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Multiplex Media Attention and Disregard Network among 129 Countries

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Presented in the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining ASONAM 2017 Sydney, Australia, 31 July - 03 August, 2017

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Multiplex Media Attention and Disregard Network among 129 Countries

  1. 1. Multiplex Media Attention and Disregard Network among 129 Countries Haewoon Kwak Jisun An Qatar Computing Research Institute Hamad Bin Khalifa University The 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining ASONAM 2017 Sydney, Australia, 31 July - 03 August, 2017
  2. 2. Outline • Paper title 101 • Motivation • Data collection - Unfiltered.news • Multiplex network analyses  ① ② ③ ④ ⑤ • Summary & future work
  3. 3. Multiplex Media Attention and Disregard Network among 129 Countries
  4. 4. Multiplex Media Attention and Disregard Network among 129 Countries Multiplex network? Media attention? Media disregard?
  5. 5. Multiplex Media Attention and Disregard Network among 129 Countries 3 Multiplex network? 1 Media attention? 2 Media disregard?
  6. 6. Media attention • What (news) media pay attention to • What news media report The NYTimes reports news about Trump The NYTimes pays attention to Trump NYTimes Trump 1
  7. 7. Media disregard • What (news) media do not pay attention to • What news media do not report • Key challenges: • How to distinguish what media did not know (and thus could not report) a certain incident from what media knew it but intentionally ignored it • We get insights from how news industry works. 2
  8. 8. How can news media report events happening at every corner of the world? • Open offices in every country and hire journalists there • Infeasible due to financial reasons • Is there anyone who gathers news reports from the world and sells “collected” news to news media again? • This is exactly what news agencies do.
  9. 9. Reasonable assumptions to capture media disregard • If many news media outlets report a certain incident, that piece of information was probably circulated by news agencies as well. • In this case, if there are news media outlets that do not report that incident, we can reasonably assume that they disregard it.
  10. 10. Multiplex network • A multilayer network is a network made up by multiple layers, each of which represents a given operation mode, social circle, or temporal instance. • In a multiplex network, each type of interaction between the nodes is described by a single layer network. Text from http://cosnet.bifi.es/network-theory/multiplex-networks/ Image from https://github.com/gajduk/social-networks-analysis-wan-bms 3
  11. 11. Multiplex Media Attention and Disregard Network among 129 Countries
  12. 12. Why is this interesting?
  13. 13. Critical role of news media • Even in the era of social media, our understanding of the world is still dominantly shaped by news media [2]*. *Reference number in the talk is the same as that in the paper. http://www.journalism.org/2016/07/07/pathways-to-news/
  14. 14. https://www.ted.com/talks/alisa_miller_shares_the_news_about_the_news
  15. 15. Bias in foreign news coverage • What we see, read, and hear about other countries is a result of the gatekeeping by the journalists and of the social, economic, and political relationships across countries [3]. ➡ Ideological discourses of hierarchy and inequality are articulated throughout the mediated representation [11]. ✓Understanding media attention is essential to detect bias in news media and make news better.
  16. 16. Previous literature on foreign news coverage • Theory of news values • Why some countries are more likely to be covered than other countries (e.g., USA, UK, China, …) • Systematic factors of international relationships • Why one country covers a certain country more than other countries (e.g., Japan frequently covers S. Korea)
  17. 17. Algeria Senegal SloveniaTunisia Luxembourg Bulgaria Italy Greece Bahrain Libya Morocco Palestine Lebanon Mauritania Ukraine Bosnia and Herzegovina Georgia Armenia Croatia Poland Estonia Serbia Latvia Slovakia Russia Netherlands Belarus Moldova Uzbekistan Azerbaijan Montenegro France Iran Cyprus Belgium Turkey Réunion Paraguay Dominican Republic Brazil Guyana Portugal Cuba Uruguay Jamaica Bolivia Barbados Costa Rica Venezuela El Salvador Mexico Trinidad and Tobago HondurasPhilippines Nicaragua Peru India Canada Spain Guatemala Pakistan Czech Republic Zimbabwe Bangladesh Uganda Kazakhstan Kyrgyzstan Sri Lanka Lithuania Kenya Thailand Vietnam Japan Fiji Macau Hong Kong Puerto Rico China New Zealand Angola Haiti Argentina Hungary United States of AmericaColombia Sweden Liechtenstein Nigeria Denmark United Kingdom Oman Qatar Kuwait Sudan United Arab Emirates Saudi Arabia Egypt Malta French Polynesia Romania Mali Germany Austria South Africa Syria Finland Switzerland Norway Cameroon Israel Yemen Iraq Jordan Australia Ecuador Panama Ireland Taiwan Malaysia Singapore Chile Nepal Limitations in previous work • Pairwise modeling is not enough to model complex nature of media attention among multiple countries.
  18. 18. Our approach • We build a multiplex media attention and disregard network (MADN) among countries and analyze its structural characteristics. Algeria Senegal SloveniaTunisia Luxembourg Bulgaria Italy Greece Bahrain Libya Morocco Palestine Lebanon Mauritania Ukraine Bosnia and Herzegovina Georgia Armenia Croatia Poland Estonia Serbia Latvia Slovakia Russia Netherlands Belarus Moldova Uzbekistan Azerbaijan Montenegro France Iran Cyprus Belgium Turkey Réunion Paraguay Dominican Republic Brazil Guyana Portugal Cuba Uruguay Jamaica Bolivia Barbados Costa Rica Venezuela El Salvador Mexico Trinidad and Tobago HondurasPhilippines Nicaragua Peru India Canada Spain Guatemala Pakistan Czech Republic Zimbabwe Bangladesh Uganda Kazakhstan Kyrgyzstan Sri Lanka Lithuania Kenya Thailand Vietnam Japan Fiji Macau Hong Kong Puerto Rico China New Zealand Angola Haiti Argentina Hungary United States of AmericaColombia Sweden Liechtenstein Nigeria Denmark United Kingdom Oman Qatar Kuwait Sudan United Arab Emirates Saudi Arabia Egypt Malta French Polynesia Romania Mali Germany Austria South Africa Syria Finland Switzerland Norway Cameroon Israel Yemen Iraq Jordan Australia Ecuador Panama Ireland Taiwan Malaysia Singapore Chile Nepal Macau Honduras Ireland Paraguay Chile Sudan Uzbekistan Israel Zimbabwe Iran Belgium Romania Nicaragua France Croatia Denmark Argentina Costa Rica Peru Finland Slovakia Réunion Iceland New Zealand Slovenia Portugal BarbadosEcuador Moldova Belarus Czech Republic Lebanon Bolivia Jordan Bosnia and Herzegovina Switzerland Libya El Salvador Senegal Austria Hungary Bulgaria Taiwan LithuaniaGuinea Canada Latvia Saudi Arabia Syria Australia Kazakhstan Yemen Egypt United Kingdom BangladeshSingapore Oman Netherlands Algeria Hong Kong China Malaysia Brazil India Ukraine Ghana Kuwait United Arab Emirates Palestine Iraq Morocco Malta Liechtenstein Uganda Zambia Azerbaijan Haiti Armenia Malawi Luxembourg South Africa Montenegro Uruguay Trinidad and Tobago GreeceJapan Serbia Sri Lanka Puerto Rico Nigeria Philippines Russia Turkey Jamaica Pakistan Dominican Republic Mali Nepal French Polynesia Guyana Angola Mauritania Italy Spain United States of America Estonia Venezuela Norway Vietnam Fiji Sweden Kenya Georgia Cameroon Kyrgyzstan Cuba Guatemala Poland Bahrain GermanyQatar Tunisia Cyprus Thailand Mexico South Korea Panama Indonesia Colombia Attention Disregard
  19. 19. Datasets we need • Collect news from many countries in the world • Handle English and non-English contents • Do not filter specific types of news
  20. 20. Candidate: GDELT? • The GDELT datasets http://www.gdeltproject.org/ • Supported by Google Jigsaw • Monitors news media around the world in over 100 languages • Actively studied in recent years [9] • Not appropriate for our work • Filters news according to predefined 300+ categories Two Tales of the World: Comparison of Widely Used World News Datasets GDELT and EventRegistry, Haewoon Kwak and Jisun An, ICWSM (4pg), 2016
  21. 21. Unfiltered.news • http://unfiltered.news run by Jigsaw
  22. 22. Why Unfiltered.news? • Retrieve data from Google News • Covers 100+ countries • Translate contents in major languages
  23. 23. Data collection • Over 212 days, for each country, we collect • Daily k topics mentioned more than other topics • Daily k topics mentioned less than news media in other countries mentioned (former definition is in the paper) ✴ 100 is the maximum number of topics that Unfiltered.news offers for a given day.
  24. 24. How to choose k • Considering human capacity for processing information*, we choose k=10. 0 50 100 150 200 0 10 20 30 40 50 60 70 80 90 100 k NumberofCountries No countries (k=100) without missing data 129 countries without missing data (k=10) Miller, George A. "The magical number seven, plus or minus two: some limits on our capacity for processing information." Psychological review 63.2 (1956): 81.
  25. 25. Build MADN NA: Attention network ND: Disregard network +
  26. 26. Modeling weighted directed network Country A Country B Topic 1 Topic 2 Topic 3 Country B Topic 5 … Topic 10 7 March 2016 Country B Topic 2 Topic 3 Topic 4 Topic 5 … Topic 10 10 March 2016 Topic 1 Topic 2 Topic 3 Topic 4 Topic 5 … Country B 12 April 2016 weight=3 The top 10 topics mentioned more in country A
  27. 27. Basic topological characteristics of MADN
  28. 28. Examining structures of MADN • Node level • Dyadic level • Triadic level • Community level • Network level Bottom-up manner
  29. 29. Node level: Country centrality
  30. 30. Country centrality Attention network Disregard network
  31. 31. Country centrality Small countries tend to report foreign news more
  32. 32. Country centrality The USA is placed in the brightest spotlight on the stage of the news world [3]
  33. 33. Country centrality Some countries appear in both
  34. 34. Country centrality A country has different news values for different countries
  35. 35. Dyadic level: Media attention bias Media attention asymmetry
  36. 36. Does one country pay attention to the other country at one time and disregard the same country at another time? Country A Country B Country A Country BND NA wA wD This shows the stability of news value of one country to another. Let’s look into the relationship between wA and wD.
  37. 37. Density plot of wA and wD 0 50 100 150 200 0 50 100 150 200 Link weight in NA LinkweightinND 1.000000 7.389056 54.598150 403.428793 2980.957987
  38. 38. Most of links have high weights in only one network 0 50 100 150 200 0 50 100 150 200 Link weight in NA LinkweightinND 1.000000 7.389056 54.598150 403.428793 2980.957987
  39. 39. News value of one country to another country is stable to some extent 0 50 100 150 200 0 50 100 150 200 Link weight in NA LinkweightinND 1.000000 7.389056 54.598150 403.428793 2980.957987 Media attention is less flexible and might have some country bias.
  40. 40. Characterizing a link by adding w A and -w D Country A Country B Country A Country B wA wD w = wA - wD w > 0: pay attention w = 0: no significant pattern w < 0: disregard
  41. 41. Relationship between two countries Country A Country B Country A Country B Country A Country B Country A Country B Country A Country B 1. exchanging attention 2. one-way attention 3. exchanging disregard 4. one-way disregard 5. exchanging attention & disregard
  42. 42. Relationship between two countries Country A Country B Country A Country B Country A Country B Country A Country B Country A Country B 1. exchanging attention 2. one-way attention 3. exchanging disregard 4. one-way disregard 5. exchanging attention & disregard 11.2% 22.9% 16.6% 40.1% 7.5%
  43. 43. Relationship between two countries Country A Country B Country A Country B Country A Country B Country A Country B Country A Country B 1. exchanging attention 2. one-way attention 3. exchanging disregard 4. one-way disregard 5. exchanging attention & disregard 11.2% 22.9% 16.6% 40.1% 7.5% More than a half of country relationships are unidirectional
  44. 44. Relationship between two countries Country A Country B Country A Country B Country A Country B Country A Country B Country A Country B 1. exchanging attention 2. one-way attention 3. exchanging disregard 4. one-way disregard 5. exchanging attention & disregard 11.2% 22.9% 16.6% 40.1% 7.5% Geographical neighbors are interested in each other.
  45. 45. Relationship between two countries Country A Country B Country A Country B Country A Country B Country A Country B Country A Country B 1. exchanging attention 2. one-way attention 3. exchanging disregard 4. one-way disregard 5. exchanging attention & disregard 11.2% 22.9% 16.6% 40.1% 7.5% Mainly led by coverage of China, Yemen, Saudi Arabia, or Ukraine
  46. 46. Relationship between two countries Country A Country B Country A Country B Country A Country B Country A Country B Country A Country B 1. exchanging attention 2. one-way attention 3. exchanging disregard 4. one-way disregard 5. exchanging attention & disregard 11.2% 22.9% 16.6% 40.1% 7.5% Relationships between some local hubs and global hub
  47. 47. Considering link weights can reveal rich dynamics Country A Country B 1. exchanging attention Country A Country B Country A Country B or or …
  48. 48. Algeria Senegal SloveniaTunisia Luxembourg Bulgaria Italy Greece Bahrain Libya Morocco Palestine Lebanon Mauritania Ukraine Bosnia and Herzegovina Georgia Armenia Croatia Poland Estonia Serbia Latvia Slovakia Russia Netherlands Belarus Moldova Uzbekistan Azerbaijan Montenegro France Iran Cyprus Belgium Turkey Réunion Paraguay Dominican Republic Brazil Guyana Portugal Cuba Uruguay Jamaica Bolivia Barbados Costa Rica Venezuela El Salvador Mexico Trinidad and Tobago HondurasPhilippines Nicaragua Peru India Canada Spain Guatemala Pakistan Czech Republic Zimbabwe Bangladesh Uganda Kazakhstan Kyrgyzstan Sri Lanka Lithuania Kenya Thailand Vietnam Japan Fiji Macau Hong Kong Puerto Rico China New Zealand Angola Haiti Argentina Hungary United States of AmericaColombia Sweden Liechtenstein Nigeria Denmark United Kingdom Oman Qatar Kuwait Sudan United Arab Emirates Saudi Arabia Egypt Malta French Polynesia Romania Mali Germany Austria South Africa Syria Finland Switzerland Norway Cameroon Israel Yemen Iraq Jordan Australia Ecuador Panama Ireland Taiwan Malaysia Singapore Chile Nepal Backbone extraction [16] • Applying disparity filter proposed by [16] and extracting significant links (called a “backbone”)
  49. 49. Link characterization by: 1. Is the link from ci to cj significant to ci compared to other links from ci? 2. Is the link from ci to cj significant to cj compared to other links to cj? ci cj ci cj 1. significant to ci? 2. significant to cj?
  50. 50. Relationship characterization by: ci cj ci cj ci cjci cj 1. Lij is significant to ci? 2. Lij is significant to cj? 3. Lji is significant to cj? 4. Lji is significant to ci?
  51. 51. Findings by relationship characterization in N A • Most of the country relationships (91.2%) are non-significant for both-countries. • Neighboring countries tend to show a strong dependency of media attention. • Hub countries get the significant media attention but do not return back well. • Former colonial ties show dependent relationships. • While the US (1st) and Syria (2nd) have similar PageRank, they receive significant media attention from 53 and 11 countries, respectively.
  52. 52. Triadic level: Motif analysis
  53. 53. Network motif • (Usually 3- or 4-) sized subgraphs that repeat in a given network
  54. 54. Proportions of each motif are different according to the types of networks Superfamilies of Evolved and Designed Networks Ron Milo, Shalev Itzkovitz, Nadav Kashtan, Reuven Levitt, Shai Shen-Orr, Inbal Ayzenshtat,Michal Sheffer, Uri Alon Science, 303(5663), 2004
  55. 55. Well-known names of each motif Feed forward loop (FFL)Fan-out Cascade Fan-in Fully connected triad Double feedback loop
  56. 56. Motif profiles of NA and ND
  57. 57. Motif profiles of NA and ND Two networks are structurally very different
  58. 58. Motif profiles of NA Transitive hierarchy is found. (If A->B and B->C, then A->C) Feed forward loop (FFL)
  59. 59. Motif profiles of ND Led by star-shaped subnetworks Fan-out Fan-in
  60. 60. Motif profiles of ND Transitivity does not hold in ND Cascade
  61. 61. Significant colored motifs in MADN Attention Disregard Complex & asymmetric nature of MADN Attention only Disregard only
  62. 62. Community level: Global village and unique blocks
  63. 63. Communities in N A found by InfoMAP [21]
  64. 64. Global village trend is found in media attention 83 countries are in one big community
  65. 65. Some small communities MENA Russia & Neighbors Southern Asia Southern Europe North Africa Southern Asia
  66. 66. Interestingly, Qatar is in a global village not in a MENA cluster Qatar Yemen UAESaudi Arabia Egypt Bahrain Kuwait Sudan
  67. 67. Huntington’s civilizational divides [22] Western Orthodox Islamic African Latin American Hindu Buddhist Sinic Japanese
  68. 68. Some alignment between two divisions but a global village [animated gif]
  69. 69. Communities in N D found by InfoMAP [21] • We found only one community that contains all the countries, meaning that there is no group of countries that disregard/are disregarded each other.
  70. 70. Network level: Node2Vec [24]
  71. 71. t-SNE visualization of vector representations of nodes in N A Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bahrain Bangladesh Barbados BelarusBelgium Bolivia Bosnia and Herzegovina Brazil Bulgaria Cameroon Canada Chile China Colombia Costa Rica Cr atia Cuba Cyprus Czech Republic Denmark Dominican Republic Ecuador Egypt El Salvador Estonia Fiji Finland France French Polynesia Georgia Germany Ghana Greece Guatemala Guinea Guyana Haiti Honduras Hong Kong HungaryIceland Ind Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kuwa Kyrgyzstan Latvia Lebanon Libya Liechtenstein Li uania Luxembourg Macau Malawi Malaysia Mali Malta Mauritania Mexico Moldova Montenegro MoroccoNepal Netherlands New Zealand Nicaragua Nigeria Norway Oman Pakistan Palestine Panama Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania Russia Réun n udi A abia Senegal Serbia Singapore Slov kia Slovenia South Africa South Korea Spain Sri Lanka Sudan Sweden Switzerland Syria Taiwan Thailand Trinidad and Tobago Tunisia Turkey Uganda Uk aine United Arab Emirates United Ki dom ited States f merica Uruguay Uzbekistan Venezuela Vietn m Yemen Zambia Zimbabwe
  72. 72. Global village trend is reconfirmed Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bahrain Bangladesh Barbados BelarusBelgium Bolivia Bosnia and Herzegovina Brazil Bulgaria Cameroon Canada Chile China Colombia Costa Rica Cr atia Cuba Cyprus Czech Republic Denmark Dominican Republic Ecuador Egypt El Salvador Estonia Fiji Finland France French Polynesia Georgia Germany Ghana Greece Guatemala Guinea Guyana Haiti Honduras Hong Kong HungaryIceland Ind Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kuwa Kyrgyzstan Latvia Lebanon Libya Liechtenstein Li uania Luxembourg Macau Malawi Malaysia Mali Malta Mauritania Mexico Moldova Montenegro MoroccoNepal Netherlands New Zealand Nicaragua Nigeria Norway Oman Pakistan Palestine Panama Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania Russia Réun n udi A abia Senegal Serbia Singapore Slov kia Slovenia South Africa South Korea Spain Sri Lanka Sudan Sweden Switzerland Syria Taiwan Thailand Trinidad and Tobago Tunisia Turkey Uganda Uk aine United Arab Emirates United Ki dom ited States f merica Uruguay Uzbekistan Venezuela Vietn m Yemen Zambia Zimbabwe Mix of different regions
  73. 73. However, geographical proximity also matters in media attention Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bahrain Bangladesh Barbados BelarusBelgium Bolivia Bosnia and Herzegovina Brazil Bulgaria Cameroon Canada Chile China Colombia Costa Rica Cr atia Cuba Cyprus Czech Republic Denmark Dominican Republic Ecuador Egypt El Salvador Estonia Fiji Finland France French Polynesia Georgia Germany Ghana Greece Guatemala Guinea Guyana Haiti Honduras Hong Kong HungaryIceland Ind Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kuwa Kyrgyzstan Latvia Lebanon Libya Liechtenstein Li uania Luxembourg Macau Malawi Malaysia Mali Malta Mauritania Mexico Moldova Montenegro MoroccoNepal Netherlands New Zealand Nicaragua Nigeria Norway Oman Pakistan Palestine Panama Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania Russia Réun n udi A abia Senegal Serbia Singapore Slov kia Slovenia South Africa South Korea Spain Sri Lanka Sudan Sweden Switzerland Syria Taiwan Thailand Trinidad and Tobago Tunisia Turkey Uganda Uk aine United Arab Emirates United Ki dom ited States f merica Uruguay Uzbekistan Venezuela Vietn m Yemen Zambia Zimbabwe Group of countries in the same region
  74. 74. t-SNE visualization of vector representations of nodes in N D Algeria Argentina Armenia Australia Austria Azerbaijan Bahrain Bangladesh Belarus Be gium Bolivia Bosnia and Herzegovina Brazil Bulgaria Cameroon Canada Chile China Colombia Costa RicaCroatia Cuba Cyprus Czech Republic Denmark Dominican Republic Ecuador Egypt El Salvador Estonia Finland France Georgia Germany Ghana Greece Guatemala Honduras Hong Kong Hungary India Indonesia Iran Iraq Ireland Isra Italy Jamaica pan Jordan Kazakhstan Kenya Kuwait Kyrgyzstan Latvia Lebanon Libya Liechtenstein Lithuania Luxembour Macau Malaysia Malta Mexico Moldova Montenegro Morocco Nepal Netherlands New Zealand Nicaragua Nigeria Norw y Oman Pakistan Palestine Panama Paraguay Peru Philippines PolandPort a Puerto Rico Qatar Romania Russ a Réunion Sau Arabia Senegal Serbia Singapo Slovakia Slovenia South Africa South Korea Sp n Sudan SwedenSwitzerland Syria Taiwan Thailand Tunisia Turkey Ukraine United Arab Emirate Un ed Ki dom United States of America Uruguay Venezuela Vie nam Yemen Zimbabwe
  75. 75. No correlation between media disregard and geographical proximity Algeria Argentina Armenia Australia Austria Azerbaijan Bahrain Bangladesh Belarus Be gium Bolivia Bosnia and Herzegovina Brazil Bulgaria Cameroon Canada Chile China Colombia Costa RicaCroatia Cuba Cyprus Czech Republic Denmark Dominican Republic Ecuador Egypt El Salvador Estonia Finland France Georgia Germany Ghana Greece Guatemala Honduras Hong Kong Hungary India Indonesia Iran Iraq Ireland Isra Italy Jamaica pan Jordan Kazakhstan Kenya Kuwait Kyrgyzstan Latvia Lebanon Libya Liechtenstein Lithuania Luxembour Macau Malaysia Malta Mexico Moldova Montenegro Morocco Nepal Netherlands New Zealand Nicaragua Nigeria Norw y Oman Pakistan Palestine Panama Paraguay Peru Philippines PolandPort a Puerto Rico Qatar Romania Russ a Réunion Sau Arabia Senegal Serbia Singapo Slovakia Slovenia South Africa South Korea Sp n Sudan SwedenSwitzerland Syria Taiwan Thailand Tunisia Turkey Ukraine United Arab Emirate Un ed Ki dom United States of America Uruguay Venezuela Vie nam Yemen Zimbabwe Mix of different regions
  76. 76. Summary • We investigate the structural characteristics of the multiplex media attention and disregard network (MADN) among 129 countries. • Through multi-level analysis from the node level to the network level, we found the skewed, hierarchical, and asymmetric structure of the MADN. • Media attention and disregard have different structures. • We observe the “global village” trend in media attention, but, at the same time, unique attention blocks remain.
  77. 77. Future work • “Media attention” is somewhat led by media, editors, and journalists (professional organization). • We would like to compare this with the worldview of typical users collected from social media. • Also, we plan to compare media attention network to country networks based on other data sources (migration, flight, trade).
  78. 78. @haewoon http://haewoon.io @JisunAn http://jisun.me https://arxiv.org/abs/1707.04941

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