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Do Cascades Recur?

Do Cascades Recur?

Cascades of information-sharing are a primary mechanism by which content reaches its audience on social media, and an active line of research has studied how such cascades, which form as content is reshared from person to person, develop and subside. In this paper, we perform a large-scale analysis of cascades on Facebook over significantly longer time scales, and find that a more complex picture emerges, in which many large cascades recur, exhibiting multiple bursts of popularity with periods of quiescence in between. We characterize recurrence by measuring the time elapsed between bursts, their overlap and proximity in the social network, and the diversity in the demographics of individuals participating in each peak. We discover that content virality, as revealed by its initial popularity, is a main driver of recurrence, with the availability of multiple copies of that content helping to spark new bursts. Still, beyond a certain popularity of content, the rate of recurrence drops as cascades start exhausting the population of interested individuals. We reproduce these observed patterns in a simple model of content recurrence simulated on a real social network. Using only characteristics of a cascade's initial burst, we demonstrate strong performance in predicting whether it will recur in the future.

Presented at WWW 2016.

Justin Cheng

April 15, 2016
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  1. Do Cascades Recur?
    Justin Cheng, Lada Adamic, Jon Kleinberg, Jure Leskovec

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  2. Several weeks later…

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  3. Time
    Popularity
    Ahmed et al. (2013), Bauckhage et al. (2013), Matsubara et al. (2012), Yang & Counts (2010)
    Prior work: cascades rise, then fall

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  4. Mar Jun Sept Dec
    Cascades rise and fall many times
    Popularity

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  5. Mar Jun Sept Dec
    Cascades rise and fall many times
    Popularity

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  6. Mar Jun Sept Dec
    Cascades consist of multiple copies
    Popularity

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  7. Mar Jun Sept Dec
    Cascades consist of multiple copies
    Popularity

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  8. Mar Jun Sept Dec
    Cascades consist of multiple copies
    Popularity

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  9. Cascades are complex
    Mar Jun Sept Dec
    Popularity

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  10. Cascades are complex
    Time

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  11. Individual copies recur
    Time

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  12. Studying recurrence on Facebook
    5 billion reshares 100 million photos 76 thousand clusters
    (Sampled over all of 2014 and de-identified)

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  13. 2 out of 5 image memes
    on Facebook recur.

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  14. 1 out of 3 videos
    on Facebook recur.

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  15. Cascades recur.

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  16. Cascades recur.
    Why do cascades
    recur?
    How do cascades
    recur?
    What is recurrence?

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  17. What is recurrence?

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  18. Defining recurrence
    Popularity r
    Time t

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  19. Defining recurrence
    p1
    p4
    p2
    Popularity r
    Time t
    p3
    (?)

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  20. Defining recurrence
    Popularity r
    Peaks have a minimum
    absolute/relative height
    rp
    ≥ h0,
    rp
    ≥ m·r
    *Not a peak
    Time t
    r
    p4
    p1
    p4
    p2
    pi
    pi
    rp
    p1
    rp
    p2
    rp
    p4

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  21. Defining recurrence
    Popularity r
    Peaks are local maxima
    rp
    ≥ max { rj
    | pi
    -w ≤ j ≤ pi
    +w }
    Time t
    p1
    p4
    p2
    pi
    rp
    p1

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  22. Defining recurrence
    Popularity r
    Valleys separate peaks
    rp
    , rp
    ≥ v · max { rj
    | pi
    < j < pi+1
    }
    Time t
    p1
    p4
    p2
    pi
    pi+1
    rp
    p1

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  23. Defining recurrence
    Popularity r
    Time t
    p1
    p4
    p2
    Recurrences

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  24. Defining recurrence
    Popularity r
    Time t
    b1
    b2
    b4
    Recurrences

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  25. Recurrence is common
    Number of Bursts
    Empirical CCDF
    0.00
    0.25
    0.50
    0.75
    1.00
    0 5 10 15

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  26. 0.00
    0.25
    0.50
    0.75
    1.00
    0 5 10 15
    Recurrence is common
    Number of Bursts
    Empirical CCDF
    40% of cascades recur
    0.40
    2

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  27. 0.00
    0.25
    0.50
    0.75
    1.00
    0 5 10 15
    Recurrence is common
    Number of Bursts
    Empirical CCDF
    Cascades have 2.3
    bursts on average
    2.3

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  28. Recurrence takes time
    Days Between 1st and 2nd Burst
    Empirical CCDF
    0.00
    0.25
    0.50
    0.75
    1.00
    0 50 100 150 200

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  29. 0.00
    0.25
    0.50
    0.75
    1.00
    0 50 100 150 200
    Recurrence takes time
    Days Between 1st and 2nd Burst
    Empirical CCDF
    A meme takes an average
    of 32 days to recur
    32

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  30. What is recurrence?
    A cascade recurs when it peaks in popularity more than once.
    Recurrence is common.
    Recurrence takes time.

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  31. How do cascades recur?

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  32. Do bursts occur in different parts
    of the network?

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  33. Bursts are (somewhat) separated
    Time
    Popularity

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  34. Bursts are (somewhat) separated
    Time
    Popularity

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  35. Bursts are (somewhat) separated
    Time
    Popularity

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  36. Bursts are (somewhat) separated
    Time
    Popularity
    3.2 connections within bursts

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  37. Bursts are (somewhat) separated
    Time
    Popularity
    1.4 connections across bursts

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  38. Are more popular cascades
    more likely to recur?

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  39. Moderate popularity increases recurrence
    Size of Initial Burst
    Mean Bursts
    1.5
    2.0
    2.5
    3.0
    3.5
    4.0
    103 104 105 106

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  40. Large initial bursts exhaust susceptibles
    Size of Initial Burst
    Proportion Exposed in Second Burst
    0.2
    0.4
    0.6
    0.8
    103 104 105 106

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  41. Are cascades with more diverse
    populations more likely to recur?

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  42. Moderate diversity increases recurrence
    Country Entropy in Initial Burst
    Mean Bursts
    Gender Entropy in Initial Burst
    2.0
    2.5
    3.0
    3.5
    0 1 2 3 4 5
    1.5
    2.0
    2.5
    3.0
    0.2 0.4 0.6 0.8 1.0

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  43. Do new copies of the same
    meme spark recurrence?

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  44. New copies can spark recurrence…
    Recurring cascades are
    spread out over more copies
    Recurring
    Non-recurring
    New copies correlate
    with recurrence
    r = 0.66
    Introduction of new copies &
    number of reshares
    4x

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  45. …but copies aren’t the only cause!
    Individual copies
    also recur
    18%
    of individual copies recur
    Copies can be traced
    back to other copies
    75%
    of copies can be attributed

    via the friendship graph

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  46. How do cascades recur?
    Bursts happen in separate parts of the network.
    Moderately viral/diverse content tends to recur.
    New copies can spark recurrence.

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  47. Why do cascades recur?

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  48. A model of recurrence

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  49. A model of recurrence
    1

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  50. A model of recurrence
    1
    2

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  51. Low virality
    1
    2

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  52. Low virality
    1
    2

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  53. High virality
    1
    2

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  54. High virality
    1
    2

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  55. Moderate virality
    1
    2

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  56. Moderate virality
    1
    2

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  57. Moderate virality
    1
    2

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  58. Popularity
    Low virality Moderate virality High virality
    Overall
    Copy 1
    Copy 2
    Time

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  59. Popularity
    Low virality Moderate virality High virality
    Overall
    Copy 1
    Copy 2
    Time

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  60. Popularity
    Low virality Moderate virality High virality
    Overall
    Copy 1
    Copy 2
    Time

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  61. Popularity
    Low virality Moderate virality High virality
    Overall
    Copy 1
    Copy 2
    Time

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  62. Low virality Moderate virality High virality
    Popularity
    Recurrence No Recurrence
    No Recurrence
    Time
    Overall
    Copy 1
    Copy 2

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  63. Simulations of this model
    replicate previous key findings.

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  64. Can we predict recurrence?

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  65. Features
    (e.g., burst length) (e.g., gender) (e.g., # edges) (e.g., # copies)
    Temporal Sharer Network Copy

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  66. Predicting recurrence
    Will it recur?
    Existence
    Will it be larger?
    Size
    When will it recur?
    Time

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  67. Predicting recurrence
    Will it recur? Will it be larger? When will it recur?
    Existence Size Time
    .89 .78 .58
    AUC
    AUC AUC

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  68. Future / Related Work
    • Effect of Multiple Networks, External Stimuli

    Gruhl et al. (2004), Kumar et al. (2005), Myers & Leskovec (2012)
    • Improved Models of Recurrence

    Barabasi (2006), Cha et al. (2012), Matsubara et al. (2012)
    • Other Factors Influencing Recurrence (Seasonality, Sentimentality)

    Altizer et al. (2006), Verdasca et al. (2005)

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  69. Cascades Do Recur.
    Justin Cheng, Lada Adamic, Jon Kleinberg, Jure Leskovec
    http://bit.ly/cascades-paper

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