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  1. Doing Digital History
    Autor*in: Roberts, Spencer
    Erschienen: 2015

    Communication Forums ; dg "Doing Digital History was a summer institute for mid-career American historians, sponsored by the National Endowment for the Humanities, Office of Digital Humanities, run by the Roy Rosenzweig Center for History in New... mehr

    Standort:
    Niedersächsische Staats- und Universitätsbibliothek Göttingen
    Signatur:
    HistGuide
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Gemeinsamer Bibliotheksverbund (GBV)

     

    Communication Forums ; dg "Doing Digital History was a summer institute for mid-career American historians, sponsored by the National Endowment for the Humanities, Office of Digital Humanities, run by the Roy Rosenzweig Center for History in New Media, George Mason University. The institute took place August 4-15, 2014 at GMU's Arlington campus. ... During the institute, participants, instructors, and graduate student assistants tweeted under the hashtag #doingdh14. Tweets from the institute were captured using Storify; tweets for recorded separately for Week One and Week Two. The entire Doing Digital History curriculum is available as a downloadable PDF (CC-BY-NC): DoingDH Curriculum 2014." [self-description]

     
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    Hinweise zum Inhalt
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schlagworte: George Mason University; Twitter <software platform>; Digital Humanities; George Mason University; Twitter <Softwareplattform>; Digital Humanities
    Bemerkung(en):

    Source: SUB
  2. Discourse of Twitter and social media
    [how we use language to create affiliation on the web]
    Autor*in: Zappavigna, Michele
    Erschienen: 2013
    Verlag:  Bloomsbury, London [u.a.]

    Standort:
    Technische Universität Chemnitz, Universitätsbibliothek
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Südwestdeutscher Bibliotheksverbund (SWB)

    Standort:
    Zentrale Hochschulbibliothek Flensburg
    Signatur:
    AP 15965 Z35
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Gemeinsamer Bibliotheksverbund (GBV)

    Standort:
    Universitätsbibliothek Heidelberg
    Signatur:
    2015 A 4254
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Südwestdeutscher Bibliotheksverbund (SWB)

    Standort:
    Universität Konstanz, Kommunikations-, Informations-, Medienzentrum (KIM)
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Südwestdeutscher Bibliotheksverbund (SWB)

    Standort:
    Universitätsbibliothek Leipzig
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Südwestdeutscher Bibliotheksverbund (SWB)

    Standort:
    Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek
    Fernleihe:
    keine Fernleihe
    Link zum Verbundkatalog:
    Südwestdeutscher Bibliotheksverbund (SWB)

    Standort:
    Universitätsbibliothek Mannheim
    Signatur:
    2014 A 1304
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe
    Link zum Verbundkatalog:
    Südwestdeutscher Bibliotheksverbund (SWB)
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    Hinweise zum Inhalt
    Quelle: Leibniz-Institut für Deutsche Sprache, Bibliothek
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Druck
    ISBN: 9781472531544; 1441141863; 9781441141866
    Weitere Identifier:
    9781472531544
    RVK Klassifikation: ES 158 ; HF 342 ; AP 15965
    Auflage/Ausgabe: 1. publ. in paperback
    Schriftenreihe: Bloomsbury discourse series
    Schlagworte: Soziales Netzwerk; Soziale Software; Diskursanalyse; Twitter <Softwareplattform>; Konversationsanalyse
    Umfang: XI, 227 S., Ill., graph. Darst., 24 cm
    Bemerkung(en):

    Enth. Literaturangaben und Register
  3. Legal issues related to the use of twitter data in language research
    Autor*in: Kamocki, Paweł ; Hannesschläger, Vanessa ; Hoorn, Esther ; Kelli, Aleksei ; Kupietz, Marc ; Lindén, Krister ; Puksas, Andrius
    Erschienen: 2021
    Verlag:  Utrecht : CLARIN ; Mannheim : Leibniz-Institut für Deutsche Sprache (IDS)

    Twitter data is used in a wide variety of research disciplines in Social Sciences and Humanities. Although most Twitter data is publicly available, its re-use and sharing raise many legal questions related to intellectual property and personal data... mehr

     

    Twitter data is used in a wide variety of research disciplines in Social Sciences and Humanities. Although most Twitter data is publicly available, its re-use and sharing raise many legal questions related to intellectual property and personal data protection. Moreover, the use of Twitter and its content is subject to the Terms of Service, which also regulate re-use and sharing. This extended abstract provides a brief analysis of these issues and introduces the new Academic Research product track, which enables authorized researchers to access Twitter API on a preferential basis.

     
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    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Aufsatz aus einem Sammelband
    Format: Online
    DDC Klassifikation: Recht (340); Sprache (400)
    Schlagworte: Recht; Twitter <Softwareplattform>; Forschungsdaten; Social Media; Sozialwissenschaften; Digital Humanities; Geistiges Eigentum; Datenschutz
    Lizenz:

    creativecommons.org/licenses/by/4.0/ ; info:eu-repo/semantics/openAccess
  4. Discussing best practices for the annotation of Twitter microtext
    Autor*in: Rehbein, Ines ; Visser, Emiel ; Lestmann, Nadine
    Erschienen: 2016
    Verlag:  Sofia : Bulgarian Academy of Sciences

    This paper contributes to the discussion on best practices for the syntactic analysis of non-canonical language, focusing on Twitter microtext. We present an annotation experiment where we test an existing POS tagset, the Stuttgart-Tübingen Tagset... mehr

     

    This paper contributes to the discussion on best practices for the syntactic analysis of non-canonical language, focusing on Twitter microtext. We present an annotation experiment where we test an existing POS tagset, the Stuttgart-Tübingen Tagset (STTS), with respect to its applicability for annotating new text from the social media, in particular from Twitter microblogs. We discuss different tagset extensions proposed in the literature and test our extended tagset on a set of 506 tweets (7.418 tokens) where we achieve an inter-annotator agreement for two human annotators in the range of 92.7 to 94.4 (k). Our error analysis shows that especially the annotation of Twitterspecific phenomena such as hashtags and at-mentions causes disagreements between the human annotators. Following up on this, we provide a discussion of the different uses of the @- and #-marker in Twitter and argue against analysing both on the POS level by means of an at-mention or hashtag label. Instead, we sketch a syntactic analysis which describes these phenomena by means of syntactic categories and grammatical functions.

     
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    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Konferenzveröffentlichung
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Syntaktische Analyse; Annotation; Twitter <Softwareplattform>
    Lizenz:

    rightsstatements.org/page/InC/1.0/ ; info:eu-repo/semantics/openAccess
  5. Overview of GermEval Task 2, 2019 shared task on the identification of offensive language
    Autor*in: Struß, Julia Maria ; Siegel, Melanie ; Ruppenhofer, Josef ; Wiegand, Michael ; Klenner, Manfred
    Erschienen: 2019
    Verlag:  München [u.a.] : German Society for Computational Linguistics & Language Technology und Friedrich-Alexander-Universität Erlangen-Nürnberg

    We present the second edition of the GermEval Shared Task on the Identification of Offensive Language. This shared task deals with the classification of German tweets from Twitter. Two subtasks were continued from the first edition, namely a... mehr

     

    We present the second edition of the GermEval Shared Task on the Identification of Offensive Language. This shared task deals with the classification of German tweets from Twitter. Two subtasks were continued from the first edition, namely a coarse-grained binary classification task and a fine-grained multi-class classification task. As a novel subtask, we introduce the classification of offensive tweets as explicit or implicit. The shared task had 13 participating groups submitting 28 runs for the coarse-grained task, another 28 runs for the fine-grained task, and 17 runs for the implicit-explicit task. We evaluate the results of the systems submitted to the shared task. The shared task homepage can be found at projects.fzai.h-da.de/iggsa/

     
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    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Konferenzveröffentlichung
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Deutsch; Beleidigung; Social Media; Twitter <Softwareplattform>; Tweet; Automatische Spracherkennung
    Lizenz:

    creativecommons.org/licenses/by-nc-sa/4.0/deed.de ; info:eu-repo/semantics/openAccess
  6. Doctor Who? Framing Through Names and Titles in German
    Autor*in: van den Berg, Esther ; Korfhage, Katharina ; Ruppenhofer, Josef ; Wiegand, Michael ; Markert, Katja
    Erschienen: 2020
    Verlag:  Paris : European Language Resources Association

    Entity framing is the selection of aspects of an entity to promote a particular viewpoint towards that entity. We investigate entity framing of political figures through the use of names and titles in German online discourse, enhancing current... mehr

     

    Entity framing is the selection of aspects of an entity to promote a particular viewpoint towards that entity. We investigate entity framing of political figures through the use of names and titles in German online discourse, enhancing current research in entity framing through titling and naming that concentrates on English only. We collect tweets that mention prominent German politicians and annotate them for stance. We find that the formality of naming in these tweets correlates positively with their stance. This confirms sociolinguistic observations that naming and titling can have a status-indicating function and suggests that this function is dominant in German tweets mentioning political figures. We also find that this status-indicating function is much weaker in tweets from users that are politically left-leaning than in tweets by right leaning users. This is in line with observations from moral psychology that left-leaning and right-leaning users assign different importance to maintaining social hierarchies.

     
    Export in Literaturverwaltung   RIS-Format
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    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Aufsatz aus einem Sammelband
    Format: Online
    DDC Klassifikation: Sprache (400)
    Schlagworte: Twitter <Softwareplattform>; Framing-Effekt; Social Media; Name; Akademischer Grad
    Lizenz:

    creativecommons.org/licenses/by-nc/4.0/ ; info:eu-repo/semantics/openAccess