ROBERT L . HOGENRAAD

PSYCHOLOGY DEPT.

UNIVERSITÉ CATHOLIQUE DE LOUVAIN, BELGIUM

SDH 2010 , VIENNA, OCT. 19 -20 , 2010

The Fog of Words

robert.hogenraad@uclouvain.be

Social science

We cannot estimate the qualities of « man » using continuous quantitities. However, numbering and classifying qualities by counting is correct for discrete qualities.

In social science and the

humanities, we do not

measure..WE COUNT.

About questionnaires« That’s not the way people talk » (a remark by Charlie Osgood)

9 American-English pan-cultural SD scales

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9 pan-cultural Russian SD scales

Before getting into the thick of things, I want to

set the main argument of my

talk.

In four slides.

After that, we’ll scan the details

My argument of mass destruction (A.M.D.)

AMD

The hermeneutic chiasma

Rule of critical asymmetry:

« The more clear and

transparent a text, the less

effort is required of the

reader. » 

AMD

In content analysis…

The less structured a text, the more structured and categorizing the analysis must be.

Example: the postcard that lands by mistake in your mailbox…

The mystery postcard …

AMD…

… that lands in your mailbox

Technical conversations between experts …

… turn easily into a quasi-private language because so many elements of it are implicit, i.e., the text is structured only for the experts, but not for outsiders.

A: “Bill, you’d better get that Linden back or you’ll lose that baby too.”

B: “Yeah, I just lost 81.”B: “Look any better?”A: “No. You still got to get rid

of about 400 Bill because you’re 400 over the short time emergency on that 80 line.”

B: “Yeah - that’s what I’m saying. Can you help me with that?”

Technical conversations .between experts …

…conversations between Senior Pool Dispatcher (A) and Con Edison System Operator (B) between 8:56pm and 9:02pm, July 13, 1977.

(Extracts from the State of New York Investigation, New York City Blackout, July 13, 1977, p. 13).

1. E P I S T E M O L O G I C A L I S S U E S

2. S TAT I S T I C A L I S S U E S

3. C O N T E N T A N A LY S I S T O T H E S E RV I C E O F P O L I C Y P L A N N I N G

Content Analysis: An Emerging Zone

1. Epistemological issues

Spicing up content analysis with epistemology

Two traditions for analyzing

texts, patristic and rabbinic, or nomothetic and idiothetic.

And when to use each of them

The two traditions of content analysis in The QUR’AN

The Qur’an. A

new translation

by Tarif Khalidi

« It is He Who sent down the Book upon you. In it are verses precise in meaning… Others are ambiguous. Those in whose heart is waywardness pursue what is ambiguous therein, seeking discord… » (The House of ‘Imran,

3:7).

THE NOMOTHETIC TRADITION IN CONTENT ANALYSIS.

EXAMPLE

(1. Epistemological issues)

Affiliation & Power categories: Motive Dict v. 4.2

Category Subcategories N. Entries Examples

Affiliation 759Affection 96 Mate, sweetheartSocial behavior 78 Answer, escortAffect 56 Dad, MomPositive affect 35 Affable, thoughtful… … …

Power 1,307Power gain 35 Emancipate, nominatePower conflicts 300 Adversary, invade… … …

SCORES FOR CATEGORY BASED DICTIONARY : CAT. 33 N-Power :..............20-30

SEG TEXT WORDS FREQ SQRT RATE DENS SQRT RATE TOTAL DIFF. FREQ DENS __________________________________________________________________ 13 4414 1011 351 8.917 135 5.530 14 13072 2366 1076 9.073 367 5.299 15 4482 1129 405 9.506 162 6.012 16 21026 2593 1502 8.452 362 4.149 17 13571 2041 1155 9.225 297 4.678 18 15102 2350 1076 8.441 329 4.667 19 7736 1437 486 7.926 166 4.632……………

Ayatollah Ali Khamenei (2009-2010)

Month Need of Affiliation Need of Power13 6,526 8,91714 7,427 9,07315 7,302 9,50616 7,187 8,45217 6,937 9,22518 7,196 8,44119 7,499 7,926… … …

Risk of conflict = nPow minus nAff -- in D. C. McClelland’s motive theory.

Grand Ayatollah Ali Khamenei: February 2009-July 2010[R² = .17, F(1, 16) = 3.3, p < .09]

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THE IDIOTHETIC TRADITION IN CONTENT ANALYSIS.

EXAMPLE

(1. Epistemological issues)

The idiothetic tradition: En route to word-word correlations

case John father

true peace

war fight poli’tcs

bird Mary

1 1 55 44 0 56 74 74 74 72 5 88 7 1 53 86 0 74 03 8 7 55 2 52 53 0 75 54 9 66 8 5 51 84 4 85 35 6 999 22 8 54 9 21 5 66 7 12 66 6 8 96 123 35 27 3 15 9 9 5 95 159 252 18 5 6 9 3 7 51 75 52 59 5 44 4 7 9 0 53 51 910 4 4 6 47 0 0 753 51 8

Word-word correlations (fictive)

JOHN FATHER TRUE PEACE WAR FIGHT POLITICS BIRD MARY

JOHN 1,0000 ,1021 ,1666 -,1554 ,2015 ,0552 -,3038 -,3104 -,2303 FATHER ,1021 1,0000 -,0422 -,0595 ,4005 -,3870 -,2054 -,3768 ,1373 TRUE ,1666 -,0422 1,0000 -,3055 ,2247 ,3311 -,2182 -,2237 -,0776 PEACE -,1554 -,0595 -,3055 1,0000 -,5062 -,5301 ,9704*** -,0680 ,3822 WAR ,2015 ,4005 ,2247 -,5062 1,0000 ,1889 -,5650 -,2206 -,1330 FIGHT ,0552 -,3870 ,3311 -,5301 ,1889 1,0000 -,4083 ,5007 -8396** POLITICS -,3038 -,2054 -,2182 ,9704*** -,5650 -,4083 1,0000 ,0011 ,3453 BIRD -,3104 -,3768 -,2237 -,0680 -,2206 ,5007 ,0011 1,0000 -,4657 MARY -,2303 ,1373 -,0776 ,3822 -,1330 -,8396** ,3453 -,4657 1,0000

Probability 2-tails : * - .05 ** - .01 ***. -.001

…and joint correspondence analysis (over 9 words and 10 observations) …

CA joint plot

Axi

s 2

Axis 1

-0.3

-0.7

-1.0

-1.4

-1.7

0.3

0.7

1.0

1.4

1.7

-0.3-0.7-1.0-1.4-1.7 0.3 0.7 1.0 1.4 1.7

… or cluster analysis Farthest neighbour

Euclidean

JohnMarypeacetruewarfightbirdpoliticsfather

1500 1250 1000 750 500 250 0

COMPARING THE NOMOTHETIC & THE IDIOTHETIC TRADITIONS IN CONTENT

ANALYSIS

RETAKE

observer instrument (telescope) object (moon)text analyst dictionary (marker) text

The patristic –dictionary– tradition to analyze texts …

…is ordinary in kind,

but allows one to reach extraordinary outcome in degree.

In the rabbinic tradition, no instrument between analyst and text

Analyst and text are in the same glass

What the hell is water?

The idiothetic« rabbinic » tradition

In The QUR’AN…

Trad 1: Forcefully substitutes words of a text with categories* (=dictionaries)

*Group of words with similar meanings

Trad 2: Looks for clusters that may refer to a theme**

**Cluster of words with different meanings

The two traditions (a)

Trad 1: Dictionaries are calibrated instruments, leave no space for doubt

Trad 2: Yields complex themes from fragments of a text, yet no unique solution

The two traditions (b)

Trad 1: Words as predictors

Trad 2: Words as symptoms*

* About unverifiable interpretations:

It is easy for human observers to see

the response they want and so to be

fooled by the data

The two traditions (c)

Trad 1: Tradition of distrust #answers to pre-existing questions [« You’ve left out everything which doesn’t fit », in Tom Stoppard’s Arcadia, p. 59]

Trad 2: One looks for

contiguities between

words of the text in order

to discover latent

meanings #commenting

the text, without altering it

The two traditions (d)

Trad 1: Dictionaries share features with other texts

Trad 2: Idiothetic, contiguities are unique, never seen before, never to be seen after

The two traditions (e)

RetakeIt is inefficient to attempt to

analyze complex textual data using a complex interpretative tool …

… as in this …

At your peril! Disaster is a sentence away!

Catch-

22!

When the General in charge of the Afghanistan war saw this graph, he said:

«When we’ll have understood that, we’ll have won the war!»

2. Statistical issues

History happens only once (1) The heart of the argument

is that one cannot analyze sampling error in the case of a unique narrative event.

History happens only once (2)

The Lloyd’s of London have an “Unusual Risks” section, because there is no distribution theory for unique events to turn to.

The once-ness of every inference model

Troy Polamalu is an American football player (from Samoa). He didn’t cut his hair for the last 7 years. They say that one hair after another, his hair is 11 kilometers long!

That wouldn’t happen to me…

The once-ness of every inference model

Now, the Head & Shoulder cosmetic company for which he makes ads insured his hair with the Lloyds of London for 1 million $.

Rate of primordial thought contents (RID) in Ulysses’ 18 chapters

Rate of primordial thought contents in Ulysses’ 18 chapters after 10 bootstrap simulations

Afterword

And then …

At the end of the day, whether or not one agrees with the conclusions is less important than the insight one can gain from recognizing the importance of the rule of critical asymmetry.

“Das Leben Geht

Weiter”

USING NUMBERS TO PREDICT BEHAVIOR

3. To the service of policy planning

Content analysis to the service of predicting conflicts

Predicting the risk of war in the speeches of President Medvedev(January 24 to September 11, 2008)

Dictionary is the Motive Dictionary (version 6.0)

Where are the cut-off points in a text?

Answer: Use CART (for Classification and Regression Trees)

When you deal with narrativity, you need to use statistics that are sensitive to it, like change-point tests

Surprise quiz in 4 questions

(As long as we do not assess something, we do not have to worry about it.)

Do you think Iran will wage a conflict against Israel?

Or would you rather think Israel would start a fight against Iran?

Or do you think American might launch a conflict against Iran?

Or do you think none of that would happen?

Answer:

IRAN?

NOPE! Grand Ayatollah Ali Khamenei: February 2009-July 2010[R² = .17, F(1, 16) = 3.3, p < .09]

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Israel?

NOPE! Prime Minister Benjamin Netanyahu: March 2009 - September 2010[R² = .35, F(2,15) = 4.0, p < .05]

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USA?

Could be…

Secretary of State Hilary Clinton about Iran: Feb. 2009-Sept 2010[R² = .37, F(1,17) = 10.1, p < .01]

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That’s all.But enough said.

Thank you for your attention

Vielen Dank für Ihre Aufmerksamkeit