@inproceedings{arican-etal-2021-creating,
title = "Creating Domain Dependent {T}urkish {W}ord{N}et and {S}enti{N}et",
author = {Ar{\i}can, Bilge Nas and
{\"O}z{\c{c}}elik, Merve and
Aslan, Deniz Baran and
Sarm{\i}{\c{s}}, Elif and
Parlar, Selen and
Y{\i}ld{\i}z, Olcay Taner},
editor = "Vossen, Piek and
Fellbaum, Christiane",
booktitle = "Proceedings of the 11th Global Wordnet Conference",
month = jan,
year = "2021",
address = "University of South Africa (UNISA)",
publisher = "Global Wordnet Association",
url = "https://aclanthology.org/2021.gwc-1.28",
pages = "243--251",
abstract = "A WordNet is a thesaurus that has a structured list of words organized depending on their meanings. WordNet represents word senses, all meanings a single lemma may have, the relations between these senses, and their definitions. Another study within the domain of Natural Language Processing is sentiment analysis. With sentiment analysis, data sets can be scored according to the emotion they contain. In the sentiment analysis we did with the data we received on the Tourism WordNet, we performed a domain-specific sentiment analysis study by annotating the data. In this paper, we propose a method to facilitate Natural Language Processing tasks such as sentiment analysis performed in specific domains via creating a specific-domain subset of an original Turkish dictionary. As the preliminary study, we have created a WordNet for the tourism domain with 14,000 words and validated it on simple tasks.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="arican-etal-2021-creating">
<titleInfo>
<title>Creating Domain Dependent Turkish WordNet and SentiNet</title>
</titleInfo>
<name type="personal">
<namePart type="given">Bilge</namePart>
<namePart type="given">Nas</namePart>
<namePart type="family">Arıcan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Merve</namePart>
<namePart type="family">Özçelik</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Deniz</namePart>
<namePart type="given">Baran</namePart>
<namePart type="family">Aslan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Elif</namePart>
<namePart type="family">Sarmış</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Selen</namePart>
<namePart type="family">Parlar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Olcay</namePart>
<namePart type="given">Taner</namePart>
<namePart type="family">Yıldız</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2021-01</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 11th Global Wordnet Conference</title>
</titleInfo>
<name type="personal">
<namePart type="given">Piek</namePart>
<namePart type="family">Vossen</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Christiane</namePart>
<namePart type="family">Fellbaum</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Global Wordnet Association</publisher>
<place>
<placeTerm type="text">University of South Africa (UNISA)</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>A WordNet is a thesaurus that has a structured list of words organized depending on their meanings. WordNet represents word senses, all meanings a single lemma may have, the relations between these senses, and their definitions. Another study within the domain of Natural Language Processing is sentiment analysis. With sentiment analysis, data sets can be scored according to the emotion they contain. In the sentiment analysis we did with the data we received on the Tourism WordNet, we performed a domain-specific sentiment analysis study by annotating the data. In this paper, we propose a method to facilitate Natural Language Processing tasks such as sentiment analysis performed in specific domains via creating a specific-domain subset of an original Turkish dictionary. As the preliminary study, we have created a WordNet for the tourism domain with 14,000 words and validated it on simple tasks.</abstract>
<identifier type="citekey">arican-etal-2021-creating</identifier>
<location>
<url>https://aclanthology.org/2021.gwc-1.28</url>
</location>
<part>
<date>2021-01</date>
<extent unit="page">
<start>243</start>
<end>251</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Creating Domain Dependent Turkish WordNet and SentiNet
%A Arıcan, Bilge Nas
%A Özçelik, Merve
%A Aslan, Deniz Baran
%A Sarmış, Elif
%A Parlar, Selen
%A Yıldız, Olcay Taner
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 11th Global Wordnet Conference
%D 2021
%8 January
%I Global Wordnet Association
%C University of South Africa (UNISA)
%F arican-etal-2021-creating
%X A WordNet is a thesaurus that has a structured list of words organized depending on their meanings. WordNet represents word senses, all meanings a single lemma may have, the relations between these senses, and their definitions. Another study within the domain of Natural Language Processing is sentiment analysis. With sentiment analysis, data sets can be scored according to the emotion they contain. In the sentiment analysis we did with the data we received on the Tourism WordNet, we performed a domain-specific sentiment analysis study by annotating the data. In this paper, we propose a method to facilitate Natural Language Processing tasks such as sentiment analysis performed in specific domains via creating a specific-domain subset of an original Turkish dictionary. As the preliminary study, we have created a WordNet for the tourism domain with 14,000 words and validated it on simple tasks.
%U https://aclanthology.org/2021.gwc-1.28
%P 243-251
Markdown (Informal)
[Creating Domain Dependent Turkish WordNet and SentiNet](https://aclanthology.org/2021.gwc-1.28) (Arıcan et al., GWC 2021)
ACL
- Bilge Nas Arıcan, Merve Özçelik, Deniz Baran Aslan, Elif Sarmış, Selen Parlar, and Olcay Taner Yıldız. 2021. Creating Domain Dependent Turkish WordNet and SentiNet. In Proceedings of the 11th Global Wordnet Conference, pages 243–251, University of South Africa (UNISA). Global Wordnet Association.