Talk by Prof. Galit Shmueli at National Taipei University of the Arts' Department of Film Making on Oct 17, 2015

1. Big Data & Analytics in the
Digital Creative Industries
Galit Shmueli 徐茉莉
Tsing Hua Distinguished Professor
Analytics
Humanity
Responsibility
Talk @ Dept. of Filmmaking , Taipei National University of the Arts, Oct 17, 2015

2. Get
Big Data
Use
Big Data
Analytics

3. Get
Big
Data

4. Content and platform providers

5. Competitors, entrepreneurs, developers, researchers

6. Publicly available
Unsolicited
Different angles

7. Analytics: Use Big Data

8. 1. Predict viewing habits to provide
user recommendations, display ads
2. Understand user preferences to
design the next episode / series
3. Predict quality of experience to
improve viewing experience
4. Identify target audience for new
show to improve marketing
strategies
5. Automate close captions creation
& translation to improve user
experience and expand market

9. 1. Predict viewing habits to provide
user recommendations, display ads
Google Play Music recommends
playlists based on time of day,
mood, and activities
www.digitalmusicnews.com (10/2014)
Search by mood, available time, plot preference…
Semantic search (“movies with gangsters”)
Input film you like, get rec’s for films, books, bands…
Compares your ratings to others with similar “taste”
Recommends similar films to movie you search for
Evaluates your taste based on your movie ratings

10. https://gigaom.com/2012/09/09/can-breaking-bads-story-sync-get-viewers-to-give-up-their-dvrs
2. Understand user preferences to
design the next episode / series

11. 3. Predict viewing experience to
deliver the best results
Improve quality of experience (QoE)
Improve streaming quality

12. 4. Identify target audience for new
show to improve marketing strategies
www.fastcompany.com
Universal hesitated about how to market their
film. It was a "difficult title to compare to
others"—was it more comedic? Did it resemble
Rock of Ages more? Was it like Sparkle? Footloose?
Or just a teen comedy? …Universal asked Analytics
firm Fizziology to analyze how the film was being
discussed on social media
Before its release they discovered: Pitch Perfect
was already morphing into a cult hit
Universal changed their entire pre-release strategy.
The film was released a week early, with a 1+1 ticket
promotion
Universal claims it was the most extensive screening
campaign in the studio's history

13. 4. Identify target audience for new
show to improve marketing
strategies
Netflix used big data for
color-design of the cover

14. 5. Automate close captions creation
& translation to improve quality of
experience (QoE) and expand to
new markets
Speech recognition
Natural language processing

15. Competitors, entrepreneurs, developers, researchers
Analytics: Use Big Data

16. The social interactions
between viewers
while watching TV
https://youtu.be/ipfsuKwQYu0

17. Let’s see Two Cases of
Big Data and Analytics in Film
& TV

20. Even if you have the data, it isn’t
easy to get recommendations right

21. Satyamev Jayate
Popular Social TV Show in India

26. Study (based on Season 1)
by Galit Shmueli & Sandeep Khurana
Indian School of Business, 2013

27. Publicly Available Data
Television
Viewership Ratings
Simulcast
Regional languages
Radio talk shows
Blogs
Print Media
Social Media
YouTube
Facebook
Twitter
Website
Search traffic trends
(Google)

28. YouTube

29. Google Trends
Daily volume for
top regions/cities
• Download CSV
• Missing for low volume
• How is a region defined?
• Other breakdowns?

30. Wikipedia

31. Looking at multi-source data

32. Challenges for
Outsiders
Technology
• Data collection
• Merging multiple sources
Data availability
• Archiving policy (Twitter)
• Provider-determined
(Google Trends)
• User-determined (YouTube)
Meaning of data
• What is a YouTube “view”?
Google Trends “State”?
• Missing data?
Merging data sources
• Level of aggregation
• What is a record?
Long term collection:
Changes in data
dissemination policy

33. Analytics for your own YouTube
content are richer

36. There’s plenty of
information also on
other users’ content
Data YouTube gives us
directly
Data we can scrape from
YouTube pages
www.youtube.com/watch?v=YphFNAVAdpE

38. www.forbes.com/sites/amadoudiallo/2013/10/06/pandora-radios-dominance-built-on-big-data-edge/

39. DNA of a Song
gender of lead vocalist, prevalent use of groove, level of distortion on the electric guitar

40. Big Data
Analytics

41. Google Developers
On the challenge of YouTube video recommendations

42. www.youtube.com/watch?v=NXQiXdY8Sbk

43. Use humans to label a clip/movie/music:
• Tag “best moment”
• Label their emotions & reactions (sad,
laughing, scared, surprised…)

44. Alternatives to Amazon Mechanical Turk
(Chinese language websites?)

45. Analytics:
Finding Patterns in the Data
(using machine learning)
Recommendations and “what goes with what”
Segmenting videos/users/etc.
Predicting user behavior
After tagging a large set of songs, videos, users…
You can use machines for:

46. Competitors, entrepreneurs
developers, researchers
Can Get
Big Data
Use
Big Data
Analytics

48. “I'm a data miner, but I hope creative industry
doesn't get corrupted by data mining…
I have read an article recently in Wired about a
music hit made basically based on data.”
(post on an Internet forum)
Andrew Leonard at Salon.com, considers some of the
implications of TV in the era of Big Data
A creator is always looking
ahead, never looking back