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The relationship between political affiliations and diet-related discussions on social media has not been studied on a population level. This study used a cost- and -time effective framework to leverage, aggregate, and analyze data from social media. This paper enhances our understanding of diet-related discussions with respect to political orientations in U.S. states. This mixed methods study used computational methods to collect tweets containing "diet" or "#diet" shared in a year, identified tweets posted by U.S. Twitter users, disclosed topics of tweets, and compared democratic, republican, and swing states based on the weight of topics. A qualitative method was employed to code topics. We found 32 unique topics extracted from more than 800,000 tweets, including a wide range of themes, such as diet types and chronic conditions. Based on the comparative analysis of the topic weights, our results revealed a significant difference between democratic, republican, and swing states. The largest difference was detected between swing and democratic states, and the smallest difference was identified between swing and republican states. Our study provides initial insight on the association of potential political leanings with health (e.g., dietary behaviors). Our results show diet discussions differ depending on the political orientation of the state in which Twitter users reside. Understanding the correlation of dietary preferences based on political orientation can help develop targeted and effective health promotion, communication, and policymaking strategies. [ABSTRACT FROM AUTHOR]

Background: Social media platforms are integrated into the lives of students. Their use in education has been studied, but this research is scarce in nursing. The objective of this study was to develop and validate the questionnaire "Use and views of the social media for nursing education" through a pilot study, to describe the use and attitudes of nursing students to social media. Methods: Cross-sectional design to validate the modified scale "Students' Use and Views of the Social Media questionnaire." The sample consisted of 107 undergraduate nursing students. Results: The factor analysis extracted three main components to explain social media use for nursing education, with component 1 being the "Need to use media in my professional training," component 2—"To deepen my professional knowledge" and component 3 "Contrast information." High reliability was demonstrated with Chronbach's alpha value (0.84). Conclusion: The final tool was proven to have high validity and reliability values, so it is positioned as a viable tool to explore this reality. Students use social media for education in a high proportion and have positive attitudes regarding their education inclusion. [ABSTRACT FROM AUTHOR]

Unhealthy habits or lifestyles, such as obesity, smoking, and alcohol consumption, are involved in the development of non-communicable diseases. The aim of this study was to analyze different communities' interest in seeking obesity, smoking, and alcohol-related terms through relative search volumes (RSVs) of Google Trends (GT). Internet search query data on obesity, smoking, and alcohol-related terms were obtained from GT from the period between 2010 and 2020. Comparisons and correlations between different topics were calculated considering both global searches and English-, Spanish-, and Italian-speaking areas. Globally, the RSVs for obesity and alcohol-related terms were similar (mean RSVs: 76% and 77%), but they were lower for smoking (65%). High RSVs were found in winter for obesity and smoking-related terms. Worldwide, a negative correlation was found between alcohol and smoking terms (r = −0.72, p < 0.01). In Italy, the correlation was positive (r = 0.58). The correlation between obesity and alcohol was positive in all the cases considered. The interest of global citizens in obesity, smoking, and alcohol was high. The RSVs for obesity were globally higher and correlated with alcohol. Alcohol and smoking terms were related depending on the area considered. [ABSTRACT FROM AUTHOR]

The wide dissemination of false information and the frequent occurrence of extreme speeches on online social platforms have become increasingly prominent, which impact on the harmony and stability of society. In order to solve the problems in the dissemination and polarization of public opinion over online social platforms, it is necessary to conduct in-depth research on the formation mechanism of the dissemination and polarization of public opinion. This article appends individual communicating willingness and forgetting effects to the Susceptible-Exposed-Infected-Recovered (SEIR) model to describe individual state transitions; secondly, it introduces three heterogeneous factors describing the characteristics of individual differences in the Jager-Amblard (J-A) model, namely: Individual conformity, individual conservative degree, and inter-individual relationship strength in order to reflect the different roles of individual heterogeneity in the opinions interaction; thirdly, it integrates the improved SEIR model and J-A model to construct the SEIR-JA model to study the formation mechanism of public opinion dissemination and polarization. Transmission parameters and polarization parameters are simulated and analyzed. Finally, a public opinion event from the pricing of China's self-developed COVID-19 vaccine are used, and related Weibo comment data about this event are also collected so as to verify the rationality and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Social media is gradually building an online information environment regarding health. This environment is filled with many types of users' emotions regarding food safety, especially negative emotions that can easily cause panic or anger among the population. However, the mechanisms of how it affects users' emotions have not been fully studied. Therefore, from the perspective of communication and social psychology, this study uses the content analysis method to analyze factors affecting social media users' emotions regarding food safety issues. In total, 371 tweet samples of genetically modified food security in Sina Weibo (similar to Twitter) were encoded, measured, and analyzed. The major findings are as follows: (1) Tweet account type, tweet topic, and emotion object were all significantly related to emotion type. Tweet depth and objectivity were both positively affected by emotion type, and objectivity had a greater impact. (2) Account type, tweet topic, and emotion object were all significantly related to emotion intensity. When the depths were the same, emotion intensity became stronger with the decrease in objectivity. (3) Account type, tweet topic, emotion object, and emotion type were all significantly related to a user's emotion communication capacity. Tweet depth, objectivity, and user's emotion intensity were positively correlated with emotion communication capacity. Positive emotions had stronger communication capacities than negative ones, which is not consistent with previous studies. These findings help us to understand both theoretically and practically the changes and dissemination of user's emotions in a food safety and health information environment. [ABSTRACT FROM AUTHOR]

Background: In recent years Galaxy has become a popular workflow management system in bioinformatics, due to its ease of installation, use and extension. The availability of Semantic Web-oriented tools in Galaxy, however, is limited. This is also the case for Semantic Web Services such as those provided by the SADI project, i.e. services that consume and produce RDF. Here we present SADI-Galaxy, a tool generator that deploys selected SADI Services as typical Galaxy tools., Results: SADI-Galaxy is a Galaxy tool generator: through SADI-Galaxy, any SADI-compliant service becomes a Galaxy tool that can participate in other out-standing features of Galaxy such as data storage, history, workflow creation, and publication. Galaxy can also be used to execute and combine SADI services as it does with other Galaxy tools. Finally, we have semi-automated the packing and unpacking of data into RDF such that other Galaxy tools can easily be combined with SADI services, plugging the rich SADI Semantic Web Service environment into the popular Galaxy ecosystem., Conclusions: SADI-Galaxy bridges the gap between Galaxy, an easy to use but "static" workflow system with a wide user-base, and SADI, a sophisticated, semantic, discovery-based framework for Web Services, thus benefiting both user communities.