Fan Yang

The integration of artificial intelligence (AI) into the intimate sphere of human relationships presents a profound challenge to traditional understanding of intimacy, necessitating a critical examination of this technology’s extension into a domain that has always been viewed as deeply human. Through in-depth semi-structured interviews (N = 23), this study examines how human–AI intimate relationships develop in Chinese society at the intersection of traditions and modernization. A three-pronged Context-Script-Cue (CSC) framework emerges, capturing how users navigate emotional investment alongside the artificial nature of AI. By empirically examining how users engage in human–AI intimate relationships, this study offers the new CSC framework for understanding the development of human–AI intimate relationships.

The COVID-19 outbreak at the end of December 2019 spread rapidly all around the world. The objective of this study is to investigate and understand the relationship between public health measures and the development of the pandemic through Google search behaviors in the United States. Our collected data includes Google search queries related to COVID-19 from 1 January to 4 April 2020. After using unit root tests (ADF test and PP test) to examine the stationary and a Hausman test to choose a random effect model, a panel data analysis is conducted to investigate the key query terms with the newly added cases. In addition, a full sample regression and two sub-sample regressions are proposed to explain: (1) The changes in COVID-19 cases number are partly related to search variables related to treatments and medical resources, such as ventilators, hospitals, and masks, which correlate positively with the number of new cases. In contrast, regarding public health measures, social distancing, lockdown, stay-at-home, and self-isolation measures were negatively associated with the number of new cases in the US. (2) In mild states, which ranked one to twenty by the average daily new cases from least to most in 50 states, the query terms about public health measures (quarantine, lockdown, and self-isolation) have a significant negative correlation with the number of new cases. However, only the query terms about lockdown and self-isolation are also negatively associated with the number of new cases in serious states (states ranking 31 to 50). Furthermore, public health measures taken by the government during the COVID-19 outbreak are closely related to the situation of controlling the pandemic.

Utilizing online surveys of 729 US and 469 Chinese respondents, this study examines the mediated relationships between age and misinformation via fear of missing out (FoMO) and digital literacy in two different cultures. Results suggest that senior citizens are uniquely vulnerable to misinformation as the victims, in that they are less likely to check on suspicious content and that they are also less motivated to share information online in general. In contrast, youngadults have a greater propensity to be the spreaders of misinformation if not made suspicious of the content due to their stronger motivations to share information online. FoMO and digital literacy significantly mediate the relationship between age and motivations to share information and the one between age and reactions to misinformation, respectively. Sociocultural differences vary the intensity of these mediated relationships. Theoretical and practical implications are discussed.

Reproductive health communication can greatly benefit college women by providing informational and emotional support for their reproductive sexual health. However, communication about birth control with friends and sexual partners can be difficult especially if there is stigma around the topic. Applying the Disclosure Decision-Making Model, this study employs a survey of 104 college women regarding their disclosure of birth control status to a peer (Model 1) and a sexual partner (Model 2) to understand the mechanisms of decision-making (i.e., stigma, relational quality, anticipated response, disclosure efficacy) on the depth of disclosing reproductive health information. Results suggest that for both models, relational quality and anticipated response were the predictors of disclosure depth. Although all the significant paths were equivalent in the two models, relational quality predicted anticipated response more strongly in partner model. Theoretical and practical implications of the findings are discussed.

From the epidemic center in Wuhan to the entirety of China, with the growing infected population, people are seeking and processing health-related information both online and from traditional media outlets such as newspapers. Online misinformation regarding COVID-19 has been influencing a wide range of readers demonstrating general citizens’ virus-related concerns, while press media have been actively participating in health communication in an attempt to build up a robust, harmonious, and healthy environment. Via a comparison between the news data with the misinformation data during the early stage of the COVID-19 pandemic, from 1 January 2020 to 20 February 2020, we conducted an LDA topic-modeling analysis and a sentiment analysis. This study sheds light on the nature of people’s methods of health communication with online and press media sources during the early period of the pandemic crisis and provides possible readable explanations for the driving force of misinformation and the emotional changes experienced by the public.