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Elections on the ground Elections on the ground

Elections on the ground - PowerPoint Presentation

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Elections on the ground - PPT Presentation

and in the air Comparing Perches and Perspectives SSLBC2012 Whats Up 2 Why am I here Everyone else was busy Excuse to visit campus Wouldnt have finished my thesis if it werent for Ellen ID: 591275

temporal elections amp tools elections temporal tools amp analysis weeks jan25 future prior twitter political 2012 time search vision

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Slide1

Elections on the ground and in the air

Comparing Perches and Perspectives

#SSLBC2012Slide2

What’s Up?

2Slide3

Why am I here?

Everyone else was busyExcuse to visit campus

Wouldn’t have finished my thesis if it weren’t for Ellen

Follow and have worked in political risk

Helped managed election observation mission in Liberia, November 2011

Currently, working at startup that uses predictive analysis and temporal analytics

3Slide4

Fields of Reference

4Slide5

Outline

Definitions, Perspectives, and Engaging

Futures & Forecasting Methodologies

Case Study: Egypt

Online Tools: Whither Twitter?

Temporal

Vision

5Slide6

When I use a word it means just what I choose it to mean — neither more nor less

.

Humpty Dumpty in Lewis Carroll’s Through the Looking Glass

1

.

D

efinitions

, Perspectives,

& Engaging ElectionsSlide7

Four Ways to Manage Info

7Slide8

Definitions

Fact: evidence used in reportOpinion: biased perspective

Data: quantity, number, sum

Information: relationships of facts

Intelligence: organized information

8Slide9

Perspective, Parsed

9Slide10

Engaging Elections

10Slide11

Primary Actors & Key Stakeholders

11Slide12

Central to Elections

12Slide13

Characteristics and Categories

13Slide14

It is hard to make predictions, especially about the future.

Yogi Berra

4. Forecasting MethodologiesSlide15

Phillip K. Dick

15Slide16

Providential:

what will be will beConventional: tomorrow will be much like today

Pessimism

: decline from past ‘Golden Age’

Discontinuity

: the future will be nothing like the present

Optimism

: faith in progress / technology cures all

Unknowable

: futile to attempt to go beyond the present

Futurist

: tempered optimism / the future is rich with possibility resulting from human planning and action

Source Prof. Howard F.

Didsbury

Jr

Seven Attitudes Towards Future

16Slide17

Forecasting Animals

17Slide18

Types of Political Risk

18Slide19

How to Make & Falsify Predictions

Probability

Impact

Time Range

19Slide20

If a man will begin with certainties, he shall end in doubts; but if he will be content to begin with doubts he shall end in certainties.

Francis Bacon

2. Case Study: EgyptSlide21

Time

Window Analysis

21Slide22

Profile: Historic Milestones

Egyptian

Gov’t

Ongoing Arrests of MB Members

President Obama’s Cairo Speech

As Opposition to Mubarak, MB Backed by

ElBaradei

MB Threatens Disruption of Elections

22

Past 5 Years

3 Months prior

1 Month following

Run-up

Up to TodaySlide23

Watersheds

pre-Jan25

23

Past 5 Years

3 Months prior to #Jan25

1 Month following #Jan25

Run-up

Up to TodaySlide24

Watersheds

post-Jan25

24

Past 5 Years

3 Months prior to #Jan25

1 Month following #Jan25

Run-up

Up to TodaySlide25

Evolution: Political Landscape

25

Source:

Arabist.netSlide26

Change

in FJP Composition

Creation of FJP & Before Elections

26

After ElectionsSlide27

When

to Watch

27

Mid-April

: Candidacy Registration Period

Mid to Late June

: anticipated electionsSlide28

Comparison

of January 2012

28

Forecast – 6 Weeks Prior

Actual – 4 Weeks During

Revised – 6 Weeks AfterSlide29

Time

-Textured January 2012

29

Forecast – 6 Weeks Prior

Actual – 4 Weeks During

Revised – 6 Weeks AfterSlide30

What

and How to Watch

30Slide31

Once we get out of the '80s, the '90s are gonna

make the '60s look like the '50s.

Dennis Hopper in

Flashback

4. Online Tools: Whither Twitter?Slide32

Seismic Shift in Intelligence

Temporal Indexing of Web Enables

Novel IntelligenceSlide33

Text

Is Loaded with Temporal Signals

North Korea

apparently began pursuing a uranium enrichment program in 1996 at the latest

...In June, officials said the

network encryption

was operational

2012 is the year when

China

will

export

more chemicals according to this source

Dr Sarkar

says the new facility will

be operational by March 2014...”

Drought and malnutrition hinder next spring’s expansion plans in

Kabul

...

“...opposition organizers plan to meet on Thursday to

protest

...”

Unstructured text has analytic & predictive power.Slide34

Using Big Data for Prediction

34Slide35

New Tools: Electionista

web app for monitoring elections over Twitter across 110 different countries in 58

languages

Tweets are categorized

geographically

and cached

so that users can scroll

back

35Slide36

New Tools: WaPo Modifiable Model

Uses 3 variables

:

% change in GDP per capita from Q1 to Q3

Average Approval in June, according to Gallup

1 incumbent party candidate is sitting president, 0 if not

SOURCES: Seth Hill, postdoctoral associate at Yale University; John Sides, associate professor at George Washington University; Lynn

Vavreck

, associate professor at UCLA; GRAPHIC: Jeremy Bowers, Emily Chow and Ezra Klein - The Washington Post. Published April 24, 2012.

36Slide37

New Tools: Google Portal

37Slide38

New Tools: Google Portal

38Slide39

New Tools: Yahoo Clues

How people search

Find most popular search terms

Compare trends between search terms

39Slide40

New Tools: RF & Temporal Analysis

40

Sentiment analysis

Temporal network analysis

Search through time

Temporal source scoringSlide41

Further Research for Twitter Data

S

entiment

analysis of political

tweets

Automatic

detection of propaganda and

disinformation

Automatic

detection of sock

puppets

Credibility checking

Basic

research on Twitter demographics and automatic profiling of users with regards to demographic

attributes

Basic

research on user participation and self-selection

bias

41Slide42

Discovery consists of seeing what everybody has seen and thinking what nobody has thought.

Albert Szent-Gyorgyi

5. Temporal VisionSlide43

Temporal Vision

43Slide44

Insight from Big Data

Watch (signal)Have expectations about what is being watched (shift)

Know how is obscured (

blindspot

)

Identify out-of-the-ordinary happenings (outlier)

Conceive of fast-moving, far-reaching events (flashpoints)

Be able to correlate them with other interesting observations (pattern)

44Slide45

Thank You!

E:

munish@recordedfuture.com

T: @

whypurifly

@

politicalrisk

L:

linkd.in/munish

45Slide46

Nobody is wrong about the future and everybody is wrong about the past.

Munish Puri