GIRAUD T. , UMS RIATE GRASLAND C. , UMR Géographie-cités LAMARCHE-PERRIN R. , LIG-MAGMA/MESCAL

1. ANR CORPUS GEOMEDIA (ANR-GUI-APP-04) IDENTIFICATION OF INTERNATIONAL MEDIA EVENTSBY SPATIAL AND TEMPORAL AGGREGATIONOF NEWSPAPERS RSS FLOWS Application to the case of the Syrian Civil Warbetween May 2011 and December 2012 GIRAUD T.,UMS RIATE GRASLAND C.,UMR Géographie-cités LAMARCHE-PERRIN R., LIG-MAGMA/MESCAL DEMAZEAU Y.,LIG-MAGMA VINCENT J.-M.,LIG-MESCAL « European Colloquium of Theoretical and Quantitative Geography  » Dourdan, 5-9 Sept. 2013

2. INTRODUCTION 2

3. L’exemple du Proche-Orient2006-2011

4. Media Flows & Geographical Links (1) A newspaper located in country i sends information about a country j RSS browser Direct geographical links

6. Media Flows & Geographical Links (2) A newspaper located in country i sends information about countries j and k RSS browser Indirect geographical links

7. COUNTRIES ASSOCIATED TO SYRIA IN RSS FLOWS FROM … Le Monde (FRA) International RSS Financial Times (GBR) World RSS Times of India (IND) World RSS Washington Post (USA) World RSS

8. I TIME ANALYSIS Which period of time are more or less focused on Syria according to RSS Flows ? 8

9. Syria Quotations over Time (week level) Le Monde The Times of India The Financial Times The Washington Post

10. Syria Quotations over Time (week level) Le Monde Frequency onthe whole period

11. Syria Quotations over Time (week level) Le Monde Frequency onthe whole period

12. Syria Quotations over Time (week level) Le Monde First meeting of theFriends of Syria Houlamassacre Violent clashes In Homs Frequency onthe whole period

13. Syria Quotations over Time (week level) Le Monde ? ? ? Frequency onthe whole period

14. Syria Quotations over Time (week level) Le Monde Frequency onthe whole period

15. Syria Quotations over Time (week level) Le Monde Battles of Damascusand Aleppo Siege of Homs Frequency onthe whole period

16. How to detect Macroscopic Eventsout of Weekly Results? Find homogeneous sub-periods in order to identify stable states Minimize the number of periods in order to reveal significant transitions Two measures that should be jointly optimized: Minimize the information loss Maximize complexity reduction Lamarche-Perrin R., Demazeau Y. and Vincent J.-M., 2013, “The Best-partitionsProblem: How to Build Meaningful Aggregations?” in Proceeding of the 12thConference on Intelligent Agent Technology, (IAT'13), Atlanta.

17. High Complexity Low Complexity Aggregation Data Aggregation Low Information Loss High Information Loss

18. Temporal Aggregationof Quotation Frequencies Frequency of Syria quotations in articles from Le Monde (week level) 0% information loss complexity reduction

19. Temporal Aggregationof Quotation Frequencies Frequency of Syria quotations in articles from Le Monde (week level) 1% information loss complexity reduction

20. Temporal Aggregationof Quotation Frequencies Frequency of Syria quotations in articles from Le Monde (week level) 5% information loss complexity reduction

21. Temporal Aggregationof Quotation Frequencies Frequency of Syria quotations in articles from Le Monde (week level) 10% information loss complexity reduction

22. Temporal Aggregationof Quotation Frequencies Frequency of Syria quotations in articles from Le Monde (week level) 20% information loss complexity reduction

23. Temporal Aggregationof Quotation Frequencies Frequency of Syria quotations in articles from Le Monde (week level) 30% information loss complexity reduction

24. Temporal Aggregationof Quotation Frequencies Frequency of Syria quotations in articles from Le Monde (week level) Siege of Homs Battles of Damascusand Aleppo Syrian armycounteroffensive Increasingrebel attacks 30% information loss complexity reduction

25. Temporal Aggregationof Quotation Frequencies Frequency of Syria quotations in articles from Le Monde (week level) 30% Civiluprise Armedinsurgenry Escalation Rebeloffensives information loss Ceasefireattempt Renewedfighting Battles ofDamascis& Aleppo complexity reduction Source: Wikipedia, "Syrian civil war"

26. Information Loss = 0% Le Monde The Times of India The Financial Times The Washington Post

27. Information Loss = 1% Le Monde The Times of India The Financial Times The Washington Post

28. Information Loss = 5% Le Monde The Times of India The Financial Times The Washington Post

29. Information Loss = 10% Le Monde The Times of India The Financial Times The Washington Post

30. Information Loss = 20% Le Monde The Times of India The Financial Times The Washington Post

31. Information Loss = 30% Le Monde The Times of India The Financial Times The Washington Post

32. Information Loss = 30% Le Monde The Times of India Battles of Damascusand Aleppo Battles of Damascusand Aleppo Battles of Damascusand Aleppo The Financial Times The Washington Post ?

33. Information Loss = 30% Irregular variationof media attention Le Monde The Times of India Irregular variationof media attention The Financial Times The Washington Post Significantmacro-variation Regular media attention

34. Outcome of time analysis An aggregation technique that: provides macro-representations of temporal variations detects events at different scales (weeks, months, years) gives global patterns to analyse newspapers behavior

35. II SPATIAL ANALYSIS Which countries are the most frequently associated to Syria in RSS flows ? 35

36. Countries associated to Syria in RSS flows Le Monde - International 36

37. Countries associated to Syria in RSS flows Financial Time - International 37

38. Countries associated to Syria in RSS flows The Washington Post - International 38

39. Countries associated to Syria in RSS flows The Times of India - International 39

40. Outcome of spatial analysis An inductive approach that reveals : Systematic association of Syria with neighboring countries involved in the conflict (Turkey, Lebanon, Jordan, …) Systematic association of Russia to Syrian conflict in all media (but not China …). Variable association of USA, France, Gulf countries, according to the different media.

41. III NETWORK ANALYSIS Can we identify a specific cluster of countries associated to Syrian Crisis ? 41

42. Transformation of raw matrix of links into matrix of dominant flows Country i is « dominated» by country j if i is associated the most frequently to j & j is more mentionned than i Dominant matrix of links Raw matrix of links

43. Dominant links of Le Monde (May 2013 – Dec. 2012) US region Network Map French region Syrian crisis Isr./Pal. conflict Comment • Division of the World between major French & US regions • Syrian conflict identified as specific region (with Russia) • Israel-Palestinian conflict as autonomous region

44. Dominant links of Financial Times (May 2013 – Dec. 2012) Isr./Pal. conflict US region Network Map Syrian crisis German region Comment • US as dominant world region with Chinese subregion • Syrian conflict identified as specific region (with Russia) • EU region dominated by Germany

45. Dominant links of The Washington Post (May 2013 – Dec. 2012) Fr Isr Pal Network Map Syrian crisis US region Comment • Major organisation of the world around US (and China) • Syrian conflict associated to neigbours (not Russia) • Israel-Palestinian conflict as autonomous region

46. Dominant links of Times of India (May 2013 – Dec. 2012) US region Network Map Cuba Comment • Vision of the world fully dominated by the US • Syrian conflict as sub region (Russia, Turkey, France) • Only Cuba-Venezuela escape from full US domination …

47. Outcome of network analysis A hierarchical clustering technique that: Provides macro-representations of international relations as reflected by associations in media news. Reveals the dominant position of USA in the international news and the variable importance of EU. Reveals the existence of local associations of countries related to geopolitical conflict or crisis (Syrian Crisis, but also Israel/Palestine, North/South Korea, …).

48. CONCLUSION Media as subjective projections of reality 48

49. Thank you for your attention http://geomediatic.net/ http://geomediatic.net/ http://gis-cist.fr 49