FACTORS OF SEMANTIC EMOTION OF COVID-19 NEWS AFTER INTRODUCTORY VACCINE ON TWITTER

This study is based on the fact that the readers get words emotion after reading the tweets of covid-19 news. Various emotions found on the tweets of twitter relate to the Covid-19 news. Some of them make the readers being fear or sad of this pandemic. This study deals with semantic emotion of covid-19 news in twitter account of CNN Breaking News. The objectives of the study is to investigate how the semantic emotions realized in Covid-19 news. The study was conducted by using descriptive qualitative. The data of this study were words from tweets which contain semantic emotion of Covid-19 news in twitter. The sources of data in this study were Covid-19 news in twitter, after vaccine Covid-19 distributed since beginning of January 2021. It was found that emotions were realized in covid-19 news, namely: basic emotion, emotional relations, caused emotions, causative, emotional goals, and complex emotions. Contrary with the expectation, happiness was the dominant emotion found in covid-19 news on twitter. Happiness is an emotion to show pleasant, while covid-19 in unpleasant situation. But in this research, it was found that happiness had a high frequency.Keywords: Semantic Emotion, Covid-19, Twitter, Vaccine

Face masks impair basic emotion recognition: Group effects and individual variability (Accepted for Publication in Social Psychology)

With the widespread adoption of masks, there is a need for understanding how facial obstruction affects emotion recognition. We asked 120 participants to identify emotions from faces with and without masks. We also examined if recognition performance was related to autistic traits and personality. Masks impacted recognition of expressions with diagnostic lower face features the most and those with diagnostic upper face features the least. Persons with higher autistic traits were worse at identifying unmasked expressions, while persons with lower extraversion and higher agreeableness were better at recognizing masked expressions. These results show that different features play different roles in emotion recognition and suggest that obscuring features affects social communication differently as a function of autistic traits and personality.

The Psychological Construction of Emotion – A Non-Essentialist Philosophy of Science

Advocates for the psychological construction of emotion view themselves as articulating a non-essentialist alternative to basic emotion theory's essentialist notion of affect programs. Psychological constructionists have also argued that holding essentialist assumptions about emotions engenders misconceptions about the psychological constructionist viewpoint. If so, it is important to understand what psychological constructionists mean by “essentialism” and “non-essentialism.” To advance the debate, I take a deeper dive into non-essentialism, comparing the non-essentialist views of the early empiricists with those of the psychological constructionists, focusing on the theories of James Russell and Lisa Barrett. Using Lakatos’ notion of scientific research programs, I also describe how Russell's and Barrett's views have evolved into different and potentially competing research programs under the psychological constructionist banner.

Are All “Basic Emotions” Emotions? A Problem for the (Basic) Emotions Construct

Despite decades of challenges to the idea that a small number of emotions enjoys the special status of “basic emotions,” the idea continues to have considerable influence in psychology and beyond. However, different theorists have proposed substantially different lists of basic emotions, which suggests that there exists no stable criterion of basicness. To some extent, the basic-emotions enterprise is bedeviled by an overreliance on English affective terms, but there also lurks a more serious problem—the lack of agreement as to what emotions are. To address this problem, three necessary conditions are proposed as a minimal requirement for a mental state to be an emotion. A detailed analysis of surprise, a widely accepted basic emotion, reveals that surprise violates even this minimal test, raising the possibility that it and perhaps other would-be basic emotions might not be emotions at all. An approach that combines ideas such as undifferentiated affect and cognitive appraisal is briefly proposed as a way of theorizing about emotions that is less dependent on the vagaries of language and incoherent notions of basic emotions. Finally, it is suggested that the perennial question of what an emotion is should be given more serious attention.

Preserving Right Pre-motor and Posterior Prefrontal Cortices Contribute to Maintaining Overall Basic Emotion

Basic emotions such as happiness, sadness, and anger are universal, regardless of the human species, and are governed by specific brain regions. A recent report revealed that mentalizing, which is the ability to estimate other individuals’ emotional states via facial expressions, can be preserved with the help of awake surgery. However, it is still questionable whether we can maintain the ability to understand others’ emotions by preserving the positive mapping sites of intraoperative assessment. Here, we demonstrated the cortical regions related to basic emotions via awake surgery for patients with frontal glioma and investigated the usefulness of functional mapping in preserving basic emotion. Of the 56 consecutive patients with right cerebral hemispheric glioma who underwent awake surgery at our hospital, intraoperative assessment of basic emotion could be successfully performed in 22 patients with frontal glioma and were included in our study. During surgery, positive responses were found in 18 points in 12 patients (54.5%). Of these, 15 points from 11 patients were found at the cortical level, mainly the premotor and posterior part of the prefrontal cortices. Then, we focused on cortical 15 positive mappings with 40 stimulations and investigated the types of emotions that showed errors by every stimulation. There was no specific rule for the region-emotional type, which was beyond our expectations. In the postoperative acute phase, the test score of basic emotion declined in nine patients, and of these, it decreased under the cut-off value (Z-score ≤ −1.65) in three patients. Although the total score declined significantly just after surgery (p = 0.022), it recovered within 3 months postoperatively. Our study revealed that through direct electrical stimulation (DES), the premotor and posterior parts of the prefrontal cortices are related to various kinds of basic emotion, but not a single one. When the region with a positive mapping site is preserved during operation, basic emotion function might be maintained although it declines transiently after surgery.

Why We Should Reject Transhumanists’ Entire Lens on the Mind and Brain

“Basic-emotion” and “dual-process” theorists, joined by transhumanists, view the mind as a set of compartments whose functionality is explained by dedicated areas or systems in the brain. The two theoretical approaches reflect core misconceptions and have been supplanted by “appraisal theory.” Beyond capturing well the entwining of reason and emotion in our mental operations, Klaus Scherer’s version of appraisal theory is compatible with mounting evidence of the brain’s complexity. Having developed a scientific line of argument against transhumanists’ lens on the mind and brain, the author turns to Aristotle’s rational essentialism. Wrongly invoked to support transhumanists’ extreme version, Aristotle’s rational essentialism incorporates a necessary role for nonrational faculties and intrapsychic harmony. While transhumanists’ lens on the mind and brain is at odds with contemporary findings, Aristotle’s view of the mind shares important commitments with Scherer’s appraisal theory and is broadly compatible with an emerging picture of the brain’s complexity.

Simultaneous prediction of valence / arousal and emotion categories and its application in an HRC scenario

We address the problem of facial expression analysis. The proposed approach predicts both basic emotion and valence/arousal values as a continuous measure for the emotional state. Experimental results including cross-database evaluation on the AffectNet, Aff-Wild, and AFEW dataset shows that our approach predicts emotion categories and valence/arousal values with high accuracies and that the simultaneous learning of discrete categories and continuous values improves the prediction of both. In addition, we use our approach to measure the emotional states of users in an Human-Robot-Collaboration scenario (HRC), show how these emotional states are affected by multiple difficulties that arise for the test subjects, and examine how different feedback mechanisms counteract negative emotions users experience while interacting with a robot system.

Translating Anger : A comparison of the Masoretic and Greek text of the Septuagint of the Book of Proverbs1

What particularities can be observed in the translation of notions of “anger” from the Hebrew to the Greek language, from a Semitic to a Hellenistic culture? This question is examined in an exemplary manner with reference to the oldest sapiential book of the Hebrew Bible, the Book of Proverbs, and its Greek translation in the Septuagint, since ProvLXX is a particularly free, receptor language oriented translation. Four tendencies can be detected in the LXX-translation of this basic emotion: the tendencies to theologization, to ethicization, to psychologization and, most clearly, the tendency to politicization.

The Design of CNN Architectures for Optimal Six Basic Emotion Classification Using Multiple Physiological Signals

This study aimed to design an optimal emotion recognition method using multiple physiological signal parameters acquired by bio-signal sensors for improving the accuracy of classifying individual emotional responses. Multiple physiological signals such as respiration (RSP) and heart rate variability (HRV) were acquired in an experiment from 53 participants when six basic emotion states were induced. Two RSP parameters were acquired from a chest-band respiration sensor, and five HRV parameters were acquired from a finger-clip blood volume pulse (BVP) sensor. A newly designed deep-learning model based on a convolutional neural network (CNN) was adopted for detecting the identification accuracy of individual emotions. Additionally, the signal combination of the acquired parameters was proposed to obtain high classification accuracy. Furthermore, a dominant factor influencing the accuracy was found by comparing the relativeness of the parameters, providing a basis for supporting the results of emotion classification. The users of this proposed model will soon be able to improve the emotion recognition model further based on CNN using multimodal physiological signals and their sensors.