<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="marinov-etal-2020-topic">
    <titleInfo>
        <title>Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Boris</namePart>
        <namePart type="family">Marinov</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Jennifer</namePart>
        <namePart type="family">Spenader</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Tommaso</namePart>
        <namePart type="family">Caselli</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2020-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Third Workshop on Computational Modeling of People‘s Opinions, Personality, and Emotion‘s in Social Media</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Malvina</namePart>
            <namePart type="family">Nissim</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Viviana</namePart>
            <namePart type="family">Patti</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Barbara</namePart>
            <namePart type="family">Plank</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Esin</namePart>
            <namePart type="family">Durmus</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Barcelona, Spain (Online)</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>The paper focuses on a large collection of Dutch tweets from the Netherlands to get an insight into the perception and reactions of users during the early months of the COVID-19 pandemic. We focused on five major user communities of users: government and health organizations, news media, politicians, the general public and conspiracy theory supporters, investigating differences among them in topic dominance and the expressions of emotions. Through topic modeling we monitor the evolution of the conversation about COVID-19 among these communities. Our results indicate that the national focus on COVID-19 shifted from the virus itself to its impact on the economy between February and April. Surprisingly, the overall emotional public response appears to be substantially positive and expressing trust, although differences can be observed in specific group of users.</abstract>
    <identifier type="citekey">marinov-etal-2020-topic</identifier>
    <location>
        <url>https://aclanthology.org/2020.peoples-1.9/</url>
    </location>
    <part>
        <date>2020-12</date>
        <extent unit="page">
            <start>87</start>
            <end>98</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic
%A Marinov, Boris
%A Spenader, Jennifer
%A Caselli, Tommaso
%Y Nissim, Malvina
%Y Patti, Viviana
%Y Plank, Barbara
%Y Durmus, Esin
%S Proceedings of the Third Workshop on Computational Modeling of People‘s Opinions, Personality, and Emotion‘s in Social Media
%D 2020
%8 December
%I Association for Computational Linguistics
%C Barcelona, Spain (Online)
%F marinov-etal-2020-topic
%X The paper focuses on a large collection of Dutch tweets from the Netherlands to get an insight into the perception and reactions of users during the early months of the COVID-19 pandemic. We focused on five major user communities of users: government and health organizations, news media, politicians, the general public and conspiracy theory supporters, investigating differences among them in topic dominance and the expressions of emotions. Through topic modeling we monitor the evolution of the conversation about COVID-19 among these communities. Our results indicate that the national focus on COVID-19 shifted from the virus itself to its impact on the economy between February and April. Surprisingly, the overall emotional public response appears to be substantially positive and expressing trust, although differences can be observed in specific group of users.
%U https://aclanthology.org/2020.peoples-1.9/
%P 87-98

Markdown (Informal)

[Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic](https://aclanthology.org/2020.peoples-1.9/) (Marinov et al., PEOPLES 2020)

• Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic (Marinov et al., PEOPLES 2020)

ACL

• Boris Marinov, Jennifer Spenader, and Tommaso Caselli. 2020. Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic. In Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media, pages 87–98, Barcelona, Spain (Online). Association for Computational Linguistics.