Publikation:

Stuttgart’s Black Thursday on Twitter : Mapping Political Protests with Social Media Data

Lade...
Vorschaubild

Dateien

Zu diesem Dokument gibt es keine Dateien.

Datum

2014

Autor:innen

Jürgens, Pascal

Herausgeber:innen

Kontakt

ISSN der Zeitschrift

Electronic ISSN

ISBN

Bibliografische Daten

Verlag

Schriftenreihe

Auflagebezeichnung

URI (zitierfähiger Link)
ArXiv-ID

Internationale Patentnummer

Angaben zur Forschungsförderung

Projekt

Open Access-Veröffentlichung
Core Facility der Universität Konstanz

Gesperrt bis

Titel in einer weiteren Sprache

Publikationstyp
Beitrag zu einem Sammelband
Publikationsstatus
Published

Erschienen in

CANTIJOCH, Marta, ed., Rachel GIBSON, ed., Stephen WARD, ed.. Analyzing Social Media Data and Web Networks. London: Palgrave Macmillan, 2014, pp. 154-196. ISBN 978-1-349-44680-3. Available under: doi: 10.1057/9781137276773_7

Zusammenfassung

Event detection based on textual data is an approach often used in the social sciences. The method has been used predominantly in the fields of international politics (Schrodt 2010) and public opinion research (Landmann and Zuell 2008). Event detection presupposes that major events leave traces in textual documents. By automatically identifying events in publicly available documents, researchers can establish timelines of events relevant to their research. For example, in international politics, researchers work on how to reliably identify political actors, time and topics from official documents, hoping to establish comprehensive and detailed maps of international treaties and conflicts. Based on these maps, they aim to develop models of the dynamics of conflict (Brandt et al. 2011). In public opinion research, one goal is to automatically deduce major events from newspaper coverage. This might be a first step in calculating the impact of these events on changes in public opinion (Landmann and Zuell 2008).

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
320 Politik

Schlagwörter

Konferenz

Rezension
undefined / . - undefined, undefined

Forschungsvorhaben

Organisationseinheiten

Zeitschriftenheft

Zugehörige Datensätze in KOPS

Zitieren

ISO 690JUNGHERR, Andreas, Pascal JÜRGENS, 2014. Stuttgart’s Black Thursday on Twitter : Mapping Political Protests with Social Media Data. In: CANTIJOCH, Marta, ed., Rachel GIBSON, ed., Stephen WARD, ed.. Analyzing Social Media Data and Web Networks. London: Palgrave Macmillan, 2014, pp. 154-196. ISBN 978-1-349-44680-3. Available under: doi: 10.1057/9781137276773_7
BibTex
@incollection{Jungherr2014Stutt-36521,
  year={2014},
  doi={10.1057/9781137276773_7},
  title={Stuttgart’s Black Thursday on Twitter : Mapping Political Protests with Social Media Data},
  isbn={978-1-349-44680-3},
  publisher={Palgrave Macmillan},
  address={London},
  booktitle={Analyzing Social Media Data and Web Networks},
  pages={154--196},
  editor={Cantijoch, Marta and Gibson, Rachel and Ward, Stephen},
  author={Jungherr, Andreas and Jürgens, Pascal}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36521">
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Jürgens, Pascal</dc:creator>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/36521"/>
    <dc:contributor>Jürgens, Pascal</dc:contributor>
    <dcterms:abstract xml:lang="eng">Event detection based on textual data is an approach often used in the social sciences. The method has been used predominantly in the fields of international politics (Schrodt 2010) and public opinion research (Landmann and Zuell 2008). Event detection presupposes that major events leave traces in textual documents. By automatically identifying events in publicly available documents, researchers can establish timelines of events relevant to their research. For example, in international politics, researchers work on how to reliably identify political actors, time and topics from official documents, hoping to establish comprehensive and detailed maps of international treaties and conflicts. Based on these maps, they aim to develop models of the dynamics of conflict (Brandt et al. 2011). In public opinion research, one goal is to automatically deduce major events from newspaper coverage. This might be a first step in calculating the impact of these events on changes in public opinion (Landmann and Zuell 2008).</dcterms:abstract>
    <dc:language>eng</dc:language>
    <dcterms:title>Stuttgart’s Black Thursday on Twitter : Mapping Political Protests with Social Media Data</dcterms:title>
    <dc:contributor>Jungherr, Andreas</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-01-05T14:19:08Z</dcterms:available>
    <dc:creator>Jungherr, Andreas</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-01-05T14:19:08Z</dc:date>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/42"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:issued>2014</dcterms:issued>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/42"/>
  </rdf:Description>
</rdf:RDF>

Interner Vermerk

xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter

Kontakt
URL der Originalveröffentl.

Prüfdatum der URL

Prüfungsdatum der Dissertation

Finanzierungsart

Kommentar zur Publikation

Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
Begutachtet
Diese Publikation teilen