A Survey on Sentiment and Emotion Analysis for Computational Literary
Studies
E. Kim, and R. Klinger. (2018)cite arxiv:1808.03137Comment: Submitted for review to DHQ (http://www.digitalhumanities.org/dhq/).
Abstract
Emotions have often been a crucial part of compelling narratives: literature
tells about people with goals, desires, passions, and intentions. In the past,
classical literary studies usually scrutinized the affective dimension of
literature within the framework of hermeneutics. However, with emergence of the
research field known as Digital Humanities (DH) some studies of emotions in
literary context have taken a computational turn. Given the fact that DH is
still being formed as a science, this direction of research can be rendered
relatively new. At the same time, the research in sentiment analysis started in
computational linguistic almost two decades ago and is nowadays an established
field that has dedicated workshops and tracks in the main computational
linguistics conferences. This leads us to the question of what are the
commonalities and discrepancies between sentiment analysis research in
computational linguistics and digital humanities? In this survey, we offer an
overview of the existing body of research on sentiment and emotion analysis as
applied to literature. We precede the main part of the survey with a short
introduction to natural language processing and machine learning, psychological
models of emotions, and provide an overview of existing approaches to sentiment
and emotion analysis in computational linguistics. The papers presented in this
survey are either coming directly from DH or computational linguistics venues
and are limited to sentiment and emotion analysis as applied to literary text.
Description
A Survey on Sentiment and Emotion Analysis for Computational Literary Studies
%0 Generic
%1 kim2018survey
%A Kim, Evgeny
%A Klinger, Roman
%D 2018
%K emotion sentiment survey toread
%T A Survey on Sentiment and Emotion Analysis for Computational Literary
Studies
%U http://arxiv.org/abs/1808.03137
%X Emotions have often been a crucial part of compelling narratives: literature
tells about people with goals, desires, passions, and intentions. In the past,
classical literary studies usually scrutinized the affective dimension of
literature within the framework of hermeneutics. However, with emergence of the
research field known as Digital Humanities (DH) some studies of emotions in
literary context have taken a computational turn. Given the fact that DH is
still being formed as a science, this direction of research can be rendered
relatively new. At the same time, the research in sentiment analysis started in
computational linguistic almost two decades ago and is nowadays an established
field that has dedicated workshops and tracks in the main computational
linguistics conferences. This leads us to the question of what are the
commonalities and discrepancies between sentiment analysis research in
computational linguistics and digital humanities? In this survey, we offer an
overview of the existing body of research on sentiment and emotion analysis as
applied to literature. We precede the main part of the survey with a short
introduction to natural language processing and machine learning, psychological
models of emotions, and provide an overview of existing approaches to sentiment
and emotion analysis in computational linguistics. The papers presented in this
survey are either coming directly from DH or computational linguistics venues
and are limited to sentiment and emotion analysis as applied to literary text.
@misc{kim2018survey,
abstract = {Emotions have often been a crucial part of compelling narratives: literature
tells about people with goals, desires, passions, and intentions. In the past,
classical literary studies usually scrutinized the affective dimension of
literature within the framework of hermeneutics. However, with emergence of the
research field known as Digital Humanities (DH) some studies of emotions in
literary context have taken a computational turn. Given the fact that DH is
still being formed as a science, this direction of research can be rendered
relatively new. At the same time, the research in sentiment analysis started in
computational linguistic almost two decades ago and is nowadays an established
field that has dedicated workshops and tracks in the main computational
linguistics conferences. This leads us to the question of what are the
commonalities and discrepancies between sentiment analysis research in
computational linguistics and digital humanities? In this survey, we offer an
overview of the existing body of research on sentiment and emotion analysis as
applied to literature. We precede the main part of the survey with a short
introduction to natural language processing and machine learning, psychological
models of emotions, and provide an overview of existing approaches to sentiment
and emotion analysis in computational linguistics. The papers presented in this
survey are either coming directly from DH or computational linguistics venues
and are limited to sentiment and emotion analysis as applied to literary text.},
added-at = {2018-12-23T17:46:48.000+0100},
author = {Kim, Evgeny and Klinger, Roman},
biburl = {https://www.bibsonomy.org/bibtex/213265b3b07e43c27f5e9f8b7b300716e/hotho},
description = {A Survey on Sentiment and Emotion Analysis for Computational Literary Studies},
interhash = {4835e73a1580ba12aa5e6278315bbed8},
intrahash = {13265b3b07e43c27f5e9f8b7b300716e},
keywords = {emotion sentiment survey toread},
note = {cite arxiv:1808.03137Comment: Submitted for review to DHQ (http://www.digitalhumanities.org/dhq/)},
timestamp = {2018-12-23T17:46:48.000+0100},
title = {A Survey on Sentiment and Emotion Analysis for Computational Literary
Studies},
url = {http://arxiv.org/abs/1808.03137},
year = 2018
}