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1 EU COHESION POLICY IN THE PUBLIC SPHERE: HOW DO THE MEDIA FRAME EU COHESION POLICY? Results from the COHESIFY media analysis VasilikiTriga Cyprus University of Technology COHESIFY Final Conference, Brussels 26 April, 2018 The COHESIFY project (February2016-April 2018) has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 693127

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Page 1: EU COHESION POLICY IN THE PUBLIC SPHERE: HOW DO THE … · 1.8 2.5 4.0 4.2 6.3 7.8 7.8 8.7 9.3 9.9 10.6 11.5 12.4 21.7 0 5 10 15 20 Hungary Ireland UK Netherlands Greece Slovenia

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EU COHESION POLICY IN THE PUBLIC SPHERE: HOW DO THE MEDIA FRAME EU COHESION POLICY?

Results from the COHESIFY media analysis

Vasiliki TrigaCyprus University of Technology

COHESIFY Final Conference, Brussels 26 April, 2018

TheCOHESIFYproject(February2016-April2018)hasreceivedfundingfromtheEuropeanUnion’sHorizon2020researchandinnovationprogrammeundergrantagreementNo.693127

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Footnotes1 Reactions: number of comments, retweets, likes, shares...etc.

Overview of Cohesify dataset

Cohesify Universe Volume Reactions1 Unique Users

Web media articles (11 lang) 33,842 N/A N/A

Framing Analysis

Stratified sample (11 lang) 2,714 N/A N/A

Computational Analysis (ENG/ES)

Web media articles 4,092 33,183 N/AUser Comments 33,183 N/A 7,945Social Media (Facebook) 3,601 60,132 2,321Social Media (Twitter) 19,653 37,886 13,298

Table: Dataset Overview

1

Reactions: number of comments, retweets, likes, shares...etc.,.

Carlos MendezUniversity of Strathclyde Add title of presentation here

Cohesify meeting:Brussels, March 23 4 /

22

MEDIA DATASET: Overview

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1 FRAMING ANALYSIS

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How is Cohesion Policy FRAMED in the news?

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Job creation Development Research & InnovationFinancial Burden

FRAMES

Environment Social justice Public services Infrastructure

Cultural heritage Cultural development

Mismanagement of fundsBureaucracy Fail to inform public/applicantsRestore order

1 2ECONOMIC CONSEQUENCES

QUALITY OF LIFE CULTURE

3INCOMPETENCE OF LOCAL GOVERNANCE

4

SUBFRAMES

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Political Leverage Political CapitalEmpowerment

FRAMES

External relations Tackling brain drain Sovereignty

Civic participation/CollaborationSocial Awareness Solidarity

Corruption Fraud

5 6

POWER NATIONAL INTERESTS

COHESION

7

MISUSE OF FUNDS

8

SUBFRAMES

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Are the dominant frames POSITIVE or NEGATIVE?

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Cohesion policy mainly framed in terms of economic gains (34%),

and impact on citizens’ everyday lives (27%)

13.4%

34.2%

27.3%

4.1%

9.0%

4.1%1.0%

2.9%3.8%

0%

5%

10%

15%

20%

25%

30%

35%

40%

NoframeEconomicconsequences(Frame1)

Quality oflife(Frame2)

Culture (Frame3)Incompetence oflocal/ nationalauthorities(Frame4)

Power(Frame5)NationalInterests(Frame

6)

Cohesion (Frame7)

Fundabuse(Frame8)

(Allcases, n=2714)

The negative frames are less frequent: ‘Incompetence’ (9%),

‘Power’ (5%) and ‘Fund Misuse’ (4%)

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COMPARATIVE ANALYSIS:THE DOMINANT FRAMES

9

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12.5 17.9 18.3 20.2 21.5 21.7 21.8 24.3 27.9 31.142.2 43.2 46.9 49.2

0.010.020.030.040.050.060.0

Qualityoflife(Frame2)

22.3 22.8 25.7 27.6 29.7 30.3 31.1 31.5 32.1 33.342.3 47.2 47.6

54.7

0102030405060

EconomicConsequences(Frame1)

The key positive and dominant frames are especially prevalent in Sl, CY, IE & UK, NL, IT

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COMPARATIVE ANALYSIS:THE NEGATIVE FRAMES

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1.8

2.5

4.0

4.2

6.3

7.8

7.8

8.7

9.3

9.9

10.6

11.5

12.4

21.7

0 5 10 15 20

Hungary

Ireland

UK

Netherlands

Greece

Slovenia

Cyprus

Italy

Total

European/…

Spain

Germany

Poland

Romania

Incompetenceoflocal/nationalauthorities(Frame4)

.6%

1.3%

2.3%

2.5%

2.5%

3.2%

3.6%

4.0%

4.7%

5.4%

5.5%

6.7%

7.2%

12.9%

0% 5% 10% 15%

Cyprus

Hungary

Poland

Ireland

Greece

Italy

UK

Total

Slovenia

Netherlands

Romania

Germany

Spain

European/…

Power(Frame5)

‘Incompetence’ frame is twice higher than average in Romania

‘Power’ frame by EU media is3 times higher than average -

Emphasis on political bargaining

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COMPARATIVE ANALYSIS:THE LEAST SALIENT FRAMES

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0%

0%

0%

.4%

.4%

.5%

.8%

.8%

.8%

1.0%

1.2%

1.3%

2.9%

3.1%

0% 1% 2% 3% 4%

Ireland

Cyprus

European/…

Romania

Hungary

Italy

Poland

UK

Greece

Total

Netherlands

Spain

Germany

Slovenia

NationalInterests(Frame6)

0%

0%

.3%

.5%

.8%

.9%

1.6%

2.2%

2.5%

2.7%

2.8%

5%

6%

20.2%

0% 5% 10% 15% 20%

Spain

Cyprus

Poland

Italy

Greece

Romania

Slovenia

Hungary

Ireland

Total

UK

European/…

Netherlands

Germany

Cohesion(Frame7)

0%

0%

.4%

.5%

1%

1.9%

2.3%

2.4%

3.4%

5.1%

8.9%

8.9%

10.2%

10.7%

0% 5% 10% 15%

Ireland

Cyprus

Greece

Slovenia

Poland

Germany

Italy

UK

Total

Spain

European/…

Romania

Hungary

Netherlands

Fundabuse(Frame8)

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TOWARS EU IDENTITY THROUGH POSITIVE NEWS?

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89%

79% 78%75%

69%62%

56% 55%48%

37%

25%

16%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

PositiveNewsValence

Positive EU news promotes a sense belonging in a community

Majority of news is positive in most cases….

… less than 50% in some cases (EU media, DE, IT, RO) – but large neutral (factual) component, not negative

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TOWARS EU IDENTITY THROUGH EUROPEANISED NEWS?

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58%

20%19%

12% 12% 11%8% 8%

4% 3% 3% 3%

0%

10%

20%

30%

40%

50%

60%

70%

EuropeanisationofNews

The EU dimension of news contributes to a European public sphere

But only European media presents news from a European perspective

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FRAMING: Conclusions

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The media does frame Cohesion Policy - shaping the way EU is understood, interpreted & evaluated 1

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FRAMING: Conclusions

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Cohesion Policy frames are rich & diverse2

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FRAMING: Conclusions

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The framing of Cohesion Policy is positiveoverall (Economic consequences, Quality of life)3

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FRAMING: Conclusions

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But Europeanised discourse is low (nationalised discourses)4

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FRAMING: Conclusions

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Regional media frame positively (effects on daily lives), national media focus more on criticism against the national government5

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2 COMPUTATIONAL TEXT ANALYSIS

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COMPUTATIONAL TEXT ANALYSIS:Online news and social media

TopicmodellingDiscoverstopicsfromtextdocuments(e.g.newsarticles,tweets,posts,etc.)andcanhandle‘bigdata’

SentimentanalysisOpinionminingapproachtodeterminepolarityoftext(positive,negativeorneutral)usingadictionaryofwords

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NEWS MEDIA: Topics & proportions

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Figure: Estimates of topic proportions based on structural topic model (n=4.092) Topics have been assigned short labels for facilitating interpretability.

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THE TERRITORIAL DIMENSION: National vs regional news focus

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Figure: Logit estimates of effect size of changing from one category to another. Note: Error bars that do not overlap with the zero line are statistically significant. Positive coefficients mean that the topic receives more emphasis at the “national” level, while negative coefficients imply that the regional level emphasises the topic more.

Estimated e↵ects: From Regional to National

(a) Spain (b) UK

Figure: Add further explanation of e↵ects estimates

Carlos MendezUniversity of Strathclyde Add title of presentation here

Cohesify meeting:Brussels, March 23 8 /

22

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NEWS MEDIA: Sentiment analysis

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News media: Comparison of sentiment across levels

Figure: Comparison of sentiment per territorial level. The sentiment analysis wasperformed on the English language sources, which means that the “Regional” and“National” levels refer to those in the UK.

Carlos MendezUniversity of Strathclyde Add title of presentation here

Cohesify meeting:Brussels, March 23 10

/ 22

Figure: Comparison of sentiment per territorial level. The sentiment analysis was performed on the English language sources, which means that "Regional" and "National" refer to UK

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USER COMMENTS: International

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Figure:SentimentanalysisofUserCommentsfrominternational-focusedmedia.

User Generated Content (USG): International

Figure: Sentiment analysis of UGC from international-focused media. Note: Mostof the facebook coverage appears to be neutral, although it is punctuated by afew negative posts/commentary

Carlos MendezUniversity of Strathclyde Add title of presentation here

Cohesify meeting:Brussels, March 23 12

/ 22

Most commentary is neutral, though punctuated by NEGATIVE COMMENTARY

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USER COMMENTS: UK

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Figure: Sentiment analysis of User Comments from UK media.

Most of the sentiment associated with USER COMMENTS is negative, especially for the Daily Mail

User Generated Content (USG): UK

Figure: Sentiment analysis of UGC from UK media. Note: Most of the sentimentassociated with UGC is negative, especially for the Daily Mail

Carlos MendezUniversity of Strathclyde Add title of presentation here

Cohesify meeting:Brussels, March 23 13

/ 22

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FACEBOOK (ENG): Activity stats

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Figure: Evolution of Facebook activity statistics over time

Facebook: English

Figure: Coverage of meta-statistics over time. Note: From roughly 2012-2013,levels of FB activity steadily increase over time

Carlos MendezUniversity of Strathclyde Add title of presentation here

Cohesify meeting:Brussels, March 23 14

/ 22

From 2012-2013, levels of FB activity are steadily INCREASING.

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FACEBOOK: Sentiment analysis of Facebook posts

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Most sentiment is NEUTRALor POSITIVE

MORE POSITIVE posts in Spanish than English

Facebook: Sentiment analysis

(a) English

(b) Spanish

Figure: Sentiment analysis of Facebook posts. Note most sentiment detected iseither neutral or positive

Carlos MendezUniversity of Strathclyde Add title of presentation here

Cohesify meeting:Brussels, March 23 17

/ 22

Facebook: Sentiment analysis

(a) English

(b) Spanish

Figure: Sentiment analysis of Facebook posts. Note most sentiment detected iseither neutral or positive

Carlos MendezUniversity of Strathclyde Add title of presentation here

Cohesify meeting:Brussels, March 23 17

/ 22

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TWITTER (ES): Topic proportions & sentiment

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12,7K tweets in Spain (compared to 7,3K in UK)

BUT NEED MORE TIME!

Figure: Sentiment analysis of tweets.

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COMPUTATIONAL ANALYSIS: Conclusions (i)

Large variation across 3 cases in Cohesion Policy topic emphasisand coverage

Topics mirror thematic Objectives and broader EU political themes,e.g. Conditionality & EU affairs/Brexit & Irregularities

Significant territorial differences in topic emphasis & sentimentanalysis e.g. EU affairs focus at national level

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COMPUTATIONAL ANALYSIS: Conclusions (ii)

News comments contain more negative sentiment (esp. UK)

Facebook activity increasing over time, but most sentiment neutral- not surprising as mostly about objective information

Twitter analysis reveals also neutral sentiment

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THANKS FOR YOUR ATTENTION!ANY QUESTIONS ?

[email protected]