alphago vs lee se-dol: tweeter analysis using hadoop and spark

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Jongwook Woo HiPIC CSULA Alphago vs Lee Se- Dol Tweeter Analysis using Hadoop and Spark March 18 2016 Jongwook Woo, PhD High-Performance Information Computing Center (HiPIC) California State University Los Angeles

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Page 1: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

Jongwook Woo

HiPIC

CSULA

Alphago vs Lee Se-DolTweeter Analysis using Hadoop and

Spark

March 18 2016Jongwook Woo, PhD

High-Performance Information Computing Center (HiPIC)California State University Los Angeles

Page 2: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Content

Hadoop and SparkIBM DashDBConclusion

Page 3: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Hadoop and Spark Environment

SystemsAzure HDInsights Spark8 Nodes

–40 cores: 2.4GHz Intel Xeon–Memory - Each Node: 28 GB

Data SourceKeyword ‘alphago’ from Tweeter via Apache NiFi

Data Size 63,193 tweets

Real Time Data Collection period03/12 – 03/17/2016

–No data collected on 03/13

Page 4: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Top 10 Countries that Tweets “Alphago”

Page 5: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Top 10 Countries

# of Tweets per CountryUSA: > 11,000Japan: > 9,000Korea: > 1,900Russia, UK: > 1,600Thai Land, France : > 1,000 Netherland, Spain, Ukraine: > 600

Page 6: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Top 10 Countries Sentiment

Positive Negative

Page 7: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Top 10 Countries

Most Tweeted Countries All countries show more positive tweets

–Korea, Japan, USA

Country Positive Negative

USA 5070 3567

Japan 8118 217

Korea 1053 407

Page 8: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Daily Tweets in 03/12 – 03/17/2016

3/12/2016 3/13/2016 3/14/2016 3/15/2016 3/16/2016 3/17/20160

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

Alphago vs Lee Sedol

Game 4: Mar 13 Lee Se-Dol win

Game 5: Mar 15

Game 3: Mar 12

Page 9: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Ngram words

3 word in row right after Go-Champion “sedol” and “se-dol”

sedol

se-dol3-grams FrequencyAgain-to-win 1,187

Is-something-I’ll 369

Is-something-i 199

In-go-tournament 168

Page 10: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Sentiment Map of Alphago

PositiveNegative

Page 11: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Sentiment Map of Lee Se-Dol vs Alphago

YouTube video: the sentiment of the World https://youtu.be/vAzdnj4fkOg?list=PLaEg1tCLuW0BYLqVS5RTbToiB8wQ2w14a

Page 12: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Tweeter Analysis using IBM DashDB

Environment:DashDB and Tweets Services of IBM Bluemix

–Load existing data Period: by March 16 2016

Authors and Followers of the Tweets

Page 13: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Top 10 Tweet Countries

With Hashtag “#Alphago”

United States: >10,000Japan: >8,000Korea: >1,800

Page 14: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Hashtags Frequency

Page 15: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Sentiment at #Alphago

Page 16: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Gender Counts Who Tweets

female male unknown

Unknown

Page 17: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Tweets counts per months

Aug-2014 Feb-2015 Feb-2016 Jan-2015 Jan-2016 Mar-20160

2000

4000

6000

8000

10000

12000

Tweets counts per months

Page 18: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Daily Tweets During Games

3/9/2016 3/10/2016 3/11/2016 3/12/2016 3/13/2016 3/14/2016 3/15/2016 3/16/20160

500

1000

1500

2000

2500

3000

3500

Daily Tweets during GamesGame 4: Mar 13 Lee Se-Dol win

Game 5: Mar 15 Game 3: Mar 12

Game 1: Mar 9

Game 2: Mar 10

Page 19: Alphago vs Lee Se-Dol: Tweeter Analysis using Hadoop and Spark

High Performance Information Computing CenterJongwook Woo

CSULA

Conclusion

Analyze Tweeters with “Alphago” USA and Japan dominates the tweets

More than KoreaEuropean countries as well

More Positive tweetsAlphago and Lee Sedol both become popular