Previous studies indicated that active interactions on social networking services (SNS) are positively linked to subjective well-being (SWB). However, how semantic SNS content affects the association between the degree of SNS interaction and SWB has not been investigated. We addressed this issue by conducting a mediation analysis using natural language processing. We first analyzed Twitter data and SWB scores from 217 participants and found that the degree of active interactions on Twitter (i.e., frequency of reply) was positively correlated with SWB. Next, our multivariate mediation analysis demonstrated that positive words served as SWB-promoting mechanisms for highly interactive people, whereas worrying words led to lower SWB for less interactive people, but negative words did not. This study revealed that natural language content explains why individuals who are highly interactive on SNS have higher SWB, whereas less interactive individuals show lower SWB.
Speech comprehension involves detecting words and interpreting their meaning according to the preceding semantic context. This process is thought to be underpinned by a predictive neural system that uses that context to anticipate upcoming words. Recent work demonstrated that such a predictive process can be probed from neural signals recorded during ecologically-valid speech listening tasks by using linear lagged models, such as the temporal response function.
Grupo de Bibliometría, Evaluación de Evidencia y Revisiones Sistemáticas (BEERS), Human Medicine Career, Universidad Científica del Sur, Lima, Peru, South America.
Background: Mycobacterium tuberculosis (M. tuberculosis) is an infectious disease that remains a significant global health problem. Despite efforts to reduce the disease, the disease remains prevalent in many parts of the world.
Background: People with premenstrual dysphoric disorder (PMDD) experience a range of symptoms that increase and decline as a result of the natural hormonal fluctuations of the menstrual cycle. For the diagnosis of PMDD, symptom severity needs to be recorded daily for at least two symptomatic cycles. In recent years, the rise in interest in Femtech (tools and technology developed to address women's health issues) has resulted in a large quantity of "period-tracking apps" being developed and downloaded.
School of Management, China Institute for Studies in Energy Policy, Collaborative Innovation Center for Energy Economics and Energy Policy, Xiamen University, Fujian, 361005, China. Electronic address:
Kitchen appliances constitute a significant portion of residential energy consumption. Promoting consumer purchases of high-energy-efficient kitchen appliances can effectively facilitate the transition to a low-carbon society. However, the role of energy saving in the current purchasing behavior of Chinese consumers regarding kitchen appliances remains unclear.
This study presents an innovative approach to cuffless blood pressure prediction by integrating speech and demographic features. With a focus on non-invasive monitoring, especially in remote regions, our model harnesses speech signals and demographic data to accurately estimate blood pressure. We found a strong correlation between our predictive model and early-stage high blood pressure, highlighting its potential for early detection.
