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Smooth turn-taking in conversation depends in part on speakers being able to communicate their intention to hold or cede the floor. Both prosodic and gestural cues have been shown to be used in this context. We investigate the interplay of pitch movements and hand gestures at locations at which speaker change becomes relevant, comparing their use in German and Swedish. We find that there are some shared functions of prosody and gesture with regard to turn-taking in the two languages, but that these shared functions appear to be mediated by the different phonological demands on pitch in the two languages.
Looking at gestures as a means for communication, they can serve conversational participants at several levels. As co-speech gestures, they can add information to the verbally expressed content and they can serve to manage turn-taking. In order to look closer at the interplay between these resources in face-to face conversation, we annotated hand gestures, syntactic completion points and the related turn-organisation, and measured the timing of gesture strokes and their lexical/phrasal referent. In a case study on German, we observe the trend that speakers vary less in gesturelexis on- and offsets when keeping the turn after syntactic completions than at speaker changes, backchannel or other locations of a conversation. This indicates that timing properties of non-verbal cues interact with verbal cues to manage turn-taking.
We examine the new task of detecting derogatory compounds (e.g. curry muncher). Derogatory compounds are much more difficult to detect than derogatory unigrams (e.g. idiot) since they are more sparsely represented in lexical resources previously found effective for this task (e.g. Wiktionary). We propose an unsupervised classification approach that incorporates linguistic properties of compounds. It mostly depends on a simple distributional representation. We compare our approach against previously established methods proposed for extracting derogatory unigrams.
We discuss the impact of data bias on abusive language detection. We show that classification scores on popular datasets reported in previous work are much lower under realistic settings in which this bias is reduced. Such biases are most notably observed on datasets that are created by focused sampling instead of random sampling. Datasets with a higher proportion of implicit abuse are more affected than datasets with a lower proportion.
We present a descriptive analysis on the two datasets from the shared task on Source, Subjective Expression and Target Extraction from Political Speeches (STEPS), the only existing German dataset for opinion role extraction of its size. Our analysis discusses the individual properties of the three components, subjective expressions, sources and targets and their relations towards each other. Our observations should help practitioners and researchers when building a system to extract opinion roles from German data.
A Supervised learning approach for the extraction of opinion sources and targets from German text
(2019)
We present the first systematic supervised learning approach for the extraction of opinion sources and targets on German language data. A wide choice of different features is presented, particularly syntactic features and generalization features. We point out specific differences between opinion sources and targets. Moreover, we explain why implicit sources can be extracted even with fairly generic features. In order to ensure comparability our classifier is trained and tested on the dataset of the STEPS shared task.
Variation im Sprachgebrauch - 'angenommen' und 'vorausgesetzt' als einbettende Prädikatsausdrücke
(2019)
Naming and titling have been discussed in sociolinguistics as markers of status or solidarity. However, these functions have not been studied on a larger scale or for social media data. We collect a corpus of tweets mentioning presidents of six G20 countries by various naming forms. We show that naming variation relates to stance towards the president in a way that is suggestive of a framing effect mediated by respectfulness. This confirms sociolinguistic theory of naming and titling as markers of status.
In this chapter, we discuss steps toward extending CMDI’s semantic interoperability beyond the Social Sciences and Humanities: We stress the need for an initial data curation step, in part supported by a relation registry that helps impose some structure on CMDI vocabulary; we describe the use of authority file information and other controlled vocabulary to help connecting CMDI-based metadata to existing Linked Data; we show how significant parts of CMDI-based metadata can be converted to bibliographic metadata standards and hence entered into library catalogs; and finally we describe first steps to convert CMDI-based metadata to RDF. The initial grassroots approach of CMDI (meaning that anybody can define metadata descriptors and components) mirrors the AAA slogan of the Semantic Web (“Anyone can say Anything about Any topic”). Ironically, this makes it hard to fully link CMDI-based metadata to other Semantic Web datasets. This paper discusses the challenges of this enterprise.
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/
Gerhard Stickel (*1937) bietet in diesem Band eine Auswahl aus seinen kleineren Arbeiten, die in der Zeit von 1966 bis 2019 erschienen sind. Geboten wird eine bunte Vielfalt von Aufsätzen und Essays zu Themen, mit denen der Autor sich in all den Jahren befasst hat, darunter: Negation, Kontrastive Grammatik, ‚Fremdwörter', Sprache und Geschlecht, Spracheinstellungen, Rechts- und Verwaltungssprache sowie deutsche und europäische Sprachpolitik. Mehrere Arbeiten sind während Stickels langjähriger Tätigkeit als Direktor des Instituts für Deutsche Sprache (1976-2002) entstanden und ab 2003 im Zusammenhang mit seinen Aufgaben in und für EFNIL, der European Federation of National Institutions for Language. Erhofft wird, dass auch die älteren Arbeiten über ihre Zeitgebundenheit hinaus für manche Linguistinnen und Linguisten sowie andere Sprachinteressierte anregend sein können.
Resistance and adaptation to newspeakerness in educational institutions: two tales from Estonia
(2019)
The term ‘new speaker’ has recently emerged as an attempt by sociolinguists not only to understand the diferent types of speaker profles that can be found in contemporary societies, but also to grasp the underlying processes of becoming a legitimate speaker in a given society. In this article, we combine the results from two studies situated in two educational institutions in Estonia in order to fnd out about speakers’ language attitudes and experiences in connection to learning and using Estonian. We concentrate on members of the international community who have relatively recently arrived to the country. Our results indicate that these speakers fuctuate between two prototypical discourses, which we broadly dub as ‘resistance’ and ‘adaptation’ to newspeakerness. Our study thereby adds to current debates on ‘new speaker’ and language policy issues by illustrating how tensions around language legitimacy are played out on the ground in a small nation state such as Estonia.