This study focuses on the strategies of responding to apologies from a cross-cultural perspective. It analyzes and compares apology response (AR) strategies adopted by three groups of English native speakers (ENS), Chinese native speakers (ENS) and Chinese EFL learners for potential cross-cultural differences. Results indicate that all three groups most favor the strategy of Indirect Acceptance to show politeness when responding to apologies. Given contextual factors such as social power, social distance and severity of offence, the three groups display different patterns of AR strategies. Chinese EFL learners' AR strategies are similar to those of Chinese native speakers, indicating the influence of native culture on their pragmatic competence.
Job burnout is a special type of work-related stress that is prevalent in our modern society, and constant burnout is extremely harmful for people's physical health and emotional wellbeing. Traditional studies for burnout mainly rely on surveys/questionnaires, which have revealed several interesting findings but are of high cost and very time consuming. With the prevalence of social networking applications, we aim to re-investigate the burnout phenomenon in a novel perspective. In this paper, we collected a dataset consisting of 1532 burnout Weibo users with their postings. Based on the previous literature, we propose a number of hypotheses about what might be the burst signal of the burnout from the perspective of language, time and interaction. Furthermore, extensive correlation analysis is conducted to investigate if these hypotheses are supported, which leads to a number of interesting findings. Finally, we develop machine learning models to predict the burst of burnout based on extracted features and achieve a relatively high accuracy, which reveals potential implications in early-stage intervention.
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