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The English language has taken advantage of the Digital Revolution to establish itself as the global language; however, only 28.6 %of Internet users speak English as their native language. Machine Trans-lation (MT) is a powerful technology that can bridge this gap. In devel-opment since the mid-20th century, MT has become available to every Internet user in the last decade, due to free online MT services. This paper aims to discuss the implications that these tools may have for the privacy of their users and how they are addressed by EU data protec-tion law. It examines the data-flows in respect of the initial processing (both from the perspective of the user and the MT service provider) and potential further processing that may be undertaken by the MT service provider.
The ubiquity of smartphones has been recognised within conversation analysis as having an impact on conversational structures and on the participants’ interactional involvement. However, most of the previous studies have relied exclusively on video recordings of overall encounters and have not systematically considered what is taking place on the device. Due to the personal nature of smartphones and their small displays, onscreen activities are of limited visibility and are thus potentially opaque for both the co-present participants (“participant opacity”) and the researchers (“analytical opacity”). While opacity can be an inherent feature of smartphones in general, analytical opacity might not be desirable for research purposes. This chapter discusses how a recording set-up consisting of static cameras, wearable cameras and dynamic screen captures allowed us to address the analytical opacity of mobile devices. Excerpts from multi-source video data of everyday encounters will illustrate how the combination of multiple perspectives can increase the visibility of interactional phenomena, reveal new analytical objects and improve analytical granularity. More specifically, these examples will emphasise the analytical advantages and challenges of a combined recording set-up with regard to smartphone use as multiactivity, the role of the affordances of the mobile device, and the prototypicality and “naturalness” of the recorded practices.
Content analysis provides a useful and multifaceted, methodological framework for Twitter analysis. CAQDAS tools support the structuring of textual data by enabling categorising and coding. Depending on the research objective, it may be appropriate to choose a mixed-methods approach that combines quantitative and qualitative elements of analysis and plays out their respective advantages to the greatest possible extent while minimising their shortcomings. In this chapter, we will discuss CAQDAS speech act analysis of tweets as an example of software-assisted content analysis. We start with some elementary thoughts on the challenges of the collection and evaluation of Twitter data before we give a brief description of the potentials and limitations of using the software QDA Miner (as one typical example for possible analysis programmes). Our focus will lie on analytical features that can be particularly helpful in speech act analysis of tweets.
One major issue in the accomplishment of contrasts in conversation is lexical choice of items which carry the semantic Ioad of the two states of affair which are represented as being opposed to one another. These items or expressions are co-selected to be understood as being contrastively related to each other. In this paper, it is argued that the activity of contrasting itself provides them with a specific local opposite meaning which they would not obtain in other contexts. Practices of contrastingare thus seen as an example of conversational activities which creatively and systematically affect situated meanings. Basedon data from various genres, such as meetings, mediation sessions and conversations, the paper discusses two practices of contrasting, their sequential construction and their interpretative effects. It is concluded that the interpretative effects of conversational contrasting rest on the sequential deployment oflinguistic resources and on the cognitive procedures of frame-based interpretation and constructing a maximally contrastive interpretation for the co-selected expressions.
Speech islands are historically and developmentally unique and will inevitably disappear within the next decades. We urgently need to preserve their remains and exploit what is left in order to make research on language-in-contact and historical as well as current comparative language research possible.
The Archive for Spoken German (AGD) at the Institute for German Language collects, fosters and archives data from completed research projects and makes them available to the wider research community.
Besides large variation corpora and corpora of conversational speech, the archive already contains a range of collections of data on German speech minorities. The latter will be outlined in this chapter. Some speech island data is already made available through the personal service of the AGD, or the database of spoken German (DGD), e.g. data on Australian German, Unserdeutsch, or German in North America. Some corpora are still being prepared for publication, but still important to document for potentially interested research projects. We therefore also explain the current problems and efforts related to the curation of speech island data, from the digitization of recordings and the collection of metadata, to the integration of transcriptions, annotations and other ways of accessing and sharing data.
Contemporary studies on the characteristics of natural language benefit enormously from the increasing amount of linguistic corpora. Aside from text and speech corpora, corpora of computer-mediated communication (CMC) Position themselves between orality and literacy, and beyond that provide in- sight into the impact of "new", mainly intemet-based media on language beha- viour. In this paper, we present an empirical attempt to work with annotated CMC corpora for the explanation of linguistic phenomena. In concrete terms, we implement machine leaming algorithms to produce decision trees that reveal rules and tendencies about the use of genitive markers in German.
This paper deals with multiword lexemes (MWLs), focussing on two types of verbal MWLs: verbal idioms and support verb constructions. We discuss the characteristic properties of MWLs, namely nonstandard compositionality, restricted substitutability of components, and restricted morpho-syntactic flexibility, and we show how these properties may cause serious problems during the analysis, generation, and transfer steps of machine translation systems. In order to cope with these problems, MT lexicons need to provide detailed descriptions of MWL properties. We list the types of information which we consider the necessary minimum for a successful processing of MWLs, and report on some feasibility studies aimed at the automatic extraction of German verbal multiword lexemes from text corpora and machine-readable dictionaries.
Different Views on Markup
(2010)
In this chapter, two different ways of grouping information represented in document markup are examined: annotation levels, referring to conceptual levels of description, and annotation layers, referring to the technical realisation of markup using e.g. document grammars. In many current XML annotation projects, multiple levels are integrated into one layer, often leading to the problem of having to deal with overlapping hierarchies. As a solution, we propose a framework for XML-based multiple, independent XML annotation layers for one text, based on an abstract representation of XML documents with logical predicates. Two realisations of the abstract representation are presented, a Prolog fact base format together with an application architecture, and a specification for XML native databases. We conclude with a discussion of projects that have currently adopted this framework.