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Food and Culture

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Slides from my talk @Yahoo Labs in November 2014, Barcelona, Spain http://labs.yahoo.com/event/claudia-wagner-presents-food-and-culture/

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Food and Culture

  1. 1. Food and Culture CSS @GESIS Claudia Wagner GESIS & University of Koblenz 6nd Nov 2014, Yahoo Labs, Spain
  2. 2. 18.11.2014 Claudia Wagner 2
  3. 3. Research and Services at GESIS Survey Design and Methodology Computer Science and Information Science Raise the standards of surveys at all phases of the survey life cycle Gender studies, Political science (e.g., GLES), Values and Attitudes research (e.g. ALLBUS), ... Computational Social Science Knowledge Discovery, Information Retrieval, Information Extraction, … Social Science Research 18.11.2014 Claudia Wagner 3
  4. 4. CSS Agenda @GESIS Support traditional Social Science research with computational methods and tools Develop new instruments to tap into the potential of found data and crowds  building a telescope for the Social Sciences Online impacts offline! Build new algorithms and tools to shift the current configurations of societies towards better futures. PAST PRESENT FUTURE 18.11.2014 Claudia Wagner 4
  5. 5. Food 18.11.2014 Claudia Wagner 5
  6. 6. Data • Ichkoche.at ~ 470k Unique Users ~1 Mil. Page Impressions per week • Kochbar.de – 2,27 Mil. Unique User in July 2014 – 1.29 million Visits (12.1 Mio. PI) in December 2008 • Chefkoch.de – 11,05 Mil. Unique User in July 2014 – 28 Mio. Visits and 242 Mio. PI in December 2010 6 Sources: http://www.agof.de/aktuelle-studie-internet/#aktuellestudie http://www.ichkoche.at/data/repository/Keyaccount/ichkoche-oewaplus-q4-2012.pdf
  7. 7. Recipe Popularities 50000 40000 30000 20000 10000 0 18.11.2014 Claudia Wagner 7
  8. 8. Ingredient Popularities 120000 100000 80000 60000 40000 20000 0 18.11.2014 Claudia Wagner 8
  9. 9. Temporal Stability 18.11.2014 Claudia Wagner 9
  10. 10. (  )  t 10 Meat Carbohydrates Fish Vegetable Alcohol Normalized Access Volume per Weekday  t X Z
  11. 11. Ichkoche.at 18.11.2014 Claudia Wagner 11
  12. 12. kochbar.de 18.11.2014 Claudia Wagner 12
  13. 13. ichkoche.at 18.11.2014 Claudia Wagner 13
  14. 14. kochbar.de 18.11.2014 Claudia Wagner 14
  15. 15. ( ( ) ( )) 1 ( ) ( ) 15 Meat Carbohydrates Fish Vegetable Alcohol Change Rate per Weekday  F t F t i i       N j j j t F t F t R 1 1
  16. 16. Most Popular Recipes • Berlin: • Frankfurt: •• VKiieenl:na: 18.11.2014 Claudia Wagner 16
  17. 17. City Similarities 18.11.2014 Claudia Wagner 17
  18. 18. Bundesarchiv Bild 173-1282, Berlin, Brandenburger Tor, Wasserwerfer 18
  19. 19. Regional Similarities 18.11.2014 Claudia Wagner 19
  20. 20. Regional Similarities Berlin East West 18.11.2014 20 West East
  21. 21. Culture 18.11.2014 Claudia Wagner 21
  22. 22. Wikipedia 27 language communities 31 cuisines 22
  23. 23. Cultural Relations Similarity Understanding Affinity 18.11.2014 Claudia Wagner 23
  24. 24. Cultural Similarity sim(퐴, 퐵) = |퐴 ∩ 퐵| |퐴 ∪ 퐵| Jaccard similarity German cuisine Italian cuisine Wheat Beer Sauerkraut Riesling Pasta Sousage Tortano Pizza Parmigiano sim( , ) = 1 8 18.11.2014 Claudia Wagner 24
  25. 25. Cultural Similarity between Neighbors 18.11.2014 Claudia Wagner 25
  26. 26. Cultural Understanding Understanding 2 / 5 0 / 6 Understanding the Italian food culture Wikipedia edition Used concepts “Native” definition 18.11.2014 26
  27. 27. Cultural Understanding 18.11.2014 27
  28. 28. What may explain Cultural Understanding? • Create for each country a list of countries ranked by where most of its immigrants come from • Create for each country a list of countries ranked by how similar their values and beliefs are according to ESS Pair ρ (p-value) wiki – ess 0.18 (0.00019) wiki – migration 0.36 (1.74e-22) 28 Germany 18.11.2014 Claudia Wagner
  29. 29. Cultural Affinity • View statistics of cuisine pages in different language editions • How much more attention than we would expect does language community A pay to the culture of community B? 18.11.2014 29
  30. 30. Cross-cultural affinities But what explains them? GERMANY TURKEY de/tr/German Croatian (+(+0.1464) 0.0173) de/tr/French Serbian (+(+0.0850) 0.0114) de/tr/Italian Polish (+0.0051) 0.0114) de/Dutch (+0.0037) ρ=0.25 18.11.2014 30
  31. 31. What drives cross-cultural attention? Popularity Model Popularity-Affinity Model es it de es it de 18.11.2014 Claudia Wagner 31
  32. 32. What drives cross-cultural attention? Popularity Model Popularity-Affinity Model 18.11.2014 32
  33. 33. Self-Focus & Regional Bias 18.11.2014 Claudia Wagner 33
  34. 34. Summary • Affinities between language communities are present in Wikipedia and drive the attention process • Cultural understanding can to some extent be explained by migration • Cultural similarities inferred from Wikipedia are pretty plausible  crowdflower • Relation between similarity, understanding and affinities? – Understanding and affinity: -0.35 – Similarity and affinity: 0.27 – Similarity and understanding: 0.19 18.11.2014 Claudia Wagner 34
  35. 35. Thank you! Questions? Comments? Lunch? @clauwa claudiawagner.info claudia.wagner@gesis.org

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