@inproceedings{calderwood-etal-2017-understanding,
title = "Understanding the Semantics of Narratives of Interpersonal Violence through Reader Annotations and Physiological Reactions",
author = "Calderwood, Alexander and
Pruett, Elizabeth A. and
Ptucha, Raymond and
Homan, Christopher and
Ovesdotter Alm, Cecilia",
editor = "Blanco, Eduardo and
Morante, Roser and
Saur{\'\i}, Roser",
booktitle = "Proceedings of the Workshop Computational Semantics Beyond Events and Roles",
month = apr,
year = "2017",
address = "Valencia, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-1801",
doi = "10.18653/v1/W17-1801",
pages = "1--9",
abstract = "Interpersonal violence (IPV) is a prominent sociological problem that affects people of all demographic backgrounds. By analyzing how readers interpret, perceive, and react to experiences narrated in social media posts, we explore an understudied source for discourse about abuse. We asked readers to annotate Reddit posts about relationships with vs. without IPV for stakeholder roles and emotion, while measuring their galvanic skin response (GSR), pulse, and facial expression. We map annotations to coreference resolution output to obtain a labeled coreference chain for stakeholders in texts, and apply automated semantic role labeling for analyzing IPV discourse. Findings provide insights into how readers process roles and emotion in narratives. For example, abusers tend to be linked with violent actions and certain affect states. We train classifiers to predict stakeholder categories of coreference chains. We also find that subjects{'} GSR noticeably changed for IPV texts, suggesting that co-collected measurement-based data about annotators can be used to support text annotation.",
}
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<abstract>Interpersonal violence (IPV) is a prominent sociological problem that affects people of all demographic backgrounds. By analyzing how readers interpret, perceive, and react to experiences narrated in social media posts, we explore an understudied source for discourse about abuse. We asked readers to annotate Reddit posts about relationships with vs. without IPV for stakeholder roles and emotion, while measuring their galvanic skin response (GSR), pulse, and facial expression. We map annotations to coreference resolution output to obtain a labeled coreference chain for stakeholders in texts, and apply automated semantic role labeling for analyzing IPV discourse. Findings provide insights into how readers process roles and emotion in narratives. For example, abusers tend to be linked with violent actions and certain affect states. We train classifiers to predict stakeholder categories of coreference chains. We also find that subjects’ GSR noticeably changed for IPV texts, suggesting that co-collected measurement-based data about annotators can be used to support text annotation.</abstract>
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%0 Conference Proceedings
%T Understanding the Semantics of Narratives of Interpersonal Violence through Reader Annotations and Physiological Reactions
%A Calderwood, Alexander
%A Pruett, Elizabeth A.
%A Ptucha, Raymond
%A Homan, Christopher
%A Ovesdotter Alm, Cecilia
%Y Blanco, Eduardo
%Y Morante, Roser
%Y Saurí, Roser
%S Proceedings of the Workshop Computational Semantics Beyond Events and Roles
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F calderwood-etal-2017-understanding
%X Interpersonal violence (IPV) is a prominent sociological problem that affects people of all demographic backgrounds. By analyzing how readers interpret, perceive, and react to experiences narrated in social media posts, we explore an understudied source for discourse about abuse. We asked readers to annotate Reddit posts about relationships with vs. without IPV for stakeholder roles and emotion, while measuring their galvanic skin response (GSR), pulse, and facial expression. We map annotations to coreference resolution output to obtain a labeled coreference chain for stakeholders in texts, and apply automated semantic role labeling for analyzing IPV discourse. Findings provide insights into how readers process roles and emotion in narratives. For example, abusers tend to be linked with violent actions and certain affect states. We train classifiers to predict stakeholder categories of coreference chains. We also find that subjects’ GSR noticeably changed for IPV texts, suggesting that co-collected measurement-based data about annotators can be used to support text annotation.
%R 10.18653/v1/W17-1801
%U https://aclanthology.org/W17-1801
%U https://doi.org/10.18653/v1/W17-1801
%P 1-9
Markdown (Informal)
[Understanding the Semantics of Narratives of Interpersonal Violence through Reader Annotations and Physiological Reactions](https://aclanthology.org/W17-1801) (Calderwood et al., SemBEaR 2017)
ACL