Comparing the Heaven's Gate "Exit Statements" to Traditional Suicide Notes.

This study investigates the presentation and distribution of emotion words in beginner-level Spanish L2 textbooks, focusing on the presence of positivity bias and the types of emotion words included. Previous research has indicated that positive words are learned earlier and used more frequently than negative words, leading to the hypothesis that L2 pedagogical materials might reflect this trend. Four widely-used beginner Spanish textbooks from major publishers were analyzed to determine the frequency and types of emotion words presented. The analysis revealed that emotion words constitute a small portion of the total vocabulary in these textbooks, with only 2.5% of the words being emotion-related. Both positive and negative emotion words were equally represented, with 32 types of each, and their occurrences were comparable, suggesting no significant positivity bias in the textbooks. This balanced distribution of emotional words is beneficial for L2 learners, providing them with a comprehensive range of emotional expressions necessary for effective communication. The study also examined the thematic focus and progression of emotion vocabulary across the textbooks. Common themes such as health and well-being, leisure and modern life, and family and relationships were identified as contexts where emotion words are frequently introduced. The textbooks generally introduced basic emotion words early in the course, with a gradual increase in complexity as students progressed. This pedagogical approach ensures that learners build a solid foundation of emotion vocabulary, which is expanded upon as they advance in their studies. A detailed semantic analysis of the emotion words revealed that positive emotion words exhibited more semantic uniformity, often related to the basic concept of happiness. In contrast, negative emotion words displayed a wider range of semantic traits, including complex emotions such as boredom, anxiety, jealousy, and hatred. This diversity in negative emotion vocabulary suggests that the textbooks effectively introduce various negative emotions appropriate for beginner-level learners. The findings of this study have several pedagogical implications. First, the balanced presentation of positive and negative emotion words in textbooks supports the development of comprehensive emotional expression skills in L2 learners. Educators are encouraged to create supportive learning environments where students can practice using emotion vocabulary in context, through activities such as role-playing, discussions, and writing exercises. Additionally, the study highlights the importance of cultural context in teaching emotion words, suggesting that instructors should incorporate cultural differences in emotional expression to enhance learners' understanding and avoid misunderstandings. Furthermore, the study suggests that traditional one-to-one translation methods in textbooks may not fully capture the nuances of emotion vocabulary. To address this, educators should provide authentic contexts and scenarios for students to practice emotion words, helping them grasp the cultural meanings and differences between L1 and L2. The use of language learning apps and authentic materials such as movies and videos can also enhance the learning experience by providing real-life examples of emotional expression. In conclusion, this study provides valuable insights into the presentation of emotion words in beginner Spanish L2 textbooks, highlighting the need for balanced and contextually rich pedagogical approaches to support the development of emotional vocabulary in L2 learners. Future research should expand the analysis to a larger number of textbooks to validate these findings and explore additional strategies for teaching emotion words effectively.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0731/a.php" alt="Hit counter" /></p>

Color has the ability to influence a variety of human behaviors, such as object recognition, the identification of facial expressions, and the ability to categorize stimuli as positive or negative. Researchers have started to examine the relationship between emotional words and colors, and the findings have revealed that brightness is often associated with positive emotional words and darkness with negative emotional words (e.g., Meier, Robinson, & Clore, Psychological Science, 15, 82-87, 2004). In addition, words such as anger and failure seem to be inherently associated with the color red (e.g., Kuhbandner & Pekrun). The purpose of the present study was to construct norms for positive and negative emotion and emotion-laden words and their color associations. Participants were asked to provide the first color that came to mind for a set of 160 emotional items. The results revealed that the color RED was most commonly associated with negative emotion and emotion-laden words, whereas YELLOW and WHITE were associated with positive emotion and emotion-laden words, respectively. The present work provides researchers with a large database to aid in stimulus construction and selection.

Text messaging is widely used by young people for communicating and seeking mental health support through chat-based helplines. However, written communication lacks nonverbal cues, and language usage is an important source of information about a person's mental health state and is known to be a marker for psychopathology. The aim of the study was to investigate language usage, and its gender differences and associations with the presence of psychiatric symptoms within a chat counseling service for adolescents and young adults. For this study, the anonymized chat content of a German messenger-based psychosocial chat counseling service for children and adolescents ("krisenchat") between May 2020 and July 2021 was analyzed. In total, 661,131 messages from 6962 users were evaluated using Linguistic Inquiry and Word Count, considering the following linguistic variables: first-person singular and plural pronouns, negations, positive and negative emotion words, insight words, and causation words. Descriptive analyses were performed, and gender differences of those variables were evaluated. Finally, a binary logistic regression analysis examined the predictive value of linguistic variables on the presence of psychiatric symptoms. Across all analyzed chats, first-person singular pronouns were used most frequently (965,542/8,328,309, 11.6%), followed by positive emotion words (408,087/8,328,309, 4.9%), insight words (341,460/8,328,309, 4.1%), negations (316,475/8,328,309, 3.8%), negative emotion words (266,505/8,328,309, 3.2%), causation words (241,520/8,328,309, 2.9%), and first-person plural pronouns (499,698/8,328,309, 0.6%). Female users and users identifying as diverse used significantly more first-person singular pronouns and insight words than male users (both P<.001). Negations were significantly more used by female users than male users or users identifying as diverse (P=.007). Similar findings were noted for negative emotion words (P=.01). The regression model of predicting psychiatric symptoms by linguistic variables was significant and indicated that increased use of first-person singular pronouns (odds ratio [OR] 1.05), negations (OR 1.11), and negative emotion words (OR 1.15) was positively associated with the presence of psychiatric symptoms, whereas increased use of first-person plural pronouns (OR 0.39) and causation words (OR 0.90) was negatively associated with the presence of psychiatric symptoms. Suicidality, self-harm, and depression showed the most significant correlations with linguistic variables. This study highlights the importance of examining linguistic features in chat counseling contexts. By integrating psycholinguistic findings into counseling practice, counselors may better understand users' psychological processes and provide more targeted support. For instance, certain linguistic features, such as high use of first-person singular pronouns, negations, or negative emotion words, may indicate the presence of psychiatric symptoms, particularly among female users and users identifying as diverse. Further research is needed to provide an in-depth look into language processes within chat counseling services.

Digital phenotyping and monitoring tools are the most promising approaches to automatically detect upcoming depressive episodes. Especially, linguistic style has been seen as a potential behavioral marker of depression, as cross-sectional studies showed, for example, less frequent use of positive emotion words, intensified use of negative emotion words, and more self-references in patients with depression compared to healthy controls. However, longitudinal studies are sparse and therefore it remains unclear whether within-person fluctuations in depression severity are associated with individuals' linguistic style. To capture affective states and concomitant speech samples longitudinally, we used an ambulatory assessment approach sampling multiple times a day via smartphones in patients diagnosed with depressive disorder undergoing sleep deprivation therapy. This intervention promises a rapid change of affective symptoms within a short period of time, assuring sufficient variability in depressive symptoms. We extracted word categories from the transcribed speech samples using the Linguistic Inquiry and Word Count. Our analyses revealed that more pleasant affective momentary states (lower reported depression severity, lower negative affective state, higher positive affective state, (positive) valence, energetic arousal and calmness) are mirrored in the use of less negative emotion words and more positive emotion words. We conclude that a patient's linguistic style, especially the use of positive and negative emotion words, is associated with self-reported affective states and thus is a promising feature for speech-based automated monitoring and prediction of upcoming episodes, ultimately leading to better patient care.

Cerebral hemispheric differences in memory of emotional and non-emotional words in normal individuals

This pilot randomized controlled trial evaluated the feasibility, acceptability, and preliminary efficacy of expressive writing to reduce HIV-related sexual risk taking and symptoms of drug dependence among emerging adult gay and bisexual men (EAGBM) through linguistic mechanisms involving use of words associated with cognitive processing (e.g., think, cause), positive emotion (e.g., love, nice), and negative emotion (e.g., hurt, shame). Between 2014 and 2015, EAGBM (n = 78; aged 18-29) completed a baseline survey and were randomized to complete three 15-min expressive writing or equivalent control-group writing sessions and follow-up assessments 2 months post-baseline. EAGBM in the expressive writing condition utilized significantly more positive emotion, negative emotion, and cognitive processing words. Path model results indicated the intervention condition resulted in significant reductions in symptoms of drug dependence and frequency of condomless anal sex (CAS) through paths mediated by positive emotion words, and significant increases in CAS through a path mediated by negative emotion words.

This chapter focuses on the era between the death of Bonnie Lu Nettles and the mass suicide that ended the Heaven's Gate's existence. It analyzes the shifts in the group's naturalistic approach engendered by the loss of Nettles, whose death resulted in a moment of cognitive dissonance for the group. The group had hitherto insisted that its members would enter the heavens in their current living bodies, something that failed to occur for Nettles. Applewhite and the other members of the group therefore shifted toward a more supernatural or nonmaterial interpretation of bodily salvation predicated on the transmigration of the souls, a clear break from Heaven's Gate's earlier position. Overall, however, the movement continued to attempt during this time to recast religious concepts in the languages of materialistic naturalism. Several sources from the 1980s and 1990s revealed the continuing emphasis on the incorporation of scientific language and the methodological foundations of science into the movement. The chapter also considers sources from this latter period of Heaven's Gate that began to assume a vocally anti-religious perspective. These sources indicate how the group attempted to situate itself as more scientific than religious, despite making claims about salvation, God, and the nature of human life that most observers would consider religious by nature. Finally, it considers the material produced in the final years of the group's history by the adherents of Heaven's Gate, especially the three longtime members of the group calling themselves Jnnody, Chkody, and Jwnody. The chapter ends with an analysis of how the group's view of science and the absorption of scientific approaches into religion led to the 1997 mass suicides that ended Heaven's Gate.

During behavioral weight management, individuals reflect on their progress and barriers through goal pursuit (goal setting and goal striving). Emotions during goal pursuit are largely unknown, and previous investigations of emotions in weight management have primarily relied on self-report. In this retrospective study, we used a well-validated computational text analysis approach to explore how emotion words changed over time during goal setting and striving conversations with a coach in a mobile weight loss program. Linear mixed models examined changes in emotion words each month from baseline to program end and compared emotion words between individuals who set an overall concrete goal for the program (concrete goal setters) and those who set an overall abstract goal (abstract goal setters). Contrary to findings using self-report, positive emotion words were stable and negative emotion words significantly increased over time. There was a marginal trend towards greater negative emotion word use being associated with greater weight loss. Concrete goal setters used more positive words than abstract goal setters, with no differences in negative emotion words and weight loss. Implications include the possibility that individuals may need increasing support over time for negative emotions expressed during goal setting and striving, and concrete goals could boost positive emotion. Future research should investigate these possibilities.

The pandemic increased the stress levels of frontline healthcare providers in every country across the globe, and continues to do so. Health care providers in the rural regions of the U.S. were more vulnerable to the impact of COVID-19 due to the lack of resources and the population they serve. A qualitative study of 25 rural healthcare providers in a western U.S. state was conducted during 2020. In this report, Linguistic Inquiry and Word Count (LIWC) was used to compare the use of emotion and reward words in 12 providers interviewed before the onset of COVID-19 on March 11, 2020, to 13 interviews conducted after COVID-19 onset. Results indicated that providers used fewer positive emotion words after COVID-19 onset compared to before COVID. Negative emotion words also decreased. Words related to the rewarding aspects of their work increased after COVID-19, but differed among the pre- and post-COVID groups. Positive emotion words was more strongly related to rewards in the post-COVID group. Providers reported concerns about access to care for those unable to be treated for the increased depression, anxiety and suicide ideation related to the pandemic. The rural health care system needs policies directed at improving patient access to care and greater funding.

Therapist-assisted Internet-delivered cognitive behavior therapy (ICBT) involves elements of expressive writing through secure messaging with a therapist. Expressive writing has been associated with psychological and physical health benefits in past research; furthermore, certain linguistic dimensions in expressive writing have been identified as particularly beneficial to health, such as less frequent use of negative emotion words and greater use of positive emotion words. No research, to date, has analyzed linguistic dimensions in client communication over the course of therapist-assisted ICBT for individuals with symptoms of generalized anxiety. This naturalistic study examined messages sent to therapists during the course of ICBT using linguistic analysis, and explored covariation of word use with symptom improvement. Data were obtained from patients with symptoms of generalized anxiety (N = 59) who completed 12 modules of therapist-assisted ICBT and rated symptoms of anxiety, depression, and panic at the beginning of each module. Linguistic analysis categorized text submitted to therapists into different word categories. Results found that patients' use of negative emotion, anxiety, causation, and insight words reduced over the course of treatment, while past tense words increased. Furthermore, negative emotion words significantly covaried with symptom ratings over the course of treatment. While causal statements cannot be made, findings improve our understanding of patient communication in ICBT and suggest that the further study of linguistic dimensions as psychological indicators and the potential utility of expressive writing strategies in therapist-assisted ICBT may be worthwhile.

NodeXL Pro is a software developed for network analysis and visualization. NodeXL Pro connects to twitter and extracts tweets about the topics that are set, and makes various analyzes with these tweets. In this study, during the US presidential election held on November 8, 2016, the tweets about the candidates were handled and sentiment analysis was performed on these twitters. When you look at tags, on November 8, 2016, the most popular tags on twitter were; hillaryclinton and trump. Instantaneous; hillaryclinton’s twits number were 24407, compared to trump labeled twets number were 4132. When tweets under both labels were examined, it was seen that the majority of the twitters did not have words with emotional expression. On the other hand, hillaryclinton labeled tweets; 1761 positive emotion words were found and 828 negative emotion words were detected. It is known that Trump had focused on social media throughout the campaign period. Although the instant twet number of the trump tag was less than the hillaryclinton tag, the number of words expressing positive emotion was 5411 and the number of words expressing negative emotion was 1659 in these twets. For Hillary Clinton, the ratio of the number positive emotion words to the number of negative emotion expression words was 2,12, about Trump while the rate of the number of positive emotion words to negative emotion words was 3.26 in tweets. In hillaryclinton-tagged tweets, with the most popular positive words; Proud, love, worked, win and wins, most popular negative words; Hate, collapse, corruption, lies and f..k. In trump-tagged, for the most popular positive; "wins, win, defeat, good, trust, amazing, supporter and work" words, for the most popular negatively; "badly, refuses, lost, f..k, hell, loses and dump" words were the most common words. When word pairs are examined; The hillaryclinton word was used in combination with the most potsword (612 times) and the word with beyonce (603 times). Again, in the twets with hillaryclinton tag positively emotional sentences the "proud" and "same" words had been used together (139 times), "worked" and "toward" words (130 times) . In twitler expressing negative emotion; The words "collapse" and hillaryclintons have been used together (29 times), "corruption" and "looks" (28 times), "lies" and "vote" words (19 times). Trump tagged twets; The trump word was mostly used; with the Donald word (563 times), vote word (198 times) and wins word (169 times). When you look at the tweets that were triggered by the Trump tag and express a positive feeling; Most of the words "trump" and "wins" (169 times), "trump" and "supporters" had been used together (123 times). When you review negative tweets that are trump labeled; The words "refuses" and "allow" (57 times), "hell" and "out" (43 times) were used together. Despite the fact that when trump and hillaryclinton-tagged twits were emotionally analyzed, the number of tweets about Trump was much less than the number of tweets about Clinton. It seems that, the number of positive emotion expression words in tweets about trump were too much in terms of the number of positive emotion words in tweets about Clinton. It is seen that the words that express positive and negative emotions about Trump and Clinton are generally very different from each other.

Linguistic Inquiry and Word Count (LIWC) software, which can analyze elements of language, has been used to measure emotional responses to film clips, yet the viability of LIWC to study emotional responses to music has not been investigated. The purpose of this study was to assess the feasibility of using LIWC software to measure emotional responses to music. Undergraduate education majors ( N = 56) listened to two 90-second musical excerpts, one happy and one sad. After each excerpt, participants wrote about induced and perceived emotional responses. A repeated-measures ANOVA used to analyze effects of excerpt, writing prompt, emotion and order revealed a significant main effect for emotion ( p = .01). Significant interactions were found between emotion and excerpt ( p &lt; .001) and between excerpt, prompt and emotion ( p = .005). Participants used significantly more positive emotion words than negative emotion words to describe the happy excerpt, and the reverse was true for the sad excerpt. Both writing prompts elicited the expected differences in emotional response; however, the perceived emotion prompt resulted in greater contrasts between positive and negative emotion words than the induced emotion prompt. Results indicate that it is feasible to use LIWC to measure emotional responses to music.

Emotional information is treated differently than any other type of information and has a powerful impact on many cognitive processes, including attention. The aim of this study was to investigate how valence and arousal impact how we process words in sentences, as well as examine two theories of emotion, categorical negativity theory and the arousal hypothesis. Categorical negativity theory suggests that the valence of a word is what truly influences how emotional information receives attention, while the arousal hypothesis posits that the arousal level of a word determines the amount of attention it receives. In the current work, we used the rapid serial visual presentation (RSVP) task to investigate interactions between valence and arousal. The valence and arousal levels of positive and negative emotion words were manipulated within the context of full-sentence reading. Analyses revealed that all negative words, regardless of arousal level, produced the standard repetition blindness effect; however, positive words appeared to benefit from repetition. This interaction of valence and arousal suggests that a new theory is needed to accommodate evidence that both valence and arousal play a role in the attentional capture of emotion words. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

ObjectiveTo explore the correlation between word frequency and 17 items of the Hamilton Depression Scale (HAMD-17) in assessing the severity of depression in clinical interviews.MethodsThis study included 70 patients with major depressive disorder (MDD) who were hospitalized in the Beijing Anding Hospital. Clinicians interviewed eligible patients, collected general information, disease symptoms, duration, and scored patients with HAMD-17. The words used by the patients during the interview were classified and extracted according to the HowNet sentiment dictionary, including positive evaluation words, positive emotional words, negative evaluation words, negative emotional words. Symptom severity was grouped according to the HAMD-17 score: mild depressive symptoms is 8–17 points, moderate depressive symptoms is 18–24 points and severe depressive symptoms is >24 points. Analysis of Variance (ANOVA) was used to analyze the four categories of words among the groups, and partial correlation analysis was used to analyze the correlation between the four categories of word frequencies based on HowNet sentiment dictionary and the HAMD-17 scale to evaluate the total score. Receiver operating characteristic (ROC) curves were used to determine meaningful cut-off values.ResultsThere was a significant difference in negative evaluation words between groups (p = 0.032). After controlling for gender, age and years of education, the HAMD-17 total score was correlated with negative evaluation words (p = 0.009, r = 0.319) and negative emotional words (p = 0.027, r = 0.272), as the severity of depressive symptoms increased, the number of negative evaluation and negative emotional words in clinical interviews increased. Negative evaluation words distinguished patients with mild and moderate-severe depression. The area under the curve is 0.693 (p = 0.006) when the cut-off value is 8.48, the Youden index was 0.41, the sensitivity was 55.2%, and the specificity was 85.4%.ConclusionIn the clinical interview with MDD patients, the number of word frequencies based on HowNet sentiment dictionary may be beneficial in evaluating the severity of depressive symptoms.

Differences in Ethical Decision making between experts and novices: A Comparative StudyEthics is a pivotal feature in developing professionalism in engineers. The production of moral behavioris intricate and demands at least four different psychological processes: moral sensitivity, moraljudgment, moral motivation and moral character and implementation. Moral motivation plays a criticalrole in predicting an individual’s ethical behavior but it is not easy to assess. According to literaturemany variables such as gender, age, work experience, personality, nationality and cultural backgroundplay a role in ethical decisions.Work experience plays a critical role in professional engineers and graduate students by exposing themto more life challenging situations than the undergraduate students (novices). The goal of this study is tocompare the differences in ethical decisions by measuring the individual differences and responses toethical case studies of three different groups: professional engineers, graduate students, andundergraduate students. Individual differences in moral motivation are important for understandinghow people deal with ethical dilemmas. This study was conducted at a large university in the UnitedStates in the Fall 2013 and Fall 2014 semesters. Our sample consists of 60 people of three differentgroups: 20 professional engineers, 20 graduate students, and 20 undergraduate students.To compare the differences in decision making, a structured questionnaire was administered to eachparticipant. The questionnaire consisted of some demographic questions followed by three personalitymeasure tests (Person and Thing Orientations, Pauhlus Spheres of control, and Big Five Personality Test)and five ethical cases adopted from Lockhead Martin Ethics Challenge Games. Guided by the literature,we hypothesized that undergraduate students who are novices are ethically challenged in decisionmaking when compared to professional engineers and graduate students. Our study is at the stage ofanalyzing the data. The findings and applications for engineering instruction will be shared in the draftpaper.