Emoji Usage Across Platforms: A Case Study for the Charlottesville Event

Khyati Mahajan; Samira Shaikh

Emoji Usage Across Platforms: A Case Study for the Charlottesville Event

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

We study emoji usage patterns across two social media platforms, one of them considered a fringe community called Gab, and the other Twitter. We find that Gab tends to comparatively use more emotionally charged emoji, but also seems more apathetic towards the violence during the event, while Twitter takes a more empathetic approach to the event.

Anthology ID:: W19-3651
Volume:: Proceedings of the 2019 Workshop on Widening NLP
Month:: August
Year:: 2019
Address:: Florence, Italy
Editors:: Amittai Axelrod, Diyi Yang, Rossana Cunha, Samira Shaikh, Zeerak Waseem
Venue:: WiNLP
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 160–162
Language:
URL:: https://aclanthology.org/W19-3651/
DOI:
Bibkey:
Cite (ACL):: Khyati Mahajan and Samira Shaikh. 2019. Emoji Usage Across Platforms: A Case Study for the Charlottesville Event. In Proceedings of the 2019 Workshop on Widening NLP, pages 160–162, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):: Emoji Usage Across Platforms: A Case Study for the Charlottesville Event (Mahajan & Shaikh, WiNLP 2019)
Copy Citation:

Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{mahajan-shaikh-2019-emoji,
    title = "Emoji Usage Across Platforms: A Case Study for the Charlottesville Event",
    author = "Mahajan, Khyati  and
      Shaikh, Samira",
    editor = "Axelrod, Amittai  and
      Yang, Diyi  and
      Cunha, Rossana  and
      Shaikh, Samira  and
      Waseem, Zeerak",
    booktitle = "Proceedings of the 2019 Workshop on Widening NLP",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W19-3651/",
    pages = "160--162",
    abstract = "We study emoji usage patterns across two social media platforms, one of them considered a fringe community called Gab, and the other Twitter. We find that Gab tends to comparatively use more emotionally charged emoji, but also seems more apathetic towards the violence during the event, while Twitter takes a more empathetic approach to the event."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="mahajan-shaikh-2019-emoji">
    <titleInfo>
        <title>Emoji Usage Across Platforms: A Case Study for the Charlottesville Event</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Khyati</namePart>
        <namePart type="family">Mahajan</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Samira</namePart>
        <namePart type="family">Shaikh</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 2019 Workshop on Widening NLP</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Amittai</namePart>
            <namePart type="family">Axelrod</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Diyi</namePart>
            <namePart type="family">Yang</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Rossana</namePart>
            <namePart type="family">Cunha</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Samira</namePart>
            <namePart type="family">Shaikh</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Zeerak</namePart>
            <namePart type="family">Waseem</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Florence, Italy</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We study emoji usage patterns across two social media platforms, one of them considered a fringe community called Gab, and the other Twitter. We find that Gab tends to comparatively use more emotionally charged emoji, but also seems more apathetic towards the violence during the event, while Twitter takes a more empathetic approach to the event.</abstract>
    <identifier type="citekey">mahajan-shaikh-2019-emoji</identifier>
    <location>
        <url>https://aclanthology.org/W19-3651/</url>
    </location>
    <part>
        <date>2019-08</date>
        <extent unit="page">
            <start>160</start>
            <end>162</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T Emoji Usage Across Platforms: A Case Study for the Charlottesville Event
%A Mahajan, Khyati
%A Shaikh, Samira
%Y Axelrod, Amittai
%Y Yang, Diyi
%Y Cunha, Rossana
%Y Shaikh, Samira
%Y Waseem, Zeerak
%S Proceedings of the 2019 Workshop on Widening NLP
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F mahajan-shaikh-2019-emoji
%X We study emoji usage patterns across two social media platforms, one of them considered a fringe community called Gab, and the other Twitter. We find that Gab tends to comparatively use more emotionally charged emoji, but also seems more apathetic towards the violence during the event, while Twitter takes a more empathetic approach to the event.
%U https://aclanthology.org/W19-3651/
%P 160-162

Download as File

Markdown (Informal)

[Emoji Usage Across Platforms: A Case Study for the Charlottesville Event](https://aclanthology.org/W19-3651/) (Mahajan & Shaikh, WiNLP 2019)

Emoji Usage Across Platforms: A Case Study for the Charlottesville Event (Mahajan & Shaikh, WiNLP 2019)

ACL

Khyati Mahajan and Samira Shaikh. 2019. Emoji Usage Across Platforms: A Case Study for the Charlottesville Event. In Proceedings of the 2019 Workshop on Widening NLP, pages 160–162, Florence, Italy. Association for Computational Linguistics.