Trends

Trending in Italy
on Dec 4, 2023

The most searched Wikipedia pages in Italy: discover what people are looking for!

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  1. IT
    Macaulay Culkin
    - 1%
  2. IT
    Saint Barbara
    new
  3. IT
    Vendetta
    new
  4. IT
    Pornhub
    + 5%
  5. IT
    Błażej Augustyn
    new
  6. IT
    Facebook
    + 1%
  7. IT
    Alex Schwazer
    new
  8. IT
    Il metodo Fenoglio - L'estate fredda
    new
  9. IT
    SSC Napoli
    - 105%
  10. IT
    Enzo Tortora
    new
  11. IT
    There Is Still Tomorrow
    - 13%
  12. IT
    Guayana Esequiba
    new
  13. IT
    Brenda Song
    + 19%
  14. IT
    Napoleon
    - 86%
  15. IT
    Roberto Vannacci
    + 12%
  16. IT
    Elena Santarelli
    new
  17. IT
    Alessandro Meluzzi
    - 65%
  18. IT
    Guyana
    new
  19. IT
    Wrong Turn
    new
  20. IT
    Corrado Augias
    new
  21. IT
    murder of Elisa Claps
    new
  22. IT
    Federica Brignone
    + 3%
  23. IT
    K-19: The Widowmaker
    new
  24. IT
    The Inner Cage
    new
  25. IT
    Massimiliano Varrese
    new
  26. IT
    YouTube
    new
  27. IT
    RAI
    - 1%
  28. IT
    XNXX.com
    - 12%
  29. IT
    Paolo Calissano
    new
  30. IT
    Monster of Florence
    new
  31. IT
    Don Carlos
    - 13%
  32. IT
    La Sad
    - 120%
  33. IT
    The Time Machine
    new
  34. IT
    Autumn in New York
    new
  35. IT
    Frank Zappa
    new
  36. IT
    Brenda Lodigiani
    new
  37. IT
    Abbey of Santa Giustina
    + 2%
  38. IT
    Jalisse
    new
  39. IT
    Beatrice Luzzi
    new
  40. IT
    Belén Rodríguez
    - 228%
  41. IT
    Un professore
    - 9%
  42. IT
    Ale e Franz
    new
  43. IT
    Duván Zapata
    new
  44. IT
    Rocky Balboa
    new
  45. IT
    Italy
    - 6%
  46. IT
    INPS
    new
  47. IT
    Yann Sommer
    new
  48. EN
    Paolo Macchiarini
    - 79%
  49. IT
    Angelina Mango
    - 63%
  50. IT
    Grande Fratello, season 17
    new
Those data refers to the most visited pages on Wikipedia from Italy on Dec 4, 2023.
The green, red and yellow indicators on each row are based on data from the day before: to get insights about the historical records, click here.
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