90B+ user interactions per month
1B+ unique web/mobile visitors per month
500B+ page views per year
2,500+ top-tier domains
Traffic from search, social, and others
Content publish time and topic
Slide 3
Slide 3 text
What is the lifespan of an online post?
Slide 4
Slide 4 text
Article’s lifespan: amount of time it takes for an article to
receive 90% of all its views within a 30-day window.
Slide 5
Slide 5 text
No content
Slide 6
Slide 6 text
What time of day do people read content online?
REPORT PERIOD
JUNE - AUGUST 2014
Slide 7
Slide 7 text
No content
Slide 8
Slide 8 text
No content
Slide 9
Slide 9 text
No content
Slide 10
Slide 10 text
Is Facebook the new Google for news sites?
REPORT PERIOD
APRIL 2012 - JULY 2015
Slide 11
Slide 11 text
No content
Slide 12
Slide 12 text
2015: Facebook Pulls Ahead of Google
as Top Traffic Source
Slide 13
Slide 13 text
2016: A Traffic Duopoly Emerges
Slide 14
Slide 14 text
Does early attention predict eventual social lift?
Slide 15
Slide 15 text
No content
Slide 16
Slide 16 text
Do readers enjoy long-form on mobile?
IN PARTNERSHIP WITH PEW RESEARCH
REPORT PERIOD
SEPTEMBER 2015
Slide 17
Slide 17 text
No content
Slide 18
Slide 18 text
No content
Slide 19
Slide 19 text
Does traffic vary by topic?
REPORT PERIOD
JANUARY - DECEMBER 2016
Slide 20
Slide 20 text
No content
Slide 21
Slide 21 text
No content
Slide 22
Slide 22 text
No content
Slide 23
Slide 23 text
Does bounce rate always matter?
REPORT PERIOD
MARCH - OCTOBER 2017
Slide 24
Slide 24 text
No content
Slide 25
Slide 25 text
No content
Slide 26
Slide 26 text
No content
Slide 27
Slide 27 text
How are Facebook and Google doing in 2017?
REPORT PERIOD
JANUARY - OCTOBER 2017
Slide 28
Slide 28 text
No content
Slide 29
Slide 29 text
No content
Slide 30
Slide 30 text
No content
Slide 31
Slide 31 text
Moving to Prediction
Slide 32
Slide 32 text
Can Internet attention predict public opinion?
Slide 33
Slide 33 text
No content
Slide 34
Slide 34 text
No content
Slide 35
Slide 35 text
No content
Slide 36
Slide 36 text
Can Internet attention predict a film’s revenue?
Slide 37
Slide 37 text
Weekly Unique Views for Movies by Studio
4M
3M
2M
1M
APR
2016
JAN
2016
Walt Disney
Paramount Pictures
JUL
2016
OCT
2016
JAN
2017
Slide 38
Slide 38 text
No content
Slide 39
Slide 39 text
No content
Slide 40
Slide 40 text
600k
500k
400k
300k
200k
100k
10k 20k 30k 40k 50k 60k 70k
Cumulative Box Office
Gross Revenue
Print Ad Cost in US $
600k
500k
400k
300k
200k
100k
Cumulative Box Office
Gross Revenue
Negative Cost in US $
50k 100k 150k 200k 250k
200k
600k
500k
400k
300k
200k
100k
400k 600k 800k 1M
Cumulative Box Office
Gross Revenue
Unique Views
0.955
Pearson Correlation Coefficient
when excluding PG rated movies
Movies rated PG
Movies not rated PG
0.474
Pearson Correlation Coefficient
when excluding PG rated movies
0.829
Pearson Correlation Coefficient
when excluding PG rated movies
Revenue Compared to
Unique Views
for Related Web Posts 3 Days Prior to Release
Revenue Compared to
Print Ad Cost in US $
Revenue Compared to
Production Cost in US $
Total unique views for posts related to a
movie three days prior to its release has
the highest correlation with revenue
compared to production cost and
advertising budget.
Slide 41
Slide 41 text
200k
600k
500k
400k
300k
200k
100k
400k 600k 800k 1M
Cumulative Box
Office Gross
Revenue
Unique Views
0.955
Pearson Correlation Coefficient
when excluding PG rated movies
Movies rated PG
Movies not rated PG
Revenue Compared to Unique Views
for Related Web Posts 3 Days Prior to Release
Slide 42
Slide 42 text
We measure how users spend time online.
There is much to learn from this data.
BROWSER SESSIONS
MOBILE INTERACTIONS
WEB CRAWL DATA ON PAGES
TRAFFIC SOURCES
VIEWS, VISITORS, AND TIME
SOCIAL SHARING ACTIVITY