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Mediatisierte Praktiken: Zur Rekontextualisierung von Anschlusskommunikation in den Sozialen Medien
(2016)
Mediatisierte Praktiken sind Gefüge kommunikativer Handlungen, die im Zuge der gesellschaftlichen Mediatisierung aufkommen, Technologien digitaler Kommunikation einbeziehen und an prä-digitale Vorgänger enger oder loser angebunden sind. Der Beitrag arbeitet den Begriff der mediatisierten Praktiken durch die Engführung zweier Forschungsstränge, der soziolinguistischen Praktiken-Forschung und der kommunikationswissenschaftlichen Mediatisierungsforschung, heraus. Rahmenbedingungen für die Mediatisierung sprachlicher Praktiken werden in fünf Dimensionen systematisiert: Formatierung, Beteiligungsrollen, Temporalität, Transkontextualität und Intermedialität. Zudem werden zwei Wege der Entstehung mediatisierter Praktiken durch „lineare“ bzw. „integrative“ Rekontextualisierung von Elementen früherer sprachlicher Praktiken unterschieden. Zur empirischen Flankierung dienen zwei Fallbeispiele der mediatisierten Anschlusskommunikation: die rezeptionsbegleitende Kommentierung der Krimiserie „Tatort“ auf Twitter einerseits, die Praktik der redaktionellen Intervention auf der Facebook-Präsenz der Nachrichtensendung Tagesschau andererseits.
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.
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 https://projects.fzai.h-da.de/iggsa/
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.