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This paper aims at showing how quantitative corpus linguistic analysis can inform qualitative analysis of digital media discourse with respect to the mediality of language in use. Using the example of protest discourse in Twitter, in the field of anti-Islamic ‘Pegida’ demonstrations, a three-step method of collecting, reducing and interpreting salient data is proposed. Each step is aligned with operative medial features of the microblog: hashtags, retweets and @-interactions. The exemplary analysis reveals the importance of discussions of attendance numbers in protest discourse and the asymmetry between administrative (i.e. the police) and non-administrative discourse agents. Furthermore, it exemplifies how frequency analysis and sequence analysis can be combined for research in media linguistics.
We investigate whether non-configurational languages, which display more word order variation than configurational ones, require more training data for a phenomenon to be parsed successfully. We perform a tightly controlled study comparing the dative alternation for English (a configurational language), German, and Russian (both non-configurational). More specifically, we compare the performance of a dependency parser when only canonical word order is present with its performance on data sets when all word orders are present. Our results show that for all languages, canonical data not only is easier to parse, but there exists no direct correspondence between the size of training sets containing free(er) word order variation and performance.
Some 25 years ago, a large-scale repatriation of Russian Germans began. As a result, more than 2,5 million people that grew up in the USSR, Russia, or other post-Soviet states, became German citizens who had native or near-native command of the Russian language. The uncomfortable differences they exhibited in comparison to those who were supposed to accept them as equals, yet failed to do so, compelled them to search for self-designations that would accommodate their new identity and to bond together to form a new minority. The authors examine the attempts of Soviet/Russian Germans to redefine their ethnic identity in terms of not just blood but also language and culture, focusing on two particular cases: the use of the name Rusak in the internet forums of the repatriated immigrants; and the linguistic-cultural practices of the older generation of immigrants.
Prosodic constructions used to compete for the speaking turn in conversation have been widely studied (French & Local (1983), Kurtić et al. (2013)). Usually, turn competition arises in overlapping talk between at least two speakers. Coordination between participants in their prosodic design of talk (Szczepek-Reed, 2006) and social action (Gorisch et al. 2012), as well as entrainment in more general terms (Levitan et al. 2011), is well established in the literature. Nevertheless, previous studies on turn competition and overlap do not investigate the prosodic design of turn competitive incomings in reference to the orientation of the speakers to each other. Rather, they assume that prosodic constructions are used for turn competition regardless of the co-participants’ design of the turn. In this paper, we ask whether the prosodic design of turn competitive talk is co-constructed between two participants talking in overlap. More specifically, we investigate whether the prosodic design of one participant’s in overlap talk is developed with respect to the interlocutor’s prosodic features during the same portion of overlapped talk, and whether this prosodic matching can discriminate between the overlaps that are competitive and those that are not. 183 Our analyses are based on two-speaker overlaps drawn from a corpus of multi-party face-to face conversation between four friends recorded in British English (Kurtic et al. 2012). 3407 instances of twospeaker overlaps have been extracted from 4 hours of talk. Two independent conversation analysts performed the interactional categorisation of overlaps into competitive and non-competitive for all these two-speaker overlap instances and achieved a good agreement of alpha=0.807 (Krippendorff 2004) as measured on a subset of 808 overlaps selected for our initial analysis. For the analysis of prosodic features we focus on F0 related features: mean, slope, span and contour, all of which have previously been shown to be used by each overlapping speaker separately for turn competition (Kurtic et al. 2009; Oertel et al. 2012). We investigate the similarity in F0 mean, slope and span by correlating these features across the two participants. For F0 contour, a similarity coefficient is computed using dynamic programming method described in Gorisch et al. (2012). We consider the difference in F0 contour similarity in competitive and non-competitive overlaps as an indication of intonational matching being a turn competitive resource. We conduct these analyses for overlaps that are clearly competitive or noncompetitive as indicated by inter-annotator agreement. In addition, we qualitatively explore those cases that annotators disagree on in order to investigate whether they reveal further important interactional or prosodic features of in-overlap talk. Our preliminary results suggest that conversational participants attend and adapt to the interlocutor during overlap depending on whether they return competition or not. We explain our findings in relation to previous work on turn competition in overlap, discuss the quantitative method employed and also address the possible consequences of our results for the study of prosodic realization of other social actions in conversation.
Feedback utterances are among the most frequent in dialogue. Feedback is also a crucial aspect of all linguistic theories that take social interaction involving language into account. However, determining communicative functions is a notoriously difficult task both for human interpreters and systems. It involves an interpretative process that integrates various sources of information. Existing work on communicative function classification comes from either dialogue act tagging where it is generally coarse grained concerning the feed- back phenomena or it is token-based and does not address the variety of forms that feed- back utterances can take. This paper introduces an annotation framework, the dataset and the related annotation campaign (involving 7 raters to annotate nearly 6000 utterances). We present its evaluation not merely in terms of inter-rater agreement but also in terms of usability of the resulting reference dataset both from a linguistic research perspective and from a more applicative viewpoint.