Trends

Trending in Italy
on Nov 14, 2023

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

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  1. IT
    Walter Mazzarri
    + 97%
  2. IT
    Circeo Massacre
    new
  3. IT
    Jannik Sinner
    + 90%
  4. IT
    Novak Djokovic
    + 82%
  5. IT
    ATP Finals
    + 55%
  6. IT
    Circeo
    new
  7. IT
    Angelo Izzo
    new
  8. IT
    Andrea Ghira
    new
  9. IT
    Gianni Guido
    new
  10. IT
    Igor Tudor
    - 176%
  11. IT
    Rudi Garcia
    + 23%
  12. IT
    Suburræterna
    new
  13. IT
    SSC Napoli
    + 49%
  14. IT
    murder of Elisa Claps
    - 11%
  15. IT
    Innichen
    new
  16. IT
    Checco Zalone
    new
  17. IT
    tennis scoring system
    new
  18. IT
    Facebook
    + 19%
  19. IT
    Ken Miles
    new
  20. IT
    Suburra: Blood on Rome
    new
  21. IT
    Sexten
    new
  22. IT
    Paola Cortellesi
    - 45%
  23. IT
    Adriano Panatta
    new
  24. IT
    Tina Lagostena Bassi
    new
  25. IT
    Blade Runner 2049
    new
  26. IT
    San Vincenzo
    new
  27. IT
    Vinicio Capossela
    new
  28. IT
    Greta Scarano
    new
  29. IT
    tiebreaker
    new
  30. IT
    The Damned of Pizzofalcone
    - 27%
  31. IT
    Shooter
    new
  32. IT
    Ford v Ferrari
    new
  33. IT
    Federico Dimarco
    - 165%
  34. IT
    Matteo Berrettini
    new
  35. IT
    Pornhub
    - 16%
  36. IT
    Daniel Boloca
    new
  37. IT
    Rafael Nadal
    new
  38. IT
    Marcello Cesena
    new
  39. IT
    Red Sparrow
    - 329%
  40. IT
    XNXX.com
    - 3%
  41. IT
    2023 ATP Finals
    new
  42. IT
    Baarìa
    new
  43. IT
    Roger Federer
    new
  44. IT
    Grand Slam of tennis
    new
  45. IT
    Rocío Muñoz Morales
    - 159%
  46. IT
    Gabriele Sandri
    - 44%
  47. IT
    David Alcaraz
    - 19%
  48. IT
    RAI
    + 2%
  49. IT
    Beatrice Luzzi
    - 67%
  50. IT
    2012–13 S.S.C. Napoli season
    new
Those data refers to the most visited pages on Wikipedia from Italy on Nov 14, 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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