Austria and the Refugee Crisis: an Analysis of American Sentiment in Social Versus Print Media
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Austria and the Refugee Crisis: An Analysis of American Sentiment in Social versus Print Media Embassy of Austria to the United States 3524 International Court NW Washington, D.C. 20008 Proposal to: Dr. Hannes R. Richter, Ph.D. Deputy Director, Austrian Press & Information Service December 2016 Prepared by: Kristin Butts Margaret Ferrill (MPA, 2017) (MPA, 2017) [email protected] [email protected] [email protected] [email protected] Phone: 240-344-5793 Phone: 925-858-6600 Kristina Hummel Steve Ozinga (MPA, 2016) (MPA, 2017) [email protected] [email protected] [email protected] [email protected] Phone: 352-615-9977 Phone: 616-340-8771 Faculty Advisor: Dr. Dora Kingsley Vertenten University of Southern California Los Angeles, CA, USA “My God, this is the end of diplomacy!” - British Foreign Minister Lord Palmerston, upon receiving his first telegram in the 1840s i Table of Contents ii Table of Figures v Table of Tables vii Glossary of Quotations viii 1. Executive Summary 1 2. Issue Statement 2 2.1 The Syrian Refugee Crisis 3 2.1.1 The Syrian Refugee Crisis and Austria 4 2.2 American Media’s Portrayal of the Syrian Refugee Crisis 6 2.2.1 Polarization of Public Opinion 6 2.2.2 Lack of Credibility in Shared Social Media Content 7 2.3 Potential Concerns of Negative American Sentiment 8 2.3.1 Policy Impact 8 2.3.2 Economic Impact 9 2.3.3 Diplomatic Impact 9 2.4 Organizational Context 9 2.4.1 Current Political Climate in Austria 9 2.4.2 American Attitudes towards Immigration Policies 10 3. Purpose 12 3.1 Researchable Questions 12 4. Research Methodology 12 4.1 Mixed Methods Approach 12 4.2 Data Mining 15 4.2.1 Sampling 15 (A) Social Media 15 (1) Workflows 17 (B) Newspapers 17 4.3 Sentiment Analysis 18 4.3.1 Limitations 19 (A) Intercoder Reliability 19 4.4 Content Analysis 20 4.4.1 Limitations 21 4.5 Descriptive Statistics 23 4.5.1 Limitations 24 4.6 Technologies Utilized 25 4.6.1 Glossary of Technology Used 25 (A) Zoomph 25 (B) LexisNexis 26 (C) Lexalytics 26 4.7 Ethical Considerations 27 5. Report of the Data Collected 27 5.1 Data Mined 27 ii 5.1.1 Raw Data Results 28 (A) Social Media 28 (B) Newspapers 30 5.1.2 Content Sources of Concern and Credibility 39 (A) Social Media 39 (1) Prominent Users 39 (a) @v_of_Europe 40 (b) @jihadwatchRS 43 (c) @onlinemagazin 44 (d) @saul42 45 (e) @mailonline 46 (f) @slava381977 46 (g) @realalexjones 48 (h) @eeynouf 48 (i) @DavidJo52951945 50 (j) @_altright_ 50 (k) @SupportDonald 51 (l) @CutiePetunie 51 (2) Sources of links to stories shared 53 (B) Newspapers 54 5.1.3 Social Media Users and Newspaper Reader Demographics 54 (A) Social Media Users 54 (B) Newspaper Readers 57 5.2 Sentiment Analyzed 59 5.2.1 Raw Data Results 60 5.2.2 Common Phrases/Phrase Sentiment 62 (A) Top 20 Newspaper Phrases and Corresponding Sentiment 63 (B) Top 20 Social Media Phrases and Corresponding Sentiment 64 5.3 Content Analyzed 66 5.3.1 Raw Data Results 66 (A) Newspaper Content Themes 66 (B) Social Media Content Themes 67 5.3.2 Categories of Content 68 (A) Security Implications and Pro-Deportation Sentiment 68 (1) Pro-Deportation Sentiment on Social Media 69 (2) Border Control 72 (3) Turkey-Migrant Deal 73 (B) National Elections and Influence on Politics 74 (1) EU Relations 80 (C) Increase of Violence due to Refugee Influx 84 (1) Violence in Social Media Sentiment 85 (2) Accountability for Crimes 87 (3) Sexual Assault Themes Shared in Social Media 87 (4) Drug Related Crimes 90 iii (5) Overwhelming Attention to Violent Stories 91 (D) Humanizing the Crisis: Refugee/Migrant Personal Stories 93 (E) Financial Implications of the Refugee Crisis 95 (1) Cost of Refugees in Social Media Sentiment 95 (F) Additional Findings 97 6. Findings 99 6.1 Social Media is Repository of Negative Sentiment 99 6.2 Partisan Affiliation Aligns with Negative Sharing 100 6.3 Negative Social Media Sentiment is Directed Toward Refugees/Migrants 100 6.3.1 Religious Affiliations 101 6.4 Wide Divergence of Content in Sources 102 6.4.1 Social Media Content not Representative of Newspaper Content 102 6.4.2 How Americans Obtain News 102 (A) Ability of Traditional Media to Influence Public Opinion 103 (B) Ability of Social Media to Influence Public Opinion 103 (C) Self-Organizing/Swarming 104 (1) Retweeting 105 (2) Consequences/risks 105 (3) Examples 106 6.5 Applying Researchable Questions to Findings 106 6.5.1 American Sentiment 106 6.5.2 Current Trends 107 6.5.3 Parallels in Relation to U.S. Presidential Candidates 108 7. Recommendations 108 7.1 Press Outreach Expansion 109 7.2 To talk to Americans, tweeting is essential 110 7.3 Volume and Content Matters 111 7.4 Adjusting to New Paradigm 112 7.5 Nation Brand Strategies 113 8. Next Steps 114 9. Conclusion 114 References 116 Appendix A: List of 50 U.S. States for Zoomph Workflow 137 Appendix B: List of 50 Most Populated U.S. Cities for Zoomph Workflow 138 Appendix C: Full List of Zoomph Social Media Data with Lexalytics Sentiment Classification 142 Appendix D: List of Newspaper Summaries and Sentiment Classification 239 Appendix E: Newspaper Articles 247 iv Figures Figure 1: Condensed Timeline of the Syrian Refugee Crisis Figure 2: Wide Partisan Gap in Views of Immigrants’ Impact on U.S. Figure 3: Process for Sentiment and Content Analysis Figure 4: Social Bot Detection Settings Utilized in Zoomph Figure 5: Descriptive Statistics for Each Level of Measurement Figure 6: Common Statistical Terms and Their Definitions Figure 7: Twitter Profile of @v_of_europe Figure 8: Activity Level of Voice of Europe and Demographic Information of Voice of Europe’s Followers Figure 9: happygrumpy.com Analysis of User @v_of_europe Figure 10: Snapshot of @jihadwatchRS Twitter Profile Figure 11: Twitter Profile of @slava381977 Figure 12: @eeynouf Twitter Profile Figure 13: Twitter Profile of @SupportDonald Figure 14: Barb’s Associations on Twitter Figure 15: Activity Level of Barb and Demographic Information of Barb’s Followers Figure 16: Sources of Content Shared via Social Media Figure 17: Demographics for Newspaper Readership Figure 18: Average Gender of Authors Figure 19: Total Ethnicity of Authors Figure 20: Generation of Authors Figure 21: Total Sentiment Compared to Audience Reached Figure 22: Total Social Media Sentiment Figure 23: Zoomph Entity Sentiment Figure 24: Sentiment per Article, by Publication Figure 25: The New York Times Overall Sentiment Figure 26: The Washington Post Overall Sentiment Figure 27: Newspaper Phrase Sentiment and Count Figure 28: Percentage of Shares Based on Theme Figure 29: Snapshot of Story “Austria Fed Up, Plans to Deport 50,000 Syrian Migrants” Figure 30: Snapshot of Story “Austria says it plans to step up deportations of migrants” Figure 31: Deportation Story “Up to 90% of failed asylum seekers not deported from Austria” Figure 32: Deportation Story “#DalaiLama says ‘refugees’ need to go back home & rebuild their own countries” Figure 33: Tweet “Hans Breuer, Austria. Jew who operates regular illegal transports bringing non-white migrants into Central Europe” Figure 34: Snapshot of Story “frenzied Refugee shouts ‘Allahu Akbar’ as he throws himself in front of Car, Climbs Tram” Figure 35: Snapshot of Story “39,000 undocumented migrants and would-be asylum seekers caught in Austria in 9 months” Figure 36: Washington Post: “An ISIS defector or willing party?” v Figure 37: Washington Post: “Hungary intends to stop migrants with hunters near border wall” Figure 38: Washington Post: “A new age of walls” Figure 39: New York Times: “The World Waits and Wonders” Figure 40: New York Times: “Merkel Accepts Blame for Her Party’s Losses” Figure 41: Washington Post: “Trumps win may be just the beginning of a global populist wave” Figure 42: Los Angeles Times: “New German tone on migrants” Figure 43: Top Issues Among American Voters Figure 44: Most Commonly Used Entities in Relation of the U.S. Presidential Candidates Figure 45: Most Commonly Used Phrases in Relation of the U.S. Presidential Candidates Figure 46: Snapshot of Story “Over 11,000 asylum seekers listed as crime suspects in Austria” Figure 47: New York Times: “European Leaders, Reeling, Meet to Weigh Fallout of U.S. Election” Figure 48: New York Times: “After Trump Win, Parallel Path is Seen for French Right” Figure 49: Washington Post: “A year after Paris attacks, Europe’s extremism problem shows no signs of going away” Figure 50: Washington Post: “Europe’s anti-immigrant leaders are taking Trump’s show on the road” Figure 51: Story “European leaders gather in Austria for migration summit” Figure 52: Story “Balkan route nations say to focus on achievable ways to prevent new migrant influx: Vienna” Figure 53: Story “Austrian Foreign Minister Calls EU Refugees Resettlement Plan ‘Unrealistic’” Figure 54: Violence Story “Austria: afghan migrant beats a bottle in the face of a local boy. Escalated violence in Europe” Figure 55: Snapshot of Story “Teenage migrant who dragged 14 year old Austrian schoolgirl from toilet” Figure 56: Violence Story “Syrian asylum seeker in court on terror charges” Figure 57: Violence Story “Austria charges Muslim refugee with 20 counts of murder” Figure 58: Violence Story “Austrian Disgrace: No jail for Muslim migrant who dumped his own baby in the middle of the road after he got drunk” Figure 59: Snapshot of Story “Iraqi refugee who raped 10yo boy at Austrian swimming pool has conviction overturned” Figure 60: Snapshot of Story “Putin about Austria, after a migrant received no jail time for raping a young boy” Figure 61: Snapshot of Story “Austria: 15-year-old Muslim child migrant rapes, bites prostitute”