This study conducts a bibliometric analysis of news discourse analysis using CiteSpace to sketch its scientific landscape based on journal articles in English in the Scopus database from 1988 through 2020. The statistical analysis provides evidence for the interdisciplinarity of this area, and shows an upward trend in general over these years as well as an accelerating growth rate in the past decade. Findings also indicate that the problem-oriented CDA has gained the most popularity in this area since its emergence, (...) and the appraisal framework, multimodality analysis, and discursive news values have become three hotspots of news discourse analysis. In addition, the authors in the West have contributed most in this area, but those from Chinese Mainland, Malaysia, South Africa, and Indonesia have gradually been an emerging powerhouse, which has added diversity in topics and will enhance equality and promote dialogue between different communities, ethnics, and races across the globe. (shrink)

Although considerable efforts have been made to summarize the behavioral ethics literature, a quantitative visualization is necessary to generate an overall understanding of research on unethical behavior in organizations. Using CiteSpace, this study conducts a bibliometric review and visualizes the intellectual base of the unethical workplace behavior field. Based on a dataset of 8765 unethical-behavior-related publications collected from the Social Sciences Citation Index (SSCI) database from 1993 to 2023, we identify landmark studies, analyze key research themes, visualize the network of (...) major theories, and track the evolution of research on unethical behavior in organizations via co-citation and co-occurrence analysis. After tracking the developmental trajectory and outlining the current state of the art, we identify potential trends in research on unethical workplace behavior and suggest some important research directions. Our bibliometric review generates a clear visualization of unethical behavior in organizations, contributing to a comprehensive understanding of this body of literature. These findings also offer valuable insights for managers seeking to address unethical behavior in their organizations and highlight implications for policymakers aiming to promote ethical workplace environments. (shrink)

This paper examines the spatial spillover effects of public transportation infrastructure on regional economy in Northeast China, the “rust belt” region in China. The dataset consists of socioeconomic data from 47 cities in the area during the period of year 2005 through 2015. Accessibility is used as an explanatory variable to reflect the influence of infrastructure on economic development. In order to avoid the endogenous, queen contiguity matrix is used to define the spatial weight matrix. In the paper, the dynamic (...) panel data model is also used to explore the effects of high-speed railways in the whole study area and attempted to confirm the spatial differences among Heilongjiang Province, Jilin Province, and Liaoning Province. The results show that the high-speed railways increase the cities’ connection in terms of accessibility, and a significant positive spillover effect exists after the construction of high-speed railways, indicating the extensive economic benefits of HSR construction, despite of the overall economic difficulty experienced by this region. (shrink)

In order to solve the problem of the influence of feature word position in lyrics on music emotion classification, this paper designs a music classification and detection model in complex noise environment. Firstly, an intelligent detection algorithm for electronic music signals under complex noise scenes is proposed, which can solve the limitations existing in the current electronic music signal detection process. At the same time, denoising technology is introduced to eliminate the noise and extract the features from the signal. Secondly, (...) from the perspective of audio and lyrics of song sentiment analysis and the unique characteristics of lyrics text, a lyric sentiment analysis method based on text title and position weight is proposed. Finally, considering the influence of the weight of feature words in different positions on the classification of lyrics, the analytic hierarchy process is used to calculate the weight of feature words in different positions of text title and lyrics before, in, and after the text. The results show that in the complex noise environment, the accuracy of music classification and detection of the proposed model is more than 90%, which is far beyond the control range of the actual application of music processing. The effect of music classification and detection is better than that of the contrast model, which has a certain practical application value. (shrink)