Misleading emotions: judgments of learning overestimate recognition of negative and positive emotional images

Effects of personality traits and mood induction on metamemory judgments and metacognitive beliefs

Although the effects of mood and personality traits on memory performance have previously been studied, their relationship to the metamemory and metacognitive processes is still unknown. In this study, we investigated the effects of mood induction (positive and negative) and personality traits (extroverted and neurotics) on metacognitive beliefs, memory confidence, the judgment of learning (JOL) and feeling of knowing (FOK) judgments during face-name recognition tasks. One hundred twenty-seven participants who met the criteria based on their extraverted and neurotic personality scores on the Big Five Personality Inventory were randomly assigned to positive and negative mood induction conditions. We found that neurotics showed lower JOL judgments and accuracy than extroverts. The interaction effect between mood and personality significantly affected JOL and FOK accuracy, indicating that while extraverts were more accurate during positive induction, neurotics were more accurate during negative induction. In addition, neurotics were underconfident in their memory and reported more negative metacognitive beliefs than extroverts. We concluded that memory and metamemory processes are distinguishable in their relationships with mood states and personality traits. Our data also showed that JOL and FOK are distinct processes that support domain-specific metacognitive judgments.

The disconnect between metamemory and memory for emotional images

Emotional information is reliably predicted to be remembered better than neutral information, and this has been found for words, images, and facial expressions. However, many studies find that these judgments of learning (JOLs) are not predictive of memory performance (e.g. [Hourihan, K. L. (2020). Misleading emotions: Judgments of learning overestimate recognition of negative and positive emotional images. Cognition and Emotion, 34(4), 771-782. https://doi.org/10.1080/02699931.2019.1682972]). The present study investigates and rules out numerous potential causes for this discrepancy between memory predictions and performance, including (1) reactivity to making JOLs, (2) idiosyncrasies of specific images used, (3), type of memory test, and (4) effects of fluency. Three additional experiments investigate whether JOLs can become more predictive of memory performance, either by experience with the task or by manipulating prior beliefs about memory for emotional images. In all experiments, we found the same effect: Emotional images are inaccurately predicted to be remembered better than neutral images. The results suggest that emotion is used as a heuristic for learning, resulting in low metamnemonic accuracy for emotional stimuli.

The impact factors of social media users' forwarding behavior of COVID-19 vaccine topic: Based on empirical analysis of Chinese Weibo users

Introduction

Social media, an essential source of public access to information regarding the COVID-19 vaccines, has a significant effect on the transmission of information regarding the COVID-19 vaccines and helps the public gain correct insights into the effectiveness and safety of the COVID-19 vaccines. The forwarding behavior of social media users on posts concerned with COVID-19 vaccine topics can rapidly disseminate vaccine information in a short period, which has a significant effect on transmission and helps the public access relevant information. However, the factors of social media users' forwarding posts are still uncertain thus far. In this paper, we investigated the factors of the forwarding COVID-19 vaccines Weibo posts on Chinese social media and verified the correlation between social network characteristics, Weibo textual sentiment characteristics, and post forwarding.

Methods

This paper used data mining, machine learning, sentiment analysis, social network analysis, and regression analysis. Using " (COVID-19 vaccine)" as the keyword, we used data mining to crawl 121,834 Weibo posts on Sina Weibo from 1 January 2021 to 31 May 2021. Weibo posts not closely correlated with the topic of the COVID-19 vaccines were filtered out using machine learning. In the end, 3,158 posts were used for data analysis. The proportions of positive sentiment and negative sentiment in the textual of Weibo posts were calculated through sentiment analysis. On that basis, the sentiment characteristics of Weibo posts were determined. The social network characteristics of information transmission on the COVID-19 vaccine topic were determined through social network analysis. The correlation between social network characteristics, sentiment characteristics of the text, and the forwarding volume of posts was verified through regression analysis.

Results

The results suggest that there was a significant positive correlation between the degree of posting users in the social network structure and the amount of forwarding. The relationship between the closeness centrality and the forwarding volume was significantly positive. The betweenness centrality was significantly positively correlated with the forwarding volume. There was no significant relationship between the number of posts containing more positive sentiments and the forwarding volume of posts. There was a significant positive correlation between the number of Weibo posts containing more negative sentiments and the forwarding volume.

Conclusion

According to the characteristics of users, COVID-19 vaccine posts from opinion leaders, "gatekeepers," and users with high-closeness centrality are more likely to be reposted. Users with these characteristics should be valued for their important role in disseminating information about COVID-19 vaccines. In addition, the sentiment contained in the Weibo post is an important factor influencing the public to forward vaccine posts. Special attention should be paid to the negative sentimental tendency contained in this post on Weibo to mitigate the negative impact of the information epidemic and improve the transmission effect of COVID-19 vaccine information.

Factors Affecting Social Media Users' Emotions Regarding Food Safety Issues: Content Analysis of a Debate among Chinese Weibo Users on Genetically Modified Food Security

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.