<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="martin-2017-community2vec">
    <titleInfo>
        <title>community2vec: Vector representations of online communities encode semantic relationships</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Trevor</namePart>
        <namePart type="family">Martin</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2017-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Second Workshop on NLP and Computational Social Science</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Dirk</namePart>
            <namePart type="family">Hovy</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Svitlana</namePart>
            <namePart type="family">Volkova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">David</namePart>
            <namePart type="family">Bamman</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">David</namePart>
            <namePart type="family">Jurgens</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Brendan</namePart>
            <namePart type="family">O’Connor</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Oren</namePart>
            <namePart type="family">Tsur</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">A</namePart>
            <namePart type="given">Seza</namePart>
            <namePart type="family">Doğruöz</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Vancouver, Canada</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Vector embeddings of words have been shown to encode meaningful semantic relationships that enable solving of complex analogies. This vector embedding concept has been extended successfully to many different domains and in this paper we both create and visualize vector representations of an unstructured collection of online communities based on user participation. Further, we quantitatively and qualitatively show that these representations allow solving of semantically meaningful community analogies and also other more general types of relationships. These results could help improve community recommendation engines and also serve as a tool for sociological studies of community relatedness.</abstract>
    <identifier type="citekey">martin-2017-community2vec</identifier>
    <identifier type="doi">10.18653/v1/W17-2904</identifier>
    <location>
        <url>https://aclanthology.org/W17-2904</url>
    </location>
    <part>
        <date>2017-08</date>
        <extent unit="page">
            <start>27</start>
            <end>31</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T community2vec: Vector representations of online communities encode semantic relationships
%A Martin, Trevor
%Y Hovy, Dirk
%Y Volkova, Svitlana
%Y Bamman, David
%Y Jurgens, David
%Y O’Connor, Brendan
%Y Tsur, Oren
%Y Doğruöz, A. Seza
%S Proceedings of the Second Workshop on NLP and Computational Social Science
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F martin-2017-community2vec
%X Vector embeddings of words have been shown to encode meaningful semantic relationships that enable solving of complex analogies. This vector embedding concept has been extended successfully to many different domains and in this paper we both create and visualize vector representations of an unstructured collection of online communities based on user participation. Further, we quantitatively and qualitatively show that these representations allow solving of semantically meaningful community analogies and also other more general types of relationships. These results could help improve community recommendation engines and also serve as a tool for sociological studies of community relatedness.
%R 10.18653/v1/W17-2904
%U https://aclanthology.org/W17-2904
%U https://doi.org/10.18653/v1/W17-2904
%P 27-31

Markdown (Informal)

[community2vec: Vector representations of online communities encode semantic relationships](https://aclanthology.org/W17-2904) (Martin, NLP+CSS 2017)

• community2vec: Vector representations of online communities encode semantic relationships (Martin, NLP+CSS 2017)

ACL

• Trevor Martin. 2017. community2vec: Vector representations of online communities encode semantic relationships. In Proceedings of the Second Workshop on NLP and Computational Social Science, pages 27–31, Vancouver, Canada. Association for Computational Linguistics.