Department Linguistik
Refine
Year of publication
Document Type
- Article (25)
- Monograph/Edited Volume (4)
Keywords
- Festschrift (2)
- Informationsstruktur (2)
- Linguistic annotation (2)
- Linguistik (2)
- Morphologie (2)
- Syntax (2)
- connective (2)
- festschrift (2)
- information structure (2)
- linguistics (2)
Adverbial connectives like therefore, which link a preceding 'external' to an 'internal' argument, can be regarded as anaphoric: The external argument is selected by an interpretation process akin to that of an event anaphor, and intervening material can appear between both arguments.
We report on a crowdsourcing experiment on the German connectives trotzdem and dennoch that studies factors that lead readers to assume such long-distance arguments: semantic plausibility of intervening material, 'subjective' versus 'objective' content, and the presence of an anaphoric morpheme in the connective.
We find that the type and content of the intervening material play an important role in argument choice.
We investigate the variation in oral and written language in terms of anaphoric distance (i.e., the textual distance between anaphors and their antecedents), expanding corpus-based research with experimental evidence.
Contrastive corpus studies demonstrate that oral genres include longer average anaphoric distance than written genres, if the distance is measured in terms of clauses (Fox, 1987; Aktas & Stede, 2020).
We designed an experiment in order to examine the contrasts in oral and written mediums, using the same genre.
We aim to gain more insight about the impact of the medium, in a situation where both mediums convey a similar level of spontaneity, informality and interactivity. We designed a story continuation study, where the participants are recruited via crowdsourcing.
To our knowledge, this is the first study of its kind, where anaphoric distance is manipulated systematically in a language production experiment in order to examine medium distinctions.
We observed that participants use more pronouns in oral medium than in written medium if the anaphoric distance is long.
This result is in line with the implications of the earlier corpus-based research. In addition, our results indicate that anaphoric distance has a larger effect in referential choice for the written medium.
Argument mining on twitter
(2021)
In the last decade, the field of argument mining has grown notably. However, only relatively few studies have investigated argumentation in social media and specifically on Twitter. Here, we provide the, to our knowledge, first critical in-depth survey of the state of the art in tweet-based argument mining. We discuss approaches to modelling the structure of arguments in the context of tweet corpus annotation, and we review current progress in the task of detecting argument components and their relations in tweets. We also survey the intersection of argument mining and stance detection, before we conclude with an outlook.
The notion of coherence relations is quite widely accepted in general, but concrete proposals differ considerably on the questions of how they should be motivated, which relations are to be assumed, and how they should be defined. This paper takes a "bottom-up" perspective by assessing the contribution made by linguistic signals (connectives), using insights from the relevant literature as well as verification by practical text annotation. We work primarily with the German language here and focus on the realm of contrast. Thus, we suggest a new inventory of contrastive connective functions and discuss their relationship to contrastive coherence relations that have been proposed in earlier work.
Reflecting in written form on one's teaching enactments has been considered a facilitator for teachers' professional growth in university-based preservice teacher education. Writing a structured reflection can be facilitated through external feedback. However, researchers noted that feedback in preservice teacher education often relies on holistic, rather than more content-based, analytic feedback because educators oftentimes lack resources (e.g., time) to provide more analytic feedback. To overcome this impediment to feedback for written reflection, advances in computer technology can be of use. Hence, this study sought to utilize techniques of natural language processing and machine learning to train a computer-based classifier that classifies preservice physics teachers' written reflections on their teaching enactments in a German university teacher education program. To do so, a reflection model was adapted to physics education. It was then tested to what extent the computer-based classifier could accurately classify the elements of the reflection model in segments of preservice physics teachers' written reflections. Multinomial logistic regression using word count as a predictor was found to yield acceptable average human-computer agreement (F1-score on held-out test dataset of 0.56) so that it might fuel further development towards an automated feedback tool that supplements existing holistic feedback for written reflections with data-based, analytic feedback.
Argumentation mining is a subfield of Computational Linguistics that aims (primarily) at automatically finding arguments and their structural components in natural language text. We provide a short introduction to this field, intended for an audience with a limited computational background. After explaining the subtasks involved in this problem of deriving the structure of arguments, we describe two other applications that are popular in computational linguistics: sentiment analysis and stance detection. From the linguistic viewpoint, they concern the semantics of evaluation in language. In the final part of the paper, we briefly examine the roles that these two tasks play in argumentation mining, both in current practice, and in possible future systems.
Newspaper text can be broadly divided in the classes ‘opinion’ (editorials, commentary, letters to the editor) and ‘neutral’ (reports). We describe a classification system for performing this separation, which uses a set of linguistically motivated features. Working with various English newspaper corpora, we demonstrate that it significantly outperforms bag-of-lemma and PoS-tag models. We conclude that the linguistic features constitute the best method for achieving robustness against change of newspaper or domain.
Connective-Lex
(2019)
In this paper, we present a tangible outcome of the TextLink network: a joint online database project displaying and linking existing and newly-created lexicons of discourse connectives in multiple languages. We discuss the definition and demarcation of the class of connectives that should be included in such a resource, and present the syntactic, semantic/pragmatic, and lexicographic information we collected. Further, the technical implementation of the database and the search functionality are presented. We discuss how the multilingual integration of several connective lexicons provides added value for linguistic researchers and other users interested in connectives, by allowing crosslinguistic comparison and a direct linking between discourse relational devices in different languages. Finally, we provide pointers for possible future extensions both in breadth (i.e., by adding lexicons for additional languages) and depth (by extending the information provided for each connective item and by strengthening the crosslinguistic links).