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The article deals with communicative failures of journalists in “YouTube” celebrity video interviews in the Ukrainian and German linguacultures from the point of view of social interaction and the theory of speech genres at all structural levels of the communicative genre construction, establishing common and distinctive features in both linguacultures. The analysis made it possible to conclude that behind a language (speech) failure there is a violation caused by a journalist, a respondent, or an external noise.
Der vorliegende Beitrag setzt sich mit dem computergestützten Transkriptionsverfahren arabisch-deutscher Gesprächsdaten für interaktionsbezogene Untersuchungen auseinander. Zunächst werden wesentliche methodische Herausforderungen der gesprächsanalytischen Arbeit adressiert: Hinsichtlich der derzeitigen Korpustechnologie ermöglicht die Verwendung von arabischen Schriftzeichen in einem mehrsprachigen, bidirektionalen Transkript keine analysegerechte Rekonstruktion von Reziprozität, Linearität und Simultaneität sprachlichen Handelns. Zudem ist die Verschriftung von arabischen Gesprächsdaten aufgrund der unzureichenden (gesprächsanalytischen) Beschäftigung mit den standardfernen Varietäten und gesprochensprachlichen Phänomenen erschwert. Daher widmet sich der zweite Teil des Beitrags den bisher erarbeiteten und erprobten Lösungsansätzen ̶ einem stringenten, gesprächsanalytisch fundierten Transkriptionssystem für gesprochenes Arabisch.
The paper deals with the process of computer-aided transcription regarding Arabic-German data material for interaction-based studies. First of all, it sheds light upon some major methodological challenges posed by the conversation-analytic approaches: due to current corpus technology, the reciprocity, linearity, and simultaneity of linguistic activities cannot be reconstructed in an analytically proper way when using the Arabic characters in multilingual and bidirectional transcripts. The difficulty of transcribing Arabic encounters is also compounded by the fact that Spoken Arabic as well as its varieties and phenomena have not been standardised enough (for conversation-analytic purposes). Therefore, the second part of this paper is dedicated to preliminary, self-developed solutions, namely a systematic method for transcribing Spoken Arabic.
You might not know what a “smombie” is, but you have certainly already met one today. In public streets and places, the so-called “smartphone zombies” regularly cross our ways. They walk slowly, in peculiar ways, their eyes and fingers focused on their smartphone displays. While some cities have already introduced specific walking lanes or ground-level traffic signs for smartphone users “on the go”, it is not only road safety that is at stake. Frequently hunching over our phones causes cervical pain, we are addicted to likes on social media, and the fear of missing out prevents us from switching off our phones. If asked if mobile device use is possibly harmful to our bodies and minds, most people would spontaneously agree. Our social skills seem to constantly diminish since smartphones have become an everyday tool: we stick to them like glue while waiting for the bus, while walking, while eating, even while being with others. Will we turn into social zombies in the end?
Special Issue: Mobile Medienpraktiken im Spannungsfeld von Öffentlichkeit, Privatheit und Anonymität
(2019)
In German oral discourse, previous research has shown that okay can be used both as a response token (e.g., for agreeing with the previous turn or for claiming a certain degree of understanding) and as a discourse marker (e.g., for closing conversational topics or sequences and/or indicating transitions). This contribution focuses on the use of okay as a response token and how it is connected with the speakers’ interactional state of knowledge (their understanding, their assumptions etc.). The analysis is based on video recorded everyday conversations in German and a sequential, micro-analytic approach (multimodal conversation analysis). The main function of conversational okay in the selected data set is related to indicating the acceptance of prior information. By okay, speakers however claim acceptance of a piece of information that they can’t verify or check. The analysis contrasts different sequences containing okay only with sequences in which change-of-state tokens such as ah and achso co-occur with okay. This illustrates that okay itself does not index prior information as new, and that it is not used for agreeing with or for confirming prior information. Instead it enables the speaker to adopt a kind of neutral, “non-agreeing” position towards a given piece of information.