There are many conflicting theories about the relationship between media reports and public opinion, but few of them are supported by empirical work on large data sets. We use sentiment results on over 260,000 China-related articles in The New York Times to show that events in international relations affect media sentiment which, in turn, affects public opinion. We find that sudden shifts in US-China relations are accompanied by changes in how The New York Times covers China and that the news reporting on China leads public opinion on China by 1 year. Our work illustrates how The New York Times, a prestigious mass media institution, propagates international relation signals to shape American views of the Chinese state and the Chinese people.
Studies on creative industries have explored how producers' properties shape their decisions about pursuing artistic novelty in their products. But how do external shocks, such as new remuneration opportunities, affect artistic novelty? In this paper, I investigate how the launch of monetization programs on online music platforms shapes musical novelty. I examined an original dataset of 12,394 songs on a Chinese music platform that launched its monetization program in 2013. Using computational tools developed in Music Information Retrieval (MIR) to compare song similarity based on their acoustic properties, I employed a novel approach to measure and model the impact of the monetization program on the musical novelty of the songs. The results suggest that while many more songs were uploaded to the platform after the program launch, these new songs are generally less novel than those before. Moreover, the decrease is particularly significant among songs released by indie companies, Pop musicians, or veteran producers. These findings demonstrate that monetization programs will restrain artistic novelty, especially among producers who are more autonomously skillful, unspecialized, or experienced.
How do citizens react to authoritarian responsiveness? To investigate this question, we study how Chinese citizens reacted to a novel government initiative which enabled social media users to publicly post requests for COVID-related medical assistance. To understand the effect of this initiative on public perceptions of government effectiveness, we employ a two-part empirical strategy. First, we conduct a survey experiment in which we directly expose subjects to real help-seeking posts, in which we find that viewing posts did not improve subjects' ratings of government effectiveness, and in some cases worsened them. Second, we analyze over 10,000 real-world Weibo posts to understand the political orientation of the discourse around help-seekers. We find that negative and politically critical posts far outweighed positive and laudatory posts, complementing our survey experiment results. To contextualize our results, we develop a theoretic framework to understand the effects of different types of responsiveness on citizens' political attitudes. We suggest that citizens' negative reactions in this case were primarily influenced by public demands for help, which illuminated existing problems and failures of governance.
One thing that has frequently been overlooked in studies of how a local government responds to its citizens is the text itself. When a petitioner drafts a post, they can pick up words and choose how the demand or question is conveyed. Thus, how a post is composed may also influence local government responsiveness. In this study, we investigated whether a delayed response is due to the way the message is drafted or the actual content by separating content-related and content-agnostic text features. Based on posts retrieved from two websites, we found that the response pattern varies by location, time, and type of queried agency. Our results also indicated that lengthy and low positive sentiment posts generally result in longer waiting times. However, more research is needed to gauge the possibility of a false negative and the meaning of contents extracted from computational tools. In addition, our work scrutinized several methodological issues and sought practical solutions to analyzing big data.
This study examines how China was covered and framed in global media reporting during the early stage of the coronavirus pandemic. Relying on a global multilingual COVID-19 online news narratives dataset, we propose multidimensional indicators to assess cross-country and cross-period variations in media discourses on China throughout the year of 2020. We derive and assess two hypotheses to explore factors accounting for the variations. The ideology-conflict hypothesis argues that the ideology distance from China determines the media attention and framing toward China in terms of COVID-19 reporting, while the crisis-mitigation hypothesis emphasizes that the domestic pandemic situation is associated with media discourses on China. Empirical analysis based on data compiled from various sources finds no evidence for the ideology-conflict hypothesis and moderate support for the crisis-mitigation hypothesis. Changes in the coronavirus situation and policy reactions are associated with changes in media coverage of China and the use of politicized terms over time. We conclude by discussing the implications of using online media data to understand the COVID-19 infodemic and its contribution to the emerging field of computational sociology.
Individuals differ in their personal and environmental characteristics, and the same treatment or condition may affect individuals in different ways or magnitudes. Heterogeneity in effects thus has important implications for academic research and policymaking. However, it is difficult to uncover and estimate heterogenous effects using conventional parametric models without making assumptions based on limited information, and results can be difficult to interpret when involving a large number of moderators. To address these limitations, this paper introduces three supervised machine learning methods for estimating heterogeneous treatment effects with experimental and observational data: causal forest, Bayesian Additive Regression Trees (BART), and an ensemble approach called X-learner. These methods are first applied to simulated datasets and then implemented using empirical education survey data from China to estimate heterogeneous effects of father absence on student cognitive ability across a series of individual and family characteristics.
The Southeast Asian region is an important part of the “Belt and Road Initiative”. In the face of the complex and diverse political, economic, and cultural environment of the region, it is necessary to understand the local situation from all angles to further promote the implementation of the “Belt and Road Initiative” development strategy. The current study of the region in the context of the “Belt and Road Initiative” is based on language communication, and the study of the Southeast Asian region is inseparable from the study of the local languages. Focusing on the language needs in the construction of the “Belt and Road Initiative” and the current situation of Chinese language services in Southeast Asia, this paper attempts to discuss current problems of Chinese language services in Asia and puts forward relevant suggestions to better promote the construction of “Belt and Road Initiative” and the exchange between China and other countries in Southeast.
This article examines the root reasons for speech cyberbullying against women in China under the context of the awareness of female independent consciousness and the feminist movement. Analyzing typical cases of speech cyberbullying against women on Chinese social media, we used a combination of historical and critical thinking. In our exploration of the root reasons for speech cyberbullying against women, the male gaze and silenced female, Chinese traditional concepts like guanxi and mianzi, patriarchy, the comparison between individualism and collectivism, and masculinity and feminity are all factors to which we paid close attention. To mitigate the problem of cyberbullying against women, the government should formulate punishments for perpetrators and advocate for women with practical actions on social media.
The purpose of the current study is to investigate the proportion, structure, and semantic prosody of “bei” passives in contemporary Chinese. The study reveals that there are similarities and differences between “bei” passives in written and spoken Chinese as well as their genres. First, the proportion of “bei” passives shows a feature of the continuum in the genres of contemporary Chinese, as ratio of “bei” passives decreases gradually in the genres from typical written Chinese to typical spoken Chinese. Second, short passives are preferred in both spoken and written Chinese. Finally, “bei” passives have a negative prosody in contemporary written and spoken Chinese except the Learned genre.
Translation is an integral part of our culture, and occupies a pivotal place in the histories of literature; however, the translator—the initiator of translation activities—has long been downgraded. It is quite necessary to elevate the status of the translators who have done so much to enrich our culture. The “cultural turn” in the West after the 1980s offered translation studies new dimensions and approaches. Gradually, equivalence-based theories came under attack and began to give way to culture-oriented translation research, which nowadays takes into account the wider context of the target culture. The target-oriented approach, developed through the transformation, highlights the cultural identities, functions, and roles of translators in the translating process. An interdisciplinary approach, which is feasible and effective, needs to be taken into account in translation. This paper is a trial to make an investigation into the translator's status with reference to model of conversation, the core concept of hermeneutics.
In practical application, the expected utility theory also has the problem of logical contradiction of decision criteria, search for a complete set of pre-selected solutions, and many other difficult problems. As a result, the expected utility theory cannot explain the decision-maker's changeable risk preference behavior, which hinders its effective application. This paper proposes to use the expectation theory to make investment decision, which overcomes the disadvantages of the above expected utility theory, points out that the emergency investment plan has dual characteristics of the coexistence of expected return and loss, meets the conditions of the risk investment decision-making problem of the expectation theory, and puts it forward in the scheme combination decision-making of the emergency plan. According to the expectation theory, scheme selection can resolve the logical contradiction of the combination scheme, and the decision-making method is more practical.
Artificial intelligence technology brings new opportunities for the development of teaching management in ordinary colleges and universities. It also makes teaching management in ordinary colleges and universities more efficient, refined, and personalized. Many ordinary colleges and universities carry out the practice of in-depth integration of artificial intelligence with teaching management and strive to ensure school infrastructure to promote the construction of smart platforms and introduce excellent performance models that enhance the effectiveness of data analysis. To further improve the effectiveness of the reform, the following suggestions are put forward: adhere to the original intention of education and return to the essence of teaching and educating; improve teachers' information technology literacy and urge teachers to change their roles; overcome technical safety issues and strengthen technology application supervision.
Taking 599 college student leaders as the research object, the mediating effects of leading motivation and behavior between adult attachment and college students’ leading efficiency were explored through structural equation modeling. Results: (1) Attachment anxiety has a significant negative effect on leading efficiency, while affinity dependence has a significant positive predictive effect on leading efficiency. (2) Service motivation, task-oriented leading behavior, or relationship-oriented leading behavior has a significant chain-mediating effect between attachment anxiety and leading efficiency. (3) Service motivation, self-development motivation, task-oriented leading behavior, and relationship-oriented leading behavior has significant chain-mediating effects between affinity and leading efficiency, respectively.
