Data Visualization at Twitter

Post on 22-Nov-2014

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My talk at the Hacks & Hackers Meetup SF at Twitter HQ on Oct 8, 2014

transcript

Krist Wongsuphasawat /@kristw

visualizationat Twitter

data

Krist Wongsuphasawat /@kristw

Krist Wongsuphasawat /@kristw

Bangkok, Thailand

Krist Wongsuphasawat /@kristw

Computer EngineerBangkok, Thailand

Chulalongkorn University

Krist Wongsuphasawat /@kristw

Computer EngineerBangkok, Thailand

Programming + Soccer

Krist Wongsuphasawat /@kristw

Computer EngineerBangkok, Thailand

Programming + Soccer

Krist Wongsuphasawat /@kristw

Computer EngineerBangkok, Thailand

Programming + Soccer

Krist Wongsuphasawat /@kristw

Computer EngineerBangkok, Thailand

M.S. in Computer ScienceUniv. of Maryland

Krist Wongsuphasawat /@kristw

Computer EngineerBangkok, Thailand

PhD in Computer ScienceUniv. of MarylandInformation Visualization

Krist Wongsuphasawat /@kristw

Computer EngineerBangkok, Thailand

PhD in Computer ScienceUniv. of MarylandInformation Visualization

IBMMicrosoft

Krist Wongsuphasawat /@kristw

Computer EngineerBangkok, Thailand

PhD in Computer ScienceUniv. of MarylandInformation Visualization

IBMMicrosoft

Sr. Data Visualization ScientistTwitter

at Twitterdata visualization

at Twitterdata visualization

visualizationat Twitterdata

visat Twitterdata

at Twitterdata

“Tweets”

at Twitterdata

“Tweets”

#eventsWorld Cup ElectionOscars

TV Shows New Year

Breaking news

EarthquakeSuper Bowl

Protest

at Twitterdata

“Tweets”

#eventsWorld Cup ElectionOscars

TV Shows New Year

Breaking news

EarthquakeSuper Bowl

Protest

#curiositySleep patternHuman behaviorLanguage …

at Twitterdata

“Tweets”

#eventsWorld Cup ElectionOscars

TV Shows New Year

Breaking news

EarthquakeSuper Bowl

Protest

What could we learn from the Tweets?

#curiositySleep patternHuman behaviorLanguage …

visat Twitterdata

“Tweets”

Tell stories about an event, Pursue curiosity or inspiration

Goal:

visat Twitterdata

“Tweets”

Tell stories about an event, Pursue curiosity or inspiration

(with deadline)

Goal:

Challenge accepted

visat Twitterdata

“Tweets”

Get data

1

easy?

Having all TweetsHow people think I feel.

How people think I feel. How I really feel.

Having all Tweets

• Too much data

• Want only relevant Tweets

• hashtag: #BRA

• keywords: “goal”

• Need to aggregate & reduce size

• Long processing time (hours)

Challenges

Hadoop ClusterVertica

Pig / Scalding (slow) SQL

Data Storage

Tool

Workflow

Hadoop ClusterVertica

Pig / Scalding (slow) SQL

Data Storage

Tool

Workflow

Hadoop ClusterVertica

Pig / Scalding (slow) SQL

Data Storage

Tool

Smaller datasetYour laptop

Workflow

Hadoop ClusterVertica

Pig / Scalding (slow) SQL

Data Storage

Tool

Final dataset

Tool node.js / python / excel (fast)

Your laptop

Workflow

Smaller dataset

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

• Peek into data

• Check data & test ideas

• Decide how to visualize

• Guided by data type

• Choose tools

• Start building

Visualize

• Peek into data

• Check data & test ideas

• Decide how to visualize

• Guided by data type

• Choose tools

• Start building

Visualize

Tableau Yeoman

d3R

(+ media)photos, videos

What?

Where? When?

GEO TIME

TEXT

data

What?

Where? When?

GEO TIME

TEXT

Visualize Data

What?

Where? When?

GEO TIME

TEXT

Visualize Data

Time Tweets/second

Time Tweets/second

Time Tweets/second + Annotation

http://www.flickr.com/photos/twitteroffice/5681263084/

What?

Where? When?

GEO TIME

TEXT

Visualize Data

GeoHeatmap

Low density

High density

GeoSan Francisco

flickr.com/photos/twitteroffice/8798020541

Low density

High density

GeoSan Francisco

Rebuild the world based on

tweet volumes

twitter.github.io/interactive/andes/

What?

Where? When?

GEO TIME

TEXT

Visualize Data

Text

www.wordle.net

Some experiments during World Cup

Text

www.wordle.net

Word cloud of Tweets right after the 1st goal

Text Word cloud of Tweets right after the 1st goal

www.wordle.net

It was an “own” goal.

What?

Where? When?

GEO TIME

TEXT

Visualize Data

Time + Geo

blog.twitter.com/2011/global-pulseyoutu.be/SybWjN9pKQk

Japan Earthquake 2011

Time + Geo Tweet pattern [Rios & Lin 2012]

Night

Late night

Daytime

Night

Late night

Daytime

Night

Late night

Daytime

Night

Late night

Daytime

Time + Geo Tweet pattern [Rios & Lin 2012]

Night

Late night

Daytime

Night

Late night

Daytime

Time + Geo Tweet pattern [Rios & Lin 2012]

Night

Late night

Daytime

Night

Late night

Daytime

Time + Geo Tweet pattern [Rios & Lin 2012]

What?

Where? When?

GEO TIME

TEXT

Visualize Data

Geo + Text Real-time Tweet map

Geo + Text Real-time Tweet map

most frequent

term

Geo + Text Real-time Tweet map

Gmail was down Jan 24, 2014

Geo + Text Real-time Tweet map

Nelson Mandela passed away Dec 5, 2013

Geo + Text Real-time Tweet map

What?

Where? When?

GEO TIME

TEXT

Visualize Data

Time + Text

UEFA Champions League

Biggest tournament for European soccer clubs

Many Tweets during the matches

UEFA Champions League

Dortmund Bayern MunichTeam 1 Team 2

Time + Text

UEFA Champions League

Dortmund Bayern MunichTeam 1 Team 2

Time + Text

UEFA Champions League

Dortmund Bayern MunichTeam 1 Team 2

Time + Text

UEFA Champions League

Dortmund Bayern Munich

Count Tweets mentioning the teams every minute

Team 1 Team 2

Time + Text

Time + Text UEFA Champions League

+ “goal” count + context

Time + Text UEFA Champions League

+ “offside”

Time + Text UEFA Champions League

+ players

Time + Text UEFA Champions League

A B C D

A C

C

Competition Tree

vs vs

vs

A B C D

A C

C

Competition Tree

vs vs

vs +

A B C D

A C

C

Competition Tree

vs vs

vs + =

What?

Where? When?

GEO TIME

TEXT

Visualize Data

Time + Text + Geo State of the Union

twitter.github.io/interactive/sotu2014

1) timeline + topic from Tweets

4) Density map of Tweets about selected topic

3) Volume of Tweets by topics

during selected part of the SOTU

2) context (speech)

twitter.github.io/interactive/sotu2014

Time + Text + Geo State of the Union

World Cup 2014Time + Text

Time + Text + Geo World Cup 2014

What?

Where? When?

GEO TIME

TEXT

Visualize Data

What?

Where? When?

GEO TIME

TEXT

Visualize Data

+Non-Twitter data

CONTEXT

Time + Text New Year 2014

Time + Text New Year 2014

Time + Text + Geo (c) New Year 2014

twitter.github.io/interactive/newyear2014/

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

Evaluate

3

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

Evaluate

3

Iterate!

• Self

• Peer feedback

• Non team members / Potential audience

Evaluation

visat Twitterdata

Get data

1

Visualize

2

Evaluate

3

visat Twitterdata

Get data

1

Visualize

2

Evaluate

3

big data => small data

visat Twitterdata

Get data

1

Visualize

2

Evaluate

3

big data => small data

What? Where? When?

visat Twitterdata

Get data

1

Visualize

2

Evaluate

3

big data => small data self, peer, external

What? Where? When?

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

Evaluate

3

big data => small data self, peer, external

What? Where? When?

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

Evaluate

3

big data => small data self, peer, external

What? Where? When?• users • followers graph • logs • etc. !

• derived data: language, sentiment

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

Evaluate

3

big data => small data self, peer, external

What? Where? When?Who? …• users

• followers graph • logs • etc. !

• derived data: language, sentiment

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

Evaluate

3

big data => small data self, peer, external

What? Where? When?Who? …• users

• followers graph • logs • etc. !

• derived data: language, sentiment

(with deadline)

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

Evaluate

3

big data => small data self, peer, external

What? Where? When?Who? …• users

• followers graph • logs • etc. !

• derived data: language, sentiment @kristw / https://interactive.twitter.com

(with deadline)

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

Evaluate

3

big data => small data self, peer, external

What? Where? When?Who? …• users

• followers graph • logs • etc. !

• derived data: language, sentiment @kristw / https://interactive.twitter.com

(with deadline)

+ visualizations by @philogb, @miguelrios & @trebor

Questions?

visat Twitterdata

“Tweets”

Get data

1

Visualize

2

Evaluate

3

big data => small data self, peer, external

What? Where? When?Who? …• users

• followers graph • logs • etc.

@kristw / https://interactive.twitter.com

(with deadline)

+ visualizations by @philogb, @miguelrios & @trebor

Thank you