Gill Oberland Er 2

8/13/2019 Gill Oberland Er 2

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Taking CareOf the Linguistic Features of Extraversion

Alastair Gill and Jon Oberlander

University of Edinburgh


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12/2/2013 Gill & Oberlander 2

Jim Carrey: Introvert? Albert Einstein: Extravert?

Which are they ... and where are you?

Extravert or Introvert?


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Personality meets HCI

Reeves and Nass had subjects solve a problem and thendiscuss solution with the computer (via a textual interface)

Language variables manipulated to provide different systempersonalities:

Dominant:

Always goes first

Strong language Uses assertions and commands

Indicates high confidence

Submissive:

Goes second

Unassertive language Uses questions and suggestions

Indicates low confidence


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Eysenck's Three Factor PEN model

Extraversion social interest and positive affect "arousal level in the cortex"

(lower levels = more extravert)

Neuroticism Response to stressors and negative affect

"activation thresholds in the limbic system"(lower thresholds = more neurotic)

Psychoticism Aggressiveness, individuality "testosterone levels?"

(higher levels = more psychotic) What are the implications for language?


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Personality and Language ... so far

Work has focussed mainly on Extraversion in speech

What has this found? Talk more in discussions (Carment et al., 1965)

Distinguished by speech cues (Scherer, 1979)

Specific (eg. syntactic category) and less specific (style)features related to lexical choice proposed (Furnham, 1990)

LIWC content analysis program used with transcriptions to look atwarmth and dominance facets of Extraversion (Berry et al., 1997)


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Textual Personality

Relatively little work on written linguistic personality Written diary entries analysed using LIWC (Pennebaker and King,

1999)

Can we replicate Pennebaker and King's findings?

How else is personality embodied in text Which linguistic features are most important for personality?

What can more sophisticated computational linguistics techniquesreveal?


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Our personality corpus

105 subjects generating two texts each

Each completed the Eysenck Personality Questionnaire

Each then composed two emails: "To a good friend whom they hadn't seen for quite some time"

One concerned past activities over the previous week

The other concerned planned activities over the next week. Each message took around 10 minutes to compose and submit by

HTML form.

The resulting 210 texts contain 65,000 words.


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Experiment 1: replication and text analysis

Factor analysis Selection of LIWC items for principal components analysis used the same

criteria as Pennebaker and King

Four factors derived which are essentially similar to theirs, with minorvariations in factor loadings

Multiple regression analysis Variables which showing a small correlation with personality type and topicindependence were entered for:

LIWC

MRC Psycholinguistic Database (used to compute mean scores for verbalfrequency, written frequency, concreteness, age of acquisition, etc.)


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Interpretation

Extraverts do write more This echoes earlier findings on speech

And they write more loosely (with fewer exact numberexpressions) For eg. several vs five

Supports Furnhams hypothesis And we also find they write less concretely

Eg. Furniture vs chair

But: The variance explained is not as great as for P and N

Correlations not as strong as found by Pennebaker and King


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Experiment 2: NLP techniques

Use simple bigram techniques to take more of a word's context into account

Select high-E and low-E subcorpora by taking texts fromsubjects with E-score > 1 s.d from mean (cf. Dewaele andPavlenko, 2002): 21 High E versus 17 Low E

12,000 words versus 8,000

Generate bigram profiles ranked by Dunning's log-likelihoodstatistic (top 50 bigrams with frequency >= 2, p < 0.001).

Calculate relative frequency ratios (Damerau 1993) for bigrams

common to both subcorpora


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On the surface

The gross features are perhaps the most intuitive in theirrepresentation of the Extraverts or Introverts.

For example, [ hi], the marker followed byhi, was unique to Extravert texts; message-initial hi.

By contrast the more formal [ hello] was found solelyin Introvert texts

Use of punctuation also differs between the two groups: Extraverts preferring multiple exclamation marks [! !], and solely

using multiple full stops [. .] as in the elliptical (...)

features of informal style, and looser use of language.


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Quantification

Introverts tend to show preference for a greater use ofquantifiers [a lot], [a few] and uniquely [all the], [one of], [lots of] and [loads

of]

Extraverts show a preference for [a bit] and uniquely use[couple of].

Not only does this demonstrate an Extravert tendency to belooser and less specific, it also apparently reveals a tendencytowards exaggeration on the part of the Introvert.


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Valence

Bigrams containing negations were used significantly only byIntroverts, as in [i dont] and [dont know] (indeed [i dont] is the bigram with most frequent use of i)

Similarly, the Extravert preferences suggest a more positive,relaxed disposition: [looking forward] and [forward to]

(presumably as in looking forward to)

[a good]

[catch up]

[take care]


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Ability and Modality

Personal views on capability are suggested by the different

collocations with infinitival to. Extraverts demonstrate ability with want, need, and able (to) Introverts more timidly and tentatively are [trying to] or [going to]

Similarly, collocations with the verb be show a distinction inuse of modal auxiliaries which has an effect on the projection

of certainty. For example, Introverts uniquely use the weaker [should be] Extraverts prefer the stronger predictive [will be], and

contracted form [ill be] (i will be).


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What about the P and N dimensions? Bigrams in 3D

High-E use ... and !! Both associated with High-N;

But one goes with High-P; the other with Low-P

High-E use [take care] This is Low-N, Low-P

Low-E use [, but] and [, because] One is High-N, High-P; The other is Mid-N, Mid-P.


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Take care!

Summary

CASA tells us that linguistic personality might matter

Simple techniques can confirm known linguistic features ofextraversion and uncover new ones

Applications: Interface agents

Personality Language Checker Future work:

Test sensitivity of readers to personality features

Investigate feature generalisability

Documents

Gill Oberland Er 2