This document summarizes research on personality-driven differences in paraphrase preference. The researchers studied over 100,000 Facebook users and their scores on the Big Five personality traits. They found that users with different personality traits showed preferences for different paraphrases of words and phrases. Extraversion correlated with preferences for shorter, more concrete and imageable paraphrases, while Openness correlated with preferences for more complex paraphrases involving older-acquired words. Analyzing stylistic differences in paraphrase choice provides insights into psycholinguistic theories and could be used to generate text tailored to different personality traits.

1. Personality Driven Differences in Paraphrase
Preference
Daniel Preot¸iuc-Pietro
Joint work with
Jordan Carpenter (Kenan Institute for Ethics, Duke)
Lyle Ungar (Computer & Information Science, UPenn)
3 August 2017

2. Motivation
User attribute prediction from text is successful:
Age (Rao et al. 2010 ACL)
Gender (Burger et al. 2011 EMNLP)
Location (Eisenstein et al. 2010 EMNLP)
Personality (Schwartz et al. 2013 PLoS One)
Impact (Lampos et al. 2014 EACL)
Political Orientation (Volkova et al. 2014 ACL)
Mental Illness (Coppersmith et al. 2014 ACL)
Occupation (Preot¸iuc-Pietro et al. 2015 ACL)
Income (Preot¸iuc-Pietro et al. 2015 PLoS One)

3. However...
Most text prediction methods uncover topical differences
relative frequency
a aa
correlation strength
Openness to Experience

4. However...
Most text prediction methods uncover topical differences
relative frequency
a aa
correlation strength
Extraversion

5. Stylistic differences
We need to be aware of style differences, rather than topical
Not useful for many practical applications that adapt to traits:
machine translation (Mirkin et al. 2015 EMNLP, Rabinovich et al 2017 EACL)
agents (e.g. customer service, tutoring)
controlling for gender or racial bias

6. Stylistic differences
One type of stylistic difference is phrase choice in context.
Splendid
Excellent
Remarkable
Source: https://wikispaces.psu.edu/display/P5PFL/TRAIT+Theory+Page
Openness
Magnificent
Fabulous
Tremendous
Source: http://inwilmingtonde.com/events/thanksgiving-eve-karaoke
Extraversion

7. Data
We study the Big Five personality traits:
115,312 Facebook users
Personality scores obtained through the MyPersonality
app (Kosinski et al, 2013)
For each trait, take top and bottom 20% of users

8. Paraphrasing
Paraphrases – alternative ways to convey the same information
Paraphrase Database (PPDB) 2.0 (Pavlick et al. 2015 ACL):
annotated with type and confidence (filter ‘equivalent’
paraphrases with >.2 confidence)
>6M automatically derived paraphrase pairs
we use only 1–3 grams
difference in a pair more than just change of stopwords or
root form of word

9. Prediction
.603
.551
.519
.551 .549
.573
.589
.578
.553
.590
.623
.639
.597 .593
.631
0.50
0.55
0.60
0.65
Openness Conscientiousness Extraversion Agreeableness Neuroticism
Paraphrases only Phrases w/o paraphrases All Phrases
Accuracy, Naive Bayes, 90-10 training-testing, balanced data

10. Quantifying Preference
Straightforward measure:
Extraversion(w) = log
Extravert(w)
Introvert(w)
(1)
Within a paraphrase pair (w1, w2), the difference
Extraversion(w1) − Extraversion(w2) is the stylistic distance.
Used previously to study paraphrase preference across age,
gender and occupational class (Preot¸iuc-Pietro, Xu & Ungar, AAAI 2016).

11. Linguistic Theories
Study which attributes of words in a pair are preferred by one
group:
Word Length in Characters
Word Length in Syllables
Simple proxies for word complexity
Affective Norms: Valence, Arousal, Dominance
14k rated words
Valence: suicide (0.15) → bacon (0.70) → laughter (1)
Concreteness
40k rated words: spirituality (1) → morning (3.44) → tiger (5)
Age of Acquisition
30k rated words: great (5.05) → splendid (7.22) → tremendous (10.63)
More in the paper ...

12. Linguistic Theories
.163
-.068
-.043
-.012
-.041
.067
.182
-.002
-.014
.036
-.001
.050
.045
.097
-.060
.010
.031
.028
.050
.047
.080
-.032
-.007
.030
.005
.040
.016
.010
-.014
.023
.000
-.024
.004
-.020
-.065
-.200 -.150 -.100 -.050 .000 .050 .100 .150 .200
Age of Acquisition
Concreteness
Dominance
Arousal
Happiness
#Syllables
Word Length
Openess Conscientiousness Extraversion Agreeableness Neuroticism
Correlation coefficients between paraphrase pair preference
and user group usage.

13. Linguistic Theories
.163
-.068
-.043
-.012
-.041
.067
.182
-.002
-.014
.036
-.001
.050
.045
.097
-.060
.010
.031
.028
.050
.047
.080
-.032
-.007
.030
.005
.040
.016
.010
-.014
.023
.000
-.024
.004
-.020
-.065
-.200 -.150 -.100 -.050 .000 .050 .100 .150 .200
Age of Acquisition
Concreteness
Dominance
Arousal
Happiness
#Syllables
Word Length
Openess Conscientiousness Extraversion Agreeableness Neuroticism
Correlation coefficients between paraphrase pair preference
and user group usage.

14. Take Aways
Stylistic difference between user groups have important
applicability
Paraphrase choice contains valuable information
Shed light on psycholinguistic theories
Potential way to generate text perceived to be from a
different user trait
See our EMNLP 2017 paper (Preot¸iuc-Pietro, Guntuku, Ungar - Controlling
Human Perception of Basic User Traits)

15. Thank you!
Questions?