Show simple item record

dc.contributor.author
Pröllochs, Nicolas
dc.contributor.author
Feuerriegel, Stefan
dc.contributor.author
Neumann, Dirk
dc.date.accessioned
2019-01-07T14:55:05Z
dc.date.available
2018-12-05T16:37:23Z
dc.date.available
2018-12-13T10:04:14Z
dc.date.available
2018-12-18T08:57:34Z
dc.date.available
2019-01-07T14:55:05Z
dc.date.issued
2018-12-21
dc.identifier.issn
1932-6203
dc.identifier.other
10.1371/journal.pone.0209323
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/309052
dc.identifier.doi
10.3929/ethz-b-000309052
dc.description.abstract
Information forms the basis for all human behavior, including the ubiquitous decision-making that people constantly perform in their every day lives. It is thus the mission of researchers to understand how humans process information to reach decisions. In order to facilitate this task, this work proposes LASSO regularization as a statistical tool to extract decisive words from textual content in order to study the reception of granular expressions in natural language. This differs from the usual use of the LASSO as a predictive model and, instead, yields highly interpretable statistical inferences between the occurrences of words and an outcome variable. Accordingly, the method suggests direct implications for the social sciences: it serves as a statistical procedure for generating domain-specific dictionaries as opposed to frequently employed heuristics. In addition, researchers can now identify text segments and word choices that are statistically decisive to authors or readers and, based on this knowledge, test hypotheses from behavioral research.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Public Library of Science
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
Statistical Inferences for Polarity Identification in Natural Language
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
PLoS ONE
ethz.journal.volume
13
en_US
ethz.journal.issue
12
en_US
ethz.journal.abbreviated
PLoS ONE
ethz.pages.start
e0209323
en_US
ethz.size
21 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
San Francicsco, CA
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::09623 - Feuerriegel, Stefan (ehemalig) / Feuerriegel, Stefan (former)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::09623 - Feuerriegel, Stefan (ehemalig) / Feuerriegel, Stefan (former)
en_US
ethz.date.deposited
2018-12-05T16:37:27Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2019-01-07T14:55:11Z
ethz.rosetta.lastUpdated
2022-03-28T22:01:02Z
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=Statistical%20Inferences%20for%20Polarity%20Identification%20in%20Natural%20Language&rft.jtitle=PLoS%20ONE&rft.date=2018-12-21&rft.volume=13&rft.issue=12&rft.spage=e0209323&rft.issn=1932-6203&rft.au=Pr%C3%B6llochs,%20Nicolas&Feuerriegel,%20Stefan&Neumann,%20Dirk&rft.genre=article&rft_id=info:doi/10.1371/journal.pone.0209323&
 Search print copy at ETH Library

Files in this item

Thumbnail

Publication type

Show simple item record