visualizing the indian elections

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Visual Insights of the World's Largest Democracy

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Visual Insights of the World’s Largest Democracy

By B.Ganes Kesari & Shravan Kumar

ODC 2014, ISB

History of Elections in IndiaInteractively explore the historical view of General Elections

AGENDA

Some Interesting InsightsDiscuss key insights across various perspectives

Counting Day UnfoldsHow real-time visual analytics were served on the Live Results

What do Elections remind us of ?

Massive Rallies..

Myriad Symbols & Colours..

Seasonal businesses..

High-decibel campaigning..

…and Victory laps.

~300 Parties fielding 8000 candidates

~800 Mn Registered Voters

~1 Mn booths served by 20 Mn people

~21,000 Votes/sec of live results

Varied data on several parameters

A Big Data problem… in every sense

But General Elections also entail…

Can we visualize the results of every single Lok Sabha election

since Independence?

https://gramener.com/election/parliament

On the other hand, which party has the most losses in Lok Sabha

elections?

https://gramener.com/election/parliament#story.ddp

Which constituency had the most number of candidates ever?

https://gramener.com/election/parliament#cartogram?METRIC=CANDIDATES&YEAR=1996

0%

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100%

0 2 4 6 8 10 12 14 16 18

# contestants

Win

ner

mar

gin

More contestants did not reduce the winner marginKarnataka, Assembly Elections 2008

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# contestants

Ru

nn

er-u

p m

argi

n

More contestants did reduce the runner-up marginKarnataka, Assembly Elections 2004

Does age make a difference?Do old candidates win less often?

1%2%

4%

6%

9%

11%

14%

11%

16%

18%

22% 22%

33%

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25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 85-90

0

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Win %The number of winning candidates as a % of candidates in the age group

CandidatesThe number of candidates in each

age group

Lok S

abha (

2004 o

nw

ard

s)

2%

4%

6%

9%

12%

15%

17%

15%16%

18% 18%

20%

27%

0%

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30%

25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 85-90

0

2000

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10000

12000

14000

Win %The number of winning candidates as a % of candidates in the age group

CandidatesThe number of candidates in each

age group

Ass

em

bly

ele

cti

ons

(2004 o

nw

ard

s)

What about wealth? How is that distributed?

http://times.gramener.com/candidates/

RS 1 LAKH

RS 10 LAKHS

RS 1 CRORE

RS 10 CRORES

RS 100 CRORE

RS 1,000 CRORES

RS 10,000 CRORES

LIVE ELECTION ANALYSIS

Our CNN-IBN Microsoft Election Analytics Canter, which you can see at www.bing.com/elections or http://ibn.gramener.com/live, served over 10 million requests on 16th May 2014 — the day of India election results.

This is one of the largest real-time visualisations that we (and perhaps many others) have attempted

LIVE ELECTION ANALYSIS

How did the regional parties fair??

Was it only the BJP who managed clean sweeps?

ADMK in TNBJD in ODTRS in TGTMC in WB Managed historic wins.

Video recreating

how the Election results unfolded

We handle terabyte-size data via non-traditional analytics and visualise it in real-time.

Gramener visualises

your data

Gramener transforms your data into concise dashboardsthat make your business problem & solution visually obvious.We help you find insights quickly, based on cognitive research,and our visualisations guide you towards actionable decisions.

A data analytics and visualisation company

Thank You!ganes.Kesari@gramener.com

shravan.kumar@gramener.com

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