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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.
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.
Coherence relations are typically taken to link two clauses or larger units and to be signaled at the text surface by conjunctions and certain adverbials. Relations, however, also can hold within clauses, indicated by prepositions like despite, due to, or in case of, when these have an internal argument denoting an eventuality. Although these prepositions act as reliable cues to indicate a specific relation, others are lexically more neutral. We investigated this situation for the German preposition bei, which turns out to be highly ambiguous. We demonstrate the range of readings in a corpus study, proposing 6 more specific prepositions as a comprehensive substitution set. All these uses of bei share a common kernel meaning, which is missed by the standard accounts that assume lexical polysemy. We examine the range of coherence relations that can be signaled by bei and provide some factors here supporting the disambiguation task in a framework of discourse interpretation
ANNIS
(2004)
In this paper, we discuss the design and implementation of our first version of the database "ANNIS" ("ANNotation of Information Structure"). For research based on empirical data, ANNIS provides a uniform environment for storing this data together with its linguistic annotations. A central database promotes standardized annotation, which facilitates interpretation and comparison of the data. ANNIS is used through a standard web browser and offers tier-based visualization of data and annotations, as well as search facilities that allow for cross-level and cross-sentential queries. The paper motivates the design of the system, characterizes its user interface, and provides an initial technical evaluation of ANNIS with respect to data size and query processing.
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.
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.