Purpose
– To evaluate and extend, existing natural language processing techniques into the domain of informal online political discussions.
Design/methodology/approach
– A database of postings from a US political discussion site was collected, along with self‐reported political orientation data for the users. A variety of sentiment analysis, text classification, and social network analysis methods were applied to the postings and evaluated against the users' self‐descriptions.
Findings
– Purely text‐based methods performed poorly, but could be improved using techniques which took into account the users' position in the online community.
Research limitations/implications
– The techniques we applied here are fairly simple, and more sophisticated learning algorithms may yield better results for text‐based classification.
Practical implications
– This work suggests that social network analysis is an important tool for performing natural language processing tasks with informal web texts.
Originality/value
– This research extends sentiment analysis to a new subject domain (US politics) and a new text genre (informal online discusssions).
Description
Taking sides: user classification for informal online political discourse: Internet Research: Vol 18, No 2
%0 Journal Article
%1 noauthororeditor
%A Malouf, Robert
%A Mullen, Tony
%D 2008
%J Internet Research
%K discours political sentiment thema thema:userclassification user
%P 177-190
%T Taking sides: user classification for informal online political discourse
%U http://www.emeraldinsight.com/doi/pdfplus/10.1108/10662240810862239
%V 18
%X Purpose
– To evaluate and extend, existing natural language processing techniques into the domain of informal online political discussions.
Design/methodology/approach
– A database of postings from a US political discussion site was collected, along with self‐reported political orientation data for the users. A variety of sentiment analysis, text classification, and social network analysis methods were applied to the postings and evaluated against the users' self‐descriptions.
Findings
– Purely text‐based methods performed poorly, but could be improved using techniques which took into account the users' position in the online community.
Research limitations/implications
– The techniques we applied here are fairly simple, and more sophisticated learning algorithms may yield better results for text‐based classification.
Practical implications
– This work suggests that social network analysis is an important tool for performing natural language processing tasks with informal web texts.
Originality/value
– This research extends sentiment analysis to a new subject domain (US politics) and a new text genre (informal online discusssions).
@article{noauthororeditor,
abstract = {Purpose
– To evaluate and extend, existing natural language processing techniques into the domain of informal online political discussions.
Design/methodology/approach
– A database of postings from a US political discussion site was collected, along with self‐reported political orientation data for the users. A variety of sentiment analysis, text classification, and social network analysis methods were applied to the postings and evaluated against the users' self‐descriptions.
Findings
– Purely text‐based methods performed poorly, but could be improved using techniques which took into account the users' position in the online community.
Research limitations/implications
– The techniques we applied here are fairly simple, and more sophisticated learning algorithms may yield better results for text‐based classification.
Practical implications
– This work suggests that social network analysis is an important tool for performing natural language processing tasks with informal web texts.
Originality/value
– This research extends sentiment analysis to a new subject domain (US politics) and a new text genre (informal online discusssions).},
added-at = {2017-04-19T21:10:24.000+0200},
author = {Malouf, Robert and Mullen, Tony},
biburl = {https://www.bibsonomy.org/bibtex/26ce2021d26a2342a1e2f72731bad60b3/lautenschlager},
description = {Taking sides: user classification for informal online political discourse: Internet Research: Vol 18, No 2},
interhash = {531bf2b7978fe71b83eb8dcd30da2af2},
intrahash = {6ce2021d26a2342a1e2f72731bad60b3},
journal = {Internet Research},
keywords = {discours political sentiment thema thema:userclassification user},
pages = {177-190},
timestamp = {2017-05-29T13:49:04.000+0200},
title = {Taking sides: user classification for informal online political discourse},
url = {http://www.emeraldinsight.com/doi/pdfplus/10.1108/10662240810862239},
volume = 18,
year = 2008
}