Sprache im 20. Jahrhundert. Gegenwartssprache
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Both for psychology and linguistics, emotion concepts are a continuing challenge for analysis in several respects. In this contribution, we take up the language of emotion as an object of study from several angles. First, we consider how frame semantic analyses of this domain by the FrameNet project have been developing over time, due to theory-internal as well as application-oriented goals, towards ever more fine-grained distinctions and greater within-frame consistency. Second, we compare how FrameNet’s linguistically oriented analysis of lexical items in the emotion domain compares to the analysis by domain experts of the experiences that give rise (directly or indirectly) to the lexical items. And finally, we consider to what extent frame semantic analysis can capture phenomena such as connotation and inference about attitudes, which are important in the field of sentiment analysis and opinion mining, even if they do not involve the direct evocation of emotion.
The current paper presents a corpus containing 35 dialogues of spontaneously spoken southern German, including half an hour of articulography for 13 of the speakers. Speakers were seated in separate recording chambers, mimicking a telephone call, and recorded on individual audio channels. The corpus provides manually corrected word boundaries and automatically aligned segment boundaries. Annotations are provided in the Praat format. In addition to audio recordings, speakers filled out a detailed questionnaire, assessing among others their audio-visual consumption habits.
In this paper, we present a GOLD standard of part-of-speech tagged transcripts of spoken German. The GOLD standard data consists of four annotation layers – transcription (modified orthography), normalization (standard orthography), lemmatization and POS tags – all of which have undergone careful manual quality control. It comes with guidelines for the manual POS annotation of transcripts of German spoken data and an extended version of the STTS (Stuttgart Tübingen Tagset) which accounts for phenomena typically found in spontaneous spoken German. The GOLD standard was developed on the basis of the Research and Teaching Corpus of Spoken German, FOLK, and is, to our knowledge, the first such dataset based on a wide variety of spontaneous and authentic interaction types. It can be used as a basis for further development of language technology and corpus linguistic applications for German spoken language.
The present study introduces articulography, the measurement of the position of tongue and lips during speech, as a promising method to the study of dialect variation. By using generalized additive modeling to analyze articulatory trajectories, we are able to reliably detect aggregate group differences, while simultaneously taking into account the individual variation across dozens of speakers. Our results on the basis of Dutch dialect data show clear differences between the southern and the northern dialect with respect to tongue position, with a more frontal tongue position in the dialect from Ubbergen (in the southern half of the Netherlands) than in the dialect of Ter Apel (in the northern half of the Netherlands). Thus articulography appears to be a suitable tool to investigate structural differences in pronunciation at the dialect level.
This paper explores on the basis of empirical research, how patterns of interaction and argumentation in political discourse on Twitter evolve as translocal communities in the creative shape of “joint digital storytelling”. Joint storytelling embraces coordinated activities by multiple actors focusing on a shared topic. By adding personal information and evaluation, participants construct an open narrative format, which can be inviting and inspiring for others, who then join in with their own narratives. This model will be exemplified by analyzing a large amount of tweets (107,000) collected during a political conflict between proponents and adversaries of a local traffic project in Germany. Analysis is based on (1) the textual level, (2) the operative level (hashtags, @- and RT-Symbol, hyperlinks etc.) and (3) the visual level of storytelling (embedded photos, videos). Results show a new way of creating translocal online communities and political deliberation.