Taking Care Of the Linguistic Features of Extraversion

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Taking CareOf the Linguistic Features of
Extraversion
Alastair Gill and Jon Oberlander University of
Edinburgh
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Extravert or Introvert?
Jim Carrey Introvert? Albert Einstein
Extravert? Which are they ... and where are you?
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Why compute with personality?

• Reeves and Nass
• Computers Are Social Actors
• Nass et al. (1995) had subjects use a text-only
  interface to solve a problem with help from the
  computer.
• Language variables were manipulated to provide
  Dominant and Submissive system versions (eg.
  turn, hedges).
• Found that
• Similarity preferred (eg. Dominant user prefers
  Dominant interface)
• Convergence even more (eg. D prefer S-to-D)
• Implications Personality matching enhances the
  users experience and leads to more positive
  evaluation.
• So whats personality, anyway?

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Personality meets HCI

• Reeves and Nass had subjects solve a problem and
  then discuss solution with the computer (via a
  textual interface)
• Language variables manipulated to provide
  different system personalities

• 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 at warmth 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 techniques reveal?

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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 minor variations in
  factor loadings
• Multiple regression analysis
• Variables which showing a small correlation with
  personality type and topic independence were
  entered for
• LIWC
• MRC Psycholinguistic Database (used to compute
  mean scores for verbal frequency, 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
  number expressions)
• 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 from subjects with E-score gt 1 s.d from
  mean (cf. Dewaele and Pavlenko, 2002)
• 21 High E versus 17 Low E
• 12,000 words versus 8,000
• Generate bigram profiles ranked by Dunning's
  log-likelihood statistic (top 50 bigrams with
  frequency gt 2, p lt 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 their representation of the Extraverts or
  Introverts.
• For example, ltSTARTgt hi, the ltSTARTgt marker
  followed by hi, was unique to Extravert texts
• message-initial hi.
• By contrast the more formal ltSTARTgt hello was
  found solely in 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 of quantifiers
• 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 be looser and less specific, it also
  apparently reveals a tendency towards
  exaggeration on the part of the Introvert.

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Valence

• Bigrams containing negations were used
  significantly only by Introverts, 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 in use 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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Summary

• CASA tells us that linguistic personality might
  matter
• Simple techniques can confirm known linguistic
  features of extraversion and uncover new ones
• Applications
• Interface agents
• Personality Language Checker
• Future work
• Test sensitivity of readers to personality
  features
• Investigate feature generalisability

Take care!