Rational and Continuous Measurement of Emotional-Fingerprint, Emotional-Quotient and Categorical vs Proportional Recognition of Facial Emotions with M.A.R.I.E., Second Half

Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual observer and a population aged 20 to 70 years. Meanwhile, it can measure the range and intensity of expressed emotions through three Face- Tests, quantify the performance of a sample of 204 observers with hypernormal measures of cognition, “thymia” (defined elsewhere), and low levels of anxiety, and perform analysis of the six primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual- Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Decision-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”, 6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Fingerprint-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.

Narrative nursing for negative emotions in patients with acute pancreatitis:Based on model construction and application

BACKGROUND Acute pancreatitis(AP),as a common acute abdomen disease,has a high incidence rate worldwide and is often accompanied by severe complications.Negative emotions lead to increased secretion of stress hormones,elevated blood sugar levels,and enhanced insulin resistance,which in turn increases the risk of AP and significantly affects the patient's quality of life.Therefore,exploring the intervention effects of narrative nursing programs on the negative emotions of patients with AP is not only helpful in alleviating psychological stress and improving quality of life but also has significant implications for improving disease outcomes and prognosis.AIM To construct a narrative nursing model for negative emotions in patients with AP and verify its efficacy in application.METHODS Through Delphi expert consultation,a narrative nursing model for negative emotions in patients with AP was constructed.A non-randomized quasi-experimental study design was used in this study.A total of 92 patients with AP with negative emotions admitted to a tertiary hospital in Nantong City of Jiangsu Province,China from September 2022 to August 2023 were recruited by convenience sampling,among whom 46 patients admitted from September 2022 to February 2023 were included in the observation group,and 46 patients from March to August 2023 were selected as control group.The observation group received narrative nursing plan,while the control group was given with routine nursing.Self-rating anxiety scale(SAS),self-rating depression scale(SDS),positive and negative affect scale(PANAS),caring behavior scale,patient satisfaction scale and 36-item short form health survey questionnaire(SF-36)were used to evaluate their emotions,satisfaction and caring behaviors in the two groups on the day of discharge,1-and 3-month following discharge.RESULTS According to the inclusion and exclusion criteria,a total of 45 cases in the intervention group and 44 cases in the control group eventually recruited and completed in the study.On the day of discharge,the intervention group showed significantly lower scores of SAS,SDS and negative emotion(28.57±4.52 vs 17.4±4.44,P<0.001),whereas evidently higher outcomes in the positive emotion score,Caring behavior scale score and satisfaction score compared to the control group(P<0.05).Repeated measurement analysis of variance showed that significant between-group differences were found in time effect,inter-group effect and interaction effect of SAS and PANAS scores as well as in time effect and inter-group effect of SF-36 scores(P<0.05);the SF-36 scores of two groups at 3 months after discharge were higher than those at 1 month after discharge(P<0.05).CONCLUSION The application of narrative nursing protocols has demonstrated significant effectiveness in alleviating anxiety,ameliorating negative emotions,and enhancing satisfaction among patients with AP.

Effects of psychological intervention on negative emotions and psychological resilience in breast cancer patients after radical mastectomy

Breast cancer(BC)is the most common malignant tumor in women,and the treatment process not only results in physical pain but also significant psychological distress in patients.Psychological intervention(PI)has been recognized as an important approach in treating postoperative psychological disorders in BC patients.It has been proven that PI has a significant therapeutic effect on postoperative psychological disorders,improving patients'negative emotions,enhancing their psychological resilience,and effectively enhancing their quality of life and treatment compliance.

Personalized and continuous care intervention affects rehabilitation,living quality,and negative emotions of patients with breast cancer

BACKGROUND Breast cancer is among the most common malignancies worldwide.With progress in treatment methods and levels,the overall survival period has been prolonged,and the demand for quality care has increased.AIM To investigate the effect of individualized and continuous care intervention in patients with breast cancer.METHODS Two hundred patients with breast cancer who received systemic therapy at The First Affiliated Hospital of Hebei North University(January 2021 to July 2023)were retrospectively selected as research participants.Among them,134 received routine care intervention(routing group)and 66 received personalized and continuous care(intervention group).Self-rating anxiety scale(SAS),self-rating depression scale(SDS),and Functional Assessment of Cancer Therapy-Breast(FACT-B)scores,including limb shoulder joint activity,complication rate,and care satisfaction,were compared between both groups after care.RESULTS SAS and SDS scores were lower in the intervention group than in the routing group at one and three months after care.The total FACT-B scores and five dimensions in the intervention group were higher than those in the routing group at three months of care.The range of motion of shoulder anteflexion,posterior extension,abduction,internal rotation,and external rotation in the intervention group was higher than that in the routing group one month after care.The incidence of postoperative complications was 18.18%lower in the intervention group than in the routing group(34.33%;P<0.05).Satisfaction with care was 90.91% higher in the intervention group than in the routing group(78.36%;P<0.05).CONCLUSION Personalized and continuous care can alleviate negative emotions in patients with breast cancer,quicken rehabilitation of limb function,decrease the incidence of complications,and improve living quality and care satisfaction.

Impact of web-based positive psychological intervention on emotions,psychological capital,and quality of life in gastric cancer patients on chemotherapy

BACKGROUND Gastric cancer is a malignant digestive tract tumor that originates from the epithelium of the gastric mucosa and occurs in the gastric antrum,particularly in the lower curvature of the stomach.AIM To evaluate the impact of a positive web-based psychological intervention on emotions,psychological capital,and quality of survival in gastric cancer patients on chemotherapy.METHODS From January 2020 to October 2023,121 cases of gastric cancer patients on chemotherapy admitted to our hospital were collected and divided into a control group(n=60)and an observation group(n=61)according to the admission order.They were given either conventional nursing care alone and conventional nursing care combined with web-based positive psychological interventions,respectively.The two groups were compared in terms of negative emotions,psychological capital,degree of cancer-caused fatigue,and quality of survival.RESULTS After intervention,the number of patients in the observation group who had negative feelings toward chemotherapy treatment was significantly lower than that of the control group(P<0.05);the Positive Psychological Capital Questionnaire score was considerably higher than that of the control group(P<0.05);the degree of cancer-caused fatigue was significantly lower than that of the control group(P<0.05);and the Quality of Life Scale for Cancer Patients(QLQ-30)score was significantly higher than that of the control group(P<0.05).CONCLUSION Implementing a web-based positive psychological intervention for gastric cancer chemotherapy patients can effectively improve negative emotions,enhance psychological capital,and improve the quality of survival.

Analysis of the Effect of Outpatient Nursing Intervention on Hypoglycemic Treatment Effect and Psychological Emotions of Diabetic Patients

Objective:To explore the effect of outpatient nursing interventions on the hypoglycemic treatment and psychological emotions of diabetic patients.Methods:148 patients who came to our hospital for outpatient treatment from February 2022 to October 2023 were selected and divided into a control group and an observation group,with 74 cases per group,according to the random number table method.The control group received routine nursing intervention,and the observation group received outpatient nursing intervention based on the control group.The two groups were observed for their effects of hypoglycemic treatment and psychological and emotional improvement before and after outpatient nursing intervention.Results:The health behavior scores of the control group were lower than that of the observation group;the post-intervention fasting blood glucose,2h postprandial blood glucose,anxiety self-rating scale(SAS),and the depression self-rating scale(SDS)of the control group were significantly higher than that of the observation group,and the difference was statistically significant(P<0.01).Conclusion:Outpatient nursing intervention encouraged patients to comply with healthy behaviors and helped control blood sugar levels.Patients’anxiety,depression,and other adverse psychological states were also improved hence the outpatient nursing intervention is worthy of further promotion.

Exploration of the Integration of Positive Emotions and Flow Experience in STEAM Education

STEAM(science,technology,engineering,arts,and mathematics)education aims to cultivate innovative talents with multidimensional literacy through interdisciplinary integration and innovative practice.However,lack of student motivation has emerged as a key factor hindering its effectiveness.This study explores the integrated application of positive emotions and flow experience in STEAM education from the perspective of positive psychology.It systematically explains how these factors enhance learning motivation and promote knowledge internalization,proposing feasible pathways for instructional design,resource provision,environment creation,and team building.The study provides theoretical insights and practical guidance for transforming STEAM education in the new era.

The Differences Between Aesthetic Emotions and Life Emotions

This essay talks mainly about the differences between aesthetic emotions and everyday emotions.Firstly we need to be sure that the work of art has something to do with emotions both of artists and audience.The paper tries to prove this from the perspectives of expressionism,formalism and representationalism.Then the paper differentiates the two kinds of emotions from three aspects.Audience need to keep psychical distance from arts,contemplating art in a disinterested way and use imagination to arouse the aesthetic emotions.Although aesthetic emotions are different from everyday emotions,there are some relations between them.The meaning of appreciating works of art is mainly to realize much more delicate or significant emotions that we could not or do not want to acquire in our limited and realistic daily life,through which we broaden our lives and know more about ourselves and the world we live in.

Amygdala-Inspired Affective Computing: to Realize Personalized Intracranial Emotions with Accurately Observed External Emotions

Artificial intelligence technology has revolutionized every industry and trade in recent years. However, its own development is encountering bottlenecks that it is unable to implement empathy with human emotions. So affective computing is getting more attention from researchers. In this paper, we propose an amygdala-inspired affective computing framework to realize the recognition of all kinds of human personalized emotions. Similar to the amygdala, the instantaneous emergency emotion is first computed more quickly in a low-redundancy convolutional neural network compressed by pruning and weight sharing with hashing trick. Then, the real-time process emotion is identified more accurately by the memory level neural networks, which is good at handling time-related signals. Finally, the intracranial emotion is recognized in personalized hidden Markov models. We demonstrate on Facial Expression of Emotion Dataset and the recognition accuracy of external emotions(including the emergency emotion and the process emotion) reached 85.72%. And the experimental results proved that the personalized affective model can generate desired intracranial emotions as expected.

EZCalm:A User Emotion Regulation System by Immersive Music Based on Plutchik's Wheel of Emotions

Nowadays,many companies hire professional trainers to keep their employees emotionally positive.In addition,more and more people are visiting psychological doctors to adjust their emotion,in order to treat mental illness or gain sense of happiness.All kinds of people mentioned above want to adjust emotions in an effective way.Therefore,a simple and effective household pattern of emotion adjustment is particularly important for people to use in common days.For such a pattern,an emotion regulation pattern combined with Plutchiks' wheel of emotions is proposed for emotion adjustment.In order to enhance the effectiveness of emotion adjustment from both the vision channel and the hearing channel,we adjust the user's emotion by visualizing music on a Helmet mounted display(HMD)device.Findings demonstrate that the proposed system can calm down participants e'motions effectively.

Individual Classification of Emotions Using EEG

Many studies suggest that EEG signals provide enough information for the detection of human emotions with feature based classification methods. However, very few studies have reported a classification method that reliably works for individual participants (classification accuracy well over 90%). Further, a necessary condition for real life applications is a method that allows, irrespective of the immense individual difference among participants, to have minimal variance over the individual classification accuracy. We conducted offline computer aided emotion classification experiments using strict experimental controls. We analyzed EEG data collected from nine participants using validated film clips to induce four different emotional states (amused, disgusted, sad and neutral). The classification rate was evaluated using both unsupervised and supervised learning algorithms (in total seven “state of the art” algorithms were tested). The largest classification accuracy was computed by means of Support Vector Machine. Accuracy rate was on average 97.2%. The experimental protocol effectiveness was further supported by very small variance among individual participants’ classification accuracy (within interval: 96.7%, 98.3%). Classification accuracy evaluated on reduced number of electrodes suggested, consistently with psychological constructionist approaches, that we were able to classify emotions considering cortical activity from areas involved in emotion representation. The experimental protocol therefore appeared to be a key factor to improve the classification outcome by means of data quality improvements.

Processing Environmental Stimuli in Paranoid Schizophrenia:Recognizing Facial Emotions and Performing Executive Functions

Objective To study the contribution of executive function to abnormal recognition of facia expressions of emotion in schizophrenia patients. Methods Abnormal recognition of facial expressions of emotion was assayed according to Japanese and Caucasian facial expressions of emotion （JACFEE）, Wisconsin card sorting test {WCST）, positive and negative symptom scale, and Hamilton anxiety and depression scale, respectively, in 88 paranoid schizophrenia patients and 75 healthy volunteers. Results Patients scored higher on the Positive and Negative Symptom Scale and the Hamilton Anxiety and Depression Scales, displayed lower JACFEE recognition accuracies and poorer WCST performances. The JACFEE recognition accuracy of contempt and disgust was negatively correlated with the negative symptom scale score while the recognition accuracy of fear was positively with the positive symptom scale score and the recognition accuracy of surprise was negatively with the general psychopathology score in patients. Moreover, the WCST could predict the JACFEE recognition accuracy of contempt, disgust, and sadness in patients, and the perseverative errors negatively predicted the recognition accuracy of sadness in healthy volunteers. The JACFEE recognition accuracy of sadness could predict the WCST categories in paranoid schizophrenia patients. Conclusion Recognition accuracy of social-/moral emotions, such as contempt, disgust and sadness is related to the executive function in paranoid schizophrenia patients, especially when regarding sadness.

A new method for simulating human emotions

How to make machines express emotions would be instrumental in establishing acompletely new paradigm for man machine interaction. A new method for simulating and assessingartificial psychology has been developed for the research of the emotion robot. The human psychologyactivity is regarded as a Markov process. An emotion space and psychology model is constructedbased on Markov process. The conception of emotion entropy is presented to assess the artificialemotion complexity. The simulating results play up to human psychology activity. This model can alsobe applied to consumer-friendly human-computer interfaces, and interactive video etc.

Predicting Complex Word Emotions and Topics through a Hierarchical Bayesian Network

In this paper, we provide a Word Emotion Topic （WET） model to predict the complex word e- motion information from text, and discover the dis- trbution of emotions among different topics. A complex emotion is defined as the combination of one or more singular emotions from following 8 basic emotion categories： joy, love, expectation, sur- prise, anxiety, sorrow, anger and hate. We use a hi- erarchical Bayesian network to model the emotions and topics in the text. Both the complex emotions and topics are drawn from raw texts, without con- sidering any complicated language features. Our ex- periment shows promising results of word emotion prediction, which outperforms the traditional parsing methods such as the Hidden Markov Model and the Conditional Random Fields（CRFs） on raw text. We also explore the topic distribution by examining the emotion topic variation in an emotion topic diagram.

Mediating effect of interpersonal relations on negative emotions and dysmenorrhea in female adolescents

Background Good interpersonal relationships can improve the negative mood and, to a certain extent, may help relieve dysmenorrhea symptoms. However, there has been no study examining the role of interpersonal relationships in dysmenorrhea and how they may interact with negative emotions. Aims To investigate the connection between negative affect and dysmenorrhea, and the role of interpersonal relationships plays in this relationship. Methods The Cox Menstrual Symptom Scale (CMSS), short-form of Depression Anxiety Stress Scale, Interpersonal Comprehensive Diagnostic Scale and UCLA (University of California at Los Angeles) Loneliness Scale were applied to 855 adolescent nursing students to collect information on severity and frequency of dysmenorrheal symptoms, negative emotions (including depression, anxiety and stress), interpersonal problems and subjective experience of loneliness among them, and the relationship among these variables was examined. Results (1) Both the severity and frequency of dysmenorrhea were positively correlated with negative emotions, loneliness experience and interpersonal problems, while negatively correlated with age at menarche.(2) The negative emotions, romantic relationship and menarche age, but not loneliness and interpersonal problems, significantly contributed to both the severity and frequency of dysmenorrhea.(3) Mediation analysis revealed that the effects of loneliness and interpersonal problems on dysmenorrhea were totally mediated by negative emotions. Conclusions This investigation indicates that the relationship between interpersonal relationships and dysmenorrhea is mediated by negative emotions.

The Application of Specific Nursing in Perioperative Patients of Thoracic Surgery and Postoperative Recovery and Improvement of Patients’ Negative Emotions

Objective: To study the application of specific nursing in perioperative patients of thoracic surgery and postoperative recovery and improvement of patients’ negative emotions. Patients and Methods: A total of 88 patients in the thoracic surgery operating room of our hospital were selected and divided into group A (specific nursing, n = 44) and group B (routine nursing, n = 44). The anxiety and depression status of the two groups were assessed by the Self-rating Anxiety Scale (SAS) and the Self-rating Depression Scale (SDS). The relevant respiratory parameters after surgery, including total lung capacity, maximum respiration flow-rate, tidal volume, and vital capacity were observed. The extubation time, ICU hospitalization time, and VAS scores of postoperative pain were compared, with a score of 10 being full. The higher the score, the higher the pain. The in-cidence of postoperative wound infection, pulmonary infection, respiratory tract infection and the satisfaction with the operation were compared. Sf-36 scale was used to score the physical function, life function, psychological function and quality of life of the patients in the two groups. Results: The surgical effect of group A was significantly higher than that of group B (all p < 0.05). The total lung capacity, maximum respiration flow-rate, tidal volume and vital capacity of group A were significantly higher than those of group B (all p < 0.05). The extubation time and hospitalization time of group A were significantly higher than those of group B (all p < 0.05). VAS score of group A was significantly lower than that of group B (all p < 0.05). The infection rate of group A was significantly lower than that in group B (all p < 0.05). Conclusion: Specific nursing has higher application value than routine nursing, which is worth further promotion in clinic.

Research on the effect of health care integration on patients’ negative emotions and satisfaction with lung cancer nursing activities

BACKGROUND Lung cancer is a clinical disease with multiple malignant tumors.Currently,it is difficult for patients to benefit from routine clinical nursing due to the lack of a pertinent and systematic approach.AIM To investigate the effect of integrated nursing care on the negative emotions and satisfaction of lung cancer patients.METHODS From January 2018 to December 2019,92 patients with lung cancer were selected and divided into the study group and the control group;there were 46 patients in each group.The control group received routine nursing,and the study group received integrated medical care in addition to the care received by the control group.Negative emotions before and after the intervention,the self-management ability score after the intervention,family care burden after the intervention and nursing satisfaction after the intervention were measured in the two groups.RESULTS After the intervention,the self-rating anxiety scale and self-rating depression scale scores in the study group were lower than those in the control group(P<0.05);the scores for health knowledge,self-concept,self-responsibility and self-care skills in the study group were higher than those in the control group(P<0.05);the scores for individual burden and responsibility burden in the study group were lower than those before the intervention(P<0.05);and the nursing satisfaction in the study group(93.48%)was higher than that in the control group(78.26%,P<0.05).CONCLUSION An integrated nursing care approach for lung cancer patients can effectively relieve the patient’s negative feelings,improve their self-management ability,help to reduce the burden of family care and improve patient satisfaction with nursing activities.

Mood assessment via animated characters: An instrument to access and evaluate emotions in young children

Objective: Mood Assessment via Animated Characters (MAAC) is a novel, computer-based instrument to improve assessment and communication about feelings in young children with internalizing distress. Well-validated assessment instruments are lacking for those under age eight years. Method: Children ages 4 - 10 years with primary diagnosis of anxiety disorder (n = 74;33 boys, 41 girls) or no diagnosis (n = 83;40 boys, 43 girls) completed MAAC for 16 feelings. Those 8 - 10 years also completed standardized measures of internalizing symptoms. Results: MAAC’s emotions clustered into positive, negative, fearful, and calm/neutral factors. Clinical children rated themselves less positive (difference score -3.18;p = 0.002) and less calm/neutral (difference score -2.06;p = 0.04), and explored fewer emotions spontaneously (difference score = -2.37;p = 0.02) than nonanxious controls. Older children’s responses correlated with scores on several standardized measures. Conclusions: MAAC appears to be highly engaging, with clinical utility in the assessment of young anxious children. Applications in other populations are considered for future study.

BERT-CNN: A Deep Learning Model for Detecting Emotions from Text

Due to the widespread usage of social media in our recent daily lifestyles,sentiment analysis becomes an important field in pattern recognition and Natural Language Processing(NLP).In this field,users’feedback data on a specific issue are evaluated and analyzed.Detecting emotions within the text is therefore considered one of the important challenges of the current NLP research.Emotions have been widely studied in psychology and behavioral science as they are an integral part of the human nature.Emotions describe a state of mind of distinct behaviors,feelings,thoughts and experiences.The main objective of this paper is to propose a new model named BERT-CNN to detect emotions from text.This model is formed by a combination of the Bidirectional Encoder Representations from Transformer(BERT)and the Convolutional Neural networks(CNN)for textual classification.This model embraces the BERT to train the word semantic representation language model.According to the word context,the semantic vector is dynamically generated and then placed into the CNN to predict the output.Results of a comparative study proved that the BERT-CNN model overcomes the state-of-art baseline performance produced by different models in the literature using the semeval 2019 task3 dataset and ISEAR datasets.The BERTCNN model achieves an accuracy of 94.7%and an F1-score of 94%for semeval2019 task3 dataset and an accuracy of 75.8%and an F1-score of 76%for ISEAR dataset.

Spatial-temporal Analysis of Emotions in Society in News

Spatial-temporal analysis of emotions in society has become popular in many studies integrating geography with the humanities,and has shown its influence on social sensing and geo-computation for social sciences.Emotions in society are often volatile,irrational,and vulnerable to the social environment.A critical challenge is to analyze changes in long-term and large-scale emotions in society.In this paper,we propose exploiting this challenge by using spatial-temporal analysis.After extracting emotional,temporal,and spatial information,a spatial standardization approach based on adataset of administrative district changes addresses the problem of Chinese toponym changes.Finally,over 1.7 million news data from the People’s Daily from 1956 to 2014 were collected to explore the changes,spatial distribution,and driving factors of emotions in society using spatial-temporal analysis.The experimental results found that the spatial-temporal analysis of emotions in society in the news is consistent with the results of related sociological research.