This document describes an experiment that studied how readers interpret texts about relationships with and without interpersonal violence (IPV). Readers annotated Reddit posts about relationships for 25 minutes on IPV and non-IPV texts. The annotations and semantic role labels assigned to abusers and victims were then analyzed and found to correspond with expectations - abusers were linked to negative tones while victims were linked to positive tones. The study aims to help develop models for automatically identifying stakeholders and IPV labels in texts to aid research on IPV.

1. • Problem: interpersonal violence
(IPV)
• 1 in 3 women and 1 in 4 men have
experienced IPV.
• Surveys for IPV are risky and
underpowered. Social media offers a
natural setting for discourse on IPV.
• We conducted an experiment which
allowed us to study:
• How readers interpret texts about
relationships without vs. with
interpersonal violence, and
• How interpretations correspond to
analysis by computational semantic
processing.
Alex Calderwood (adc9020@rit.edu)
Elizabeth Pruett, Ray Ptucha, Christopher M. Homan, Cecilia Ovesdotter Alm
Acknowledgements: This material is based upon work supported by the National Science Foundation under Award No. IIS-1559889. Any opinions, findings, and
conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Top role labels assigned to Abusers and Victims
after removing labels occurring for the Partner set
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P artne r S e co ndary Othe r Victim Victim-
S uppo rte r
Abuse r Abuse -Enable r Othe r
Possible Annotator Agreement Active Annotator Agreement
• Readers read and annotated public
Reddit posts about relationships
without and with IPV for 25 min per
trial.
Abuser Victim
Abusers are linked to negative tone
Victim-Supporter to positive
Our aim is to aid the behavioral health
field’s study of IPV. We will develop
models to automatically assign:
• Stakeholder labels to a co-reference
chain with stakeholder mentions
• IPV labels to a text given its associated
set of coreference chains.
• After removing labels common to
all relationships, the sets of
Abuser and Victim semantic role
labels are almost disjoint.
• Computer generated semantic
labels match expectations.
• We identified candidate features
for machine-based analysis tasks.
Semantic role
labeling aims to
identify and
name the roles
of sentence
constituents.
Top role labels assigned to Partners in relationships w/o IPV
Abusers are linked to anger in texts
Evidence of gender in co-reference chains corresponding to
Abuser and Victim stakeholder annotations
Text annotation interface used in study
Data flow for analysis
Reader experiment process
Setup for text annotation study
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#labelcorefrencechains(40texts)
Annotator strongly agree on several stakeholder labels
Central stakeholders are identified more in the text accounts
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0.12
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RelativeFrequency
P o sitive Ne gative
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0.002
0.004
0.006
0.008
0.01
0.012
0.014
0.016
0.018
0.02
RelativeFrequency
Anx ie ty Ange r S ad
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RelativeFrequency
First P e rso n S e co nd P e rso n Third P e rso n
Part of speech changes based on stakeholder label