch of social scientists.

But they have a lot oflimitations. They work:

with few news-media perstudy.

with small numbers ofnews-items.

in small time periods.

on a single country’smedia.

...


Examples

Examples of papers published in the recent issues of Journal ofCommunication:

“A total of 529 stories from NBC Nightly News and 322 stories airedon Special Report about Iraq, and 64 and 47, respectively, aboutAfghanistan were analyzed by two coders”S. Aday, “Chasing the Bad News: An Analysis of 2005 Iraq and Afghanistan War

Coverage on NBC and Fox News Channel”, J. of Com. 60, 144-164 (2010).


Examples

Examples of papers published in the recent issues of Journal ofCommunication:

“A total of 529 stories from NBC Nightly News and 322 stories airedon Special Report about Iraq, and 64 and 47, respectively, aboutAfghanistan were analyzed by two coders”S. Aday, “Chasing the Bad News: An Analysis of 2005 Iraq and Afghanistan War

Coverage on NBC and Fox News Channel”, J. of Com. 60, 144-164 (2010).

“Our corpus of data consisted of Channel 2s broadcasts on the eve ofMDHH between 7:30 p.m. and midnight in the years 1994-2007[...].All 278 items aired on the 14 examined evenings were coded.”O. Meyers et al. “Prime Time Commemoration: An Analysis of Television

Broadcasts on Israel’s Memorial Day for the Holocaust and the Heroism”, J. of

Com. 59, 456-480 (2009).


Example of Coding Scheme

These questionaires haveto be completedmanually.

Even more, typically morethan one coders have tocomplete the samequestionaires for the samenews items.


Nowadays...

Most media offer their content online in a convinient form.


Our Dataset

215 media outlets

over the 27 EU countries

in 22 different languages

for a 6 months period

A total of 1.3M newsarticles.


Our Dataset

215 media outlets

over the 27 EU countries

in 22 different languages

for a 6 months period

A total of 1.3M newsarticles.

What macro-patterns can be found using modern AI techniques?


The EU mediasphereCo-coverage network: We link two outlets if they share more stories thanexpected by chance (χ2

− scores).


The EU mediasphereCo-coverage network: We link two outlets if they share more stories thanexpected by chance (χ2

− scores).

This network has 203 nodes and 6702 edges.I. Flaounas (University of Bristol) June 8, 2010 7 / 16

A bit sparser....

This network has 197 nodes, 3386 edges and 3 connected components.Singleton nodes are omitted.


What kind of connected components are formed?



We go as sparse as possible with stopping criterion the modularitymaximization.The probability of two non-singleton outlets from the same country toend up in the same connected component is 82.9% (p < 0.001).Nationality is the major underline criterion of what stories mediaoutlets choose to publish.



We go as sparse as possible with stopping criterion the modularitymaximization.The probability of two non-singleton outlets from the same country toend up in the same connected component is 82.9% (p < 0.001).Nationality is the major underline criterion of what stories mediaoutlets choose to publish.

We will work on countries level rather than outlets level.


Which are the strongest connections between countries?


Which are the strongest connections between countries?

We go as sparse as possible while keeping the network connected.

This network has 27 nodes and 112 edges.


Can we explain relations of countries?



We found significant (p < 0.001) correlation of countries’ media-content

similarity to their:

Economical proximity — based on trade volume 31.03%






Cultural proximity — based on song contest votting patterns 32.05%






Cultural proximity — based on song contest votting patterns 32.05%

Geographical proximity — based on sharing of borders 33.86%


How ‘close’ countries really are, based on common media

interests?We use χ2-scores as similarities and project countries in a 2-D plane usingMultidimensional Scaling.


How ‘close’ countries really are, based on common media

interests?We use χ2-scores as similarities and project countries in a 2D plane usingMultidimensional Scaling.

We colour in blue the Eurozonemembers.

These countries are closer to thecenter, that is the averageEU-media content.


Ranking of countries

Based on their deviation from average EU media content (in 26D space).


Ranking of countries

Based on their deviation from average EU media content (in 26D space).

Rank Country Euro A.Year

1 France Y 19572 Austria Y 19953 Germany Y 19574 Greece Y 19815 Ireland Y 19736 Cyprus Y 20047 Slovenia Y 20048 Spain Y 19869 Slovakia Y 200410 Italy Y 195711 Belgium Y 195712 Luxembourg Y 195713 Bulgaria N 200714 Netherlands Y 1957

15 U. Kingdom N 197316 Finland Y 199517 Sweden N 199518 Poland N 200419 Estonia N 200420 Denmark N 197321 Portugal Y 198622 Malta Y 200423 Czech Republic N 200424 Romania N 200725 Latvia N 200426 Hungary N 200427 Lithuania N 2004


Any other important factors?

Correlations of countries deviation from average EU media content.

Factor Correlation (%) p-values

In Eurozone 70.65 <0.001





In Eurozone 70.65 <0.001Accession Year -49.32 0.009





In Eurozone 70.65 <0.001Accession Year -49.32 0.009GDP 2008 44.75 0.020





In Eurozone 70.65 <0.001Accession Year -49.32 0.009GDP 2008 44.75 0.020Population 23.05 0.247





In Eurozone 70.65 <0.001Accession Year -49.32 0.009GDP 2008 44.75 0.020Population 23.05 0.247Area 15.63 0.435





In Eurozone 70.65 <0.001Accession Year -49.32 0.009GDP 2008 44.75 0.020Population 23.05 0.247Area 15.63 0.435Population Density 7.45 0.712


Methods Summary

RSS parsing

Web page content scrapping

Statistical Machine Translation

Stemming, stop-words removal

Bag-of-words representation

Best Reciprocal Hit Clustering

Network construction

Multidimensional Scaling

Statistics...


Methods Summary

RSS parsing

Web page content scrapping

Statistical Machine Translation

Stemming, stop-words removal

Bag-of-words representation

Best Reciprocal Hit Clustering

Network construction

Multidimensional Scaling

Statistics...

Thank you!


Detecting macro-patterns in the EU media sphere

Data & Analytics

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