Incivility Detection in Online Comments

Farig Sadeque; Stephen Rains; Yotam Shmargad; Kate Kenski; Kevin Coe; Steven Bethard

doi:10.18653/v1/S19-1031

Incivility Detection in Online Comments

Farig Sadeque, Stephen Rains, Yotam Shmargad, Kate Kenski, Kevin Coe, Steven Bethard

Correct Metadata for

Important: The Anthology treat PDFs as authoritative. Please use this form only to correct data that is out of line with the PDF. See our corrections guidelines if you need to change the PDF.

Title Adjust the title. Retain tags such as <fixed-case>.

Authors Adjust author names and order to match the PDF.

Abstract Correct abstract if needed. Retain XML formatting tags such as <tex-math>.

Verification against PDF Ensure that the new title/authors match the snapshot below. (If there is no snapshot or it is too small, consult the PDF.)

Authors concatenated from the text boxes above:

ALL author names match the snapshot above—including middle initials, hyphens, and accents.

Abstract

Incivility in public discourse has been a major concern in recent times as it can affect the quality and tenacity of the discourse negatively. In this paper, we present neural models that can learn to detect name-calling and vulgarity from a newspaper comment section. We show that in contrast to prior work on detecting toxic language, fine-grained incivilities like namecalling cannot be accurately detected by simple models like logistic regression. We apply the models trained on the newspaper comments data to detect uncivil comments in a Russian troll dataset, and find that despite the change of domain, the model makes accurate predictions.

Anthology ID:: S19-1031
Volume:: Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)
Month:: June
Year:: 2019
Address:: Minneapolis, Minnesota
Editors:: Rada Mihalcea, Ekaterina Shutova, Lun-Wei Ku, Kilian Evang, Soujanya Poria
Venue:: *SEM
SIGs:: SIGSEM | SIGLEX
Publisher:: Association for Computational Linguistics
Note:
Pages:: 283–291
Language:
URL:: https://aclanthology.org/S19-1031/
DOI:: 10.18653/v1/S19-1031
Bibkey:
Cite (ACL):: Farig Sadeque, Stephen Rains, Yotam Shmargad, Kate Kenski, Kevin Coe, and Steven Bethard. 2019. Incivility Detection in Online Comments. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 283–291, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):: Incivility Detection in Online Comments (Sadeque et al., *SEM 2019)
Copy Citation:
PDF:: https://aclanthology.org/S19-1031.pdf

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{sadeque-etal-2019-incivility,
    title = "Incivility Detection in Online Comments",
    author = "Sadeque, Farig  and
      Rains, Stephen  and
      Shmargad, Yotam  and
      Kenski, Kate  and
      Coe, Kevin  and
      Bethard, Steven",
    editor = "Mihalcea, Rada  and
      Shutova, Ekaterina  and
      Ku, Lun-Wei  and
      Evang, Kilian  and
      Poria, Soujanya",
    booktitle = "Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*{SEM} 2019)",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/S19-1031/",
    doi = "10.18653/v1/S19-1031",
    pages = "283--291",
    abstract = "Incivility in public discourse has been a major concern in recent times as it can affect the quality and tenacity of the discourse negatively. In this paper, we present neural models that can learn to detect name-calling and vulgarity from a newspaper comment section. We show that in contrast to prior work on detecting toxic language, fine-grained incivilities like namecalling cannot be accurately detected by simple models like logistic regression. We apply the models trained on the newspaper comments data to detect uncivil comments in a Russian troll dataset, and find that despite the change of domain, the model makes accurate predictions."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="sadeque-etal-2019-incivility">
    <titleInfo>
        <title>Incivility Detection in Online Comments</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Farig</namePart>
        <namePart type="family">Sadeque</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Stephen</namePart>
        <namePart type="family">Rains</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Yotam</namePart>
        <namePart type="family">Shmargad</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kate</namePart>
        <namePart type="family">Kenski</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kevin</namePart>
        <namePart type="family">Coe</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Steven</namePart>
        <namePart type="family">Bethard</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Rada</namePart>
            <namePart type="family">Mihalcea</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Shutova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lun-Wei</namePart>
            <namePart type="family">Ku</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Kilian</namePart>
            <namePart type="family">Evang</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Soujanya</namePart>
            <namePart type="family">Poria</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Minneapolis, Minnesota</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Incivility in public discourse has been a major concern in recent times as it can affect the quality and tenacity of the discourse negatively. In this paper, we present neural models that can learn to detect name-calling and vulgarity from a newspaper comment section. We show that in contrast to prior work on detecting toxic language, fine-grained incivilities like namecalling cannot be accurately detected by simple models like logistic regression. We apply the models trained on the newspaper comments data to detect uncivil comments in a Russian troll dataset, and find that despite the change of domain, the model makes accurate predictions.</abstract>
    <identifier type="citekey">sadeque-etal-2019-incivility</identifier>
    <identifier type="doi">10.18653/v1/S19-1031</identifier>
    <location>
        <url>https://aclanthology.org/S19-1031/</url>
    </location>
    <part>
        <date>2019-06</date>
        <extent unit="page">
            <start>283</start>
            <end>291</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T Incivility Detection in Online Comments
%A Sadeque, Farig
%A Rains, Stephen
%A Shmargad, Yotam
%A Kenski, Kate
%A Coe, Kevin
%A Bethard, Steven
%Y Mihalcea, Rada
%Y Shutova, Ekaterina
%Y Ku, Lun-Wei
%Y Evang, Kilian
%Y Poria, Soujanya
%S Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota
%F sadeque-etal-2019-incivility
%X Incivility in public discourse has been a major concern in recent times as it can affect the quality and tenacity of the discourse negatively. In this paper, we present neural models that can learn to detect name-calling and vulgarity from a newspaper comment section. We show that in contrast to prior work on detecting toxic language, fine-grained incivilities like namecalling cannot be accurately detected by simple models like logistic regression. We apply the models trained on the newspaper comments data to detect uncivil comments in a Russian troll dataset, and find that despite the change of domain, the model makes accurate predictions.
%R 10.18653/v1/S19-1031
%U https://aclanthology.org/S19-1031/
%U https://doi.org/10.18653/v1/S19-1031
%P 283-291

Download as File

Markdown (Informal)

[Incivility Detection in Online Comments](https://aclanthology.org/S19-1031/) (Sadeque et al., *SEM 2019)

Incivility Detection in Online Comments (Sadeque et al., *SEM 2019)

ACL

Farig Sadeque, Stephen Rains, Yotam Shmargad, Kate Kenski, Kevin Coe, and Steven Bethard. 2019. Incivility Detection in Online Comments. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 283–291, Minneapolis, Minnesota. Association for Computational Linguistics.