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This study investigated whether an analysis of narrative style (word use and cross-clausal syntax) of patients with symptoms of generalised anxiety and depression disorders can help predict the likelihood of successful participation in guided self-help. Texts by 97 people who had made contact with a primary care mental health service were analysed. Outcome measures were completion of the guided self-help programme, and change in symptoms assessed by a standardised scale (CORE-OM). Regression analyses indicated that some aspects of participants' syntax helped to predict completion of the programme, and that aspects of syntax and word use helped to predict improvement of symptoms. Participants using non-finite complement clauses with above-average frequency were four times more likely to complete the programme (95% confidence interval 1.4 to 11.7) than other participants. Among those who completed, the use of causation words and complex syntax (adverbial clauses) predicted improvement, accounting for 50% of the variation in well-being benefit. These results suggest that the analysis of narrative style can provide useful information for assessing the likelihood of success of individuals participating in a mental health guided self-help programme.
Temporal frames of reference
(2010)
Von Bush administration zu Kohl-Regierung: Englische Einflüsse auf deutsche Nominalkonstruktionen?
(2010)
In diesem Beitrag wird eine neue, funktional motivierte Systematik für den adnominalen Genitiv und entsprechende von-Phrasen, die zusammenfassend als ‘possessive Attribute’ bezeichnet werden, entwickelt. Sie beruht auf Erkenntnissen aus der sprachtypologischen Forschung und dem Vergleich mit anderen, vor allem germanischen Sprachen. Der Beschreibungsrahmen für die NP mit der übergreifenden ‘funktionalen Domäne’ der Referenz und den zugehörigen Subdomänen wird vorgestellt. Possessive Attribute können als eine Ausdrucksform der Subdomäne Modifikation bestimmt werden. Es wird gezeigt, dass possessive Attribute verschiedene funktionale Typen der Modifikation realisieren können: referentiell-verankernde (der Hut meiner Schwester), qualitative (ein Autor deutscher Herkunft) und klassifikatorische (ein Mann der Tat). Auch randständige possessive Attribute wie der ‘Teilungsgenitiv’ (eine Tasse heißen Tees) und der Identitätsgenitiv (das Laster der Unbescheidenheit) werden berücksichtigt. Die neue Ordnung possessiver Attribute nach funktionalen Subdomänen ist der traditionellen Einteilung vorzuziehen, insofern als sie lediglich Grundunterscheidungen gemäß dem referenzsemantischen Status des Modifikators (begrifflich versus referentiell) und nach dem Beitrag des Modifikators zur Bedeutungskomposition der NP (verankernd versus qualitativ bzw. klassifikatorisch) berücksichtigt. Zudem ist sie durch Testverfahren wie den Pronominalisierungstest abgesichert.
Within cognitive linguistics, there is an increasing awareness that the study of linguistic phenomena needs to be grounded in usage. Ideally, research in cognitive linguistics should be based on authentic language use, its results should be replicable, and its claims falsifiable. Consequently, more and more studies now turn to corpora as a source of data. While corpus-based methodologies have increased in sophistication, the use of corpus data is also associated with a number of unresolved problems. The study of cognition through off-line linguistic data is, arguably, indirect, even if such data fulfils desirable qualities such as being natural, representative and plentiful. Several topics in this context stand out as particularly pressing issues. This discussion note addresses (1) converging evidence from corpora and experimentation, (2) whether corpora mirror psychological reality, (3) the theoretical value of corpus linguistic studies of ‘alternations’, (4) the relation of corpus linguistics and grammaticality judgments, and, lastly, (5) the nature of explanations in cognitive corpus linguistics. We do not claim to resolve these issues nor to cover all possible angles; instead, we strongly encourage reactions and further discussion.
How (and when) do speakers generalise from memorised exemplars of a construction to a productive schema? The present paper presents a novel take on this issue by offering a corpus-based approach to semantic extension processes. Focusing on clusters of German ADJ N expressions involving the heavily polysemous adjective tief ‚deep’, it is shown that type frequency (a commonly used measure of productivity) needs to be relativised to distinct semantic classes within the overall usage spectrum of a given construction in order to predict the occurrence of novel types within a particular region of this spectrum. Some methodological and theoretical implications for usage-based linguistic model building are considered.
Standardly, verb-first (V1) conditionals are considered to be mere variants of wenn-conditionals; accordingly, left-peripheral V1-clauses are analyzed as embedded into the prefields of declarative apodosis clauses, just like their V-end counterparts. We challenge this view, proposing instead that dependent V1-clauses are syntactically unembedded/unintegrated, and, consequently, that postposed declarative apodosis clauses are either V2-declaratives with prefield ellipsis or V1-declaratives. We argue our case by presenting evidence that (i) wenn-clauses differ considerably from V1-clauses in semantic distribution, (ii) unlike wenn-clauses, V1-clauses do not meet the criteria for syntactic embedding, (iii) the alternatives entailed by (ii) for the structural analysis of a postposed apodosis both have empirical support. As for a syntactic analysis of V1-structures suited to these findings, we argue that a CP adjunction analysis is currently the best option available. We also point out connections between the semantic restrictions on V1-conditionals and the semantics of V1-interrogatives that are suggestive of a common semantic core, which raises hope that our background vision (ultimately, all dependent V-to-C clauses are semantically licensed substitutes for genuine subordinates) may also be true for V1-clauses.
Accentuation, Uncertainty and Exhaustivity - Towards a Model of Pragmatic Focus Interpretation
(2010)
This paper presents a model of pragmatic focus interpretation that is assumed to be part of a complete language comprehension model and that is inspired by Levelt's language processing model. The model is derived from our empirical data on the role of accentuation, prosodic indicators of uncertainty and context for pragmatic focus interpretation. In its present state, the model is restricted to these data, but nevertheless generates predictions.
This paper describes work directed towards the development of a syllable prominence-based prosody generation functionality for a German unit selection speech synthesis system. A general concept for syllable prominence-based prosody generation in unit selection synthesis is proposed. As a first step towards its implementation, an automated syllable prominence annotation procedure based on acoustic analyses has been performed on the BOSS speech corpus. The prominence labeling has been evaluated against an existing annotation of lexical stress levels and manual prominence labeling on a subset of the corpus. We discuss methods and results and give an outlook on further implementation steps.
In recent years, text classification in sentiment analysis has mostly focused on two types of classification, the distinction between objective and subjective text, i.e. subjectivity detection, and the distinction between positive and negative subjective text, i.e. polarity classification. So far, there has been little work examining the distinction between definite polar subjectivity and indefinite polar subjectivity. While the former are utterances which can be categorized as either positive or negative, the latter cannot be categorized as either of these two categories. This paper presents a small set of domain independent features to detect indefinite polar sentences. The features reflect the linguistic structure underlying these types of utterances. We give evidence for the effectiveness of these features by incorporating them into an unsupervised rule-based classifier for sentence-level analysis and compare its performance with supervised machine learning classifiers, i.e. Support Vector Machines (SVMs) and Nearest Neighbor Classifier (kNN). The data used for the experiments are web-reviews collected from three different domains.