Managing conflict on WhatsApp

García-Gómez, Antonio

doi:10.1075/jlac.00015.gar

Cited by 10 publications

(3 citation statements)

References 29 publications

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“…From a linguistic perspective, researchers have centred on its multimodality (Calero Vaquera 2014, Sampietro 2016a, 2016b, Aull 2019, politeness (Flores-Salgado and Castineira-Benitez 2018), users' profile statuses (Sánchez-Moya and Cruz-Moya 2015b, Maíz-Arévalo 2018), the use of typographical variation (Sánchez-Moya and Cruz-Moya 2015a), the use of laughter as a resource to manage conversations (Petitjean and Morel 2017), its positive effects to increase phatic talk (Yus 2017) and the presence of conflict in WhatsApp interactions (García-Gómez 2018, Fernández-Amaya 2019. Like other kinds of mediated communication, WhatsApp digital interactions contain elements from both spoken and written varieties of the language (Crystal 2006, Baron 2008, Angouri and Tseliga 2010, Yus 2011, Jones and Hafner 2012, Pérez-Sabater 2012, Calero Vaquera 2014, Petitjean and Morel 2017.…”

Section: Digital Discourse: Whatsappmentioning

confidence: 99%

Disagreement and (im)politeness in a Spanish family members’ WhatsApp group

Amaya

Люсия

2019

Russian Journal of Linguistics

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The present paper explores disagreement and impoliteness in a WhatsApp interaction within a Spanish family that took place during the 2018 International Women’s Day. The conversation is linguistically examined using categories of disagreement strategies proposed by previous authors (Pomerantz 1984, Brown and Levinson 1987, Rees-Miller 2000, Locher 2004, Kreutel 2007, Malamed 2010, Shum and Lee 2013). Furthermore, multimodal analysis (Dresner and Herring 2010, 2013, Jewitt 2013, Bourlai and Herring 2014; Herring 2015) is used to consider not only participants’ linguistic strategies for expressing disagreement, but also the function of multimedia elements and emojis (Dresner and Herring 2010, 2013, Yus 2014, 2017, Sampietro 2016a, 2016b, Aull 2019). The analysis is followed by an interview to better understand the participants’ communicative intentions towards disagreements in relation to (im)politeness. A total of 427 instances of disagreement are identified, with the most common strategies being giving opposite opinions and emotional or personal reasons. This is to be expected since the group is divided from the very beginning into detractors and supporters of feminism, and they are also defending their opposite viewpoints by giving examples from their own life experience. Based on the participants’ opinions, the most significant result is the fact that, although disagreement may lead to face-threat, and thus impoliteness in other contexts (Langlotz and Locher 2012, Sifianou 2012, Shum and Lee 2013), in this WhatsApp interaction, the Spanish family members did not consider it to be impolite, and it is even evaluated in positive terms by some of the participants (Angouri and Locher 2012).

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Section: Digital Discourse: Whatsappmentioning

confidence: 99%

Disagreement and (im)politeness in a Spanish family members’ WhatsApp group

Amaya

Люсия

2019

Russian Journal of Linguistics

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“…They investigated the usage of personal pronouns such as "you" and "your," modal adjuncts such as "can," "could," and "must," as well as the deployment of healthcare knowledge. The literature also demonstrates a growing interest in conflictual discourse among scholars, as evidenced by the studies conducted by Norrick (2013), Ardington (2013), Haugh and Sinkeviciute (2018), Kalbermatten (2018), Karafoti (2019), andGarcía-Gómez (2018). These studies have explored various aspects of conflict, including aggression, discourse patterns, accusations, linguistic strategies, and the impact of conflict on relationships.…”

Section: Literature Reviewmentioning

confidence: 99%

Insurance Discourse Analysis: Identifying Register Variables and Generic Stages in English Cross-border Complaint Calls

WAN

2024

HJLCB

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Interpersonal meaning-making resources are construed by customer service representatives (CSRs) and customers in call center telephone conversations. The purpose of the present study is to explore the contextual features—specifically, register variables and generic stages—that American customers and Filipino CSRs employ to create meaning potentials in cross-border insurance calls. The results of this study reveal that register variables, specific generic stages, and various lexicogrammatical choices play significant roles in call center negotiation. The theoretical framework used in this research is Systemic Functional Linguistics (SFL), which provides valuable insights into the study of text at the register level, including field, mode, and tenor, as well as semantically, in terms of metafunctions. A data set of over 2000 English conversations from an insurance call center in the Philippines was examined, and 20 longer complaint calls involving complex negotiations were carefully selected for transcription. These calls amounted to approximately four hours of talk, resulting in a total of 39,440 words, and the findings highlight the register variables and common generic stages observed in the analyzed calls. It is observed that customers frequently use the recount strategy in call center encounters. Recounts are typically used by the customer in the Objection stage and are associated with delayed refusal in generic stages, contributing to the formation of experiential meanings. It is hoped that the present study provides insights into call center discourse in the insurance industry by identifying the register and generic features of cross-border complaint calls.

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“…Depending on the research question at hand, researchers might need access to raw message data (García-Gómez, 2018 ; Sampietro, 2019 ; Sprugnoli et al, 2018 ). In other cases, however, anonymous user data are sufficient to answer the respective questions (Narayanan et al, 2019 ; Seufert et al, 2015 , 2016 ), and researchers should be as parsimonious as possible with using PII (see also Kohne et al, 2022 ) .…”

Section: The Whatsr Packagementioning

confidence: 99%

ChatDashboard: A Framework to collect, link, and process donated WhatsApp Chat Log Data

Kohne,

Montag

2023

Behav Res

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In this paper, we present ChatDashboard, a framework for collecting, linking, and processing donated WhatsApp chat log data. The framework consists of the WhatsR R package for parsing, anonymizing, and preprocessing donated WhatsApp chat logs, the ChatDashboard R Shiny web app for uploading, reviewing, and securely donating WhatsApp chat logs, and DashboardTester, an automated script for testing the correct setup of the framework by simulating participants. With ChatDashboard, researchers can set up their own data collections to gather transparently donated WhatsApp chat log data from consenting participants and link them to survey responses. It enables researchers to retrospectively collect highly granular data on interpersonal interactions and communication without building their own tools from scratch. We briefly discuss the advantages of donated WhatsApp chat log data for investigating social relationships and provide a detailed explanation of the ChatDashboard framework. Additionally, we provide a step-by-step guideline in the supplementary materials for researchers to set up their own data donation pipelines.

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Managing conflict on WhatsApp

Cited by 10 publications

References 29 publications

Disagreement and (im)politeness in a Spanish family members’ WhatsApp group

Disagreement and (im)politeness in a Spanish family members’ WhatsApp group

Insurance Discourse Analysis: Identifying Register Variables and Generic Stages in English Cross-border Complaint Calls

ChatDashboard: A Framework to collect, link, and process donated WhatsApp Chat Log Data

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