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Journal articles on the topic 'Linguistic suicide'
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O’Dea, B., M. Larsen, P. Batterham, A. Calear, and H. Christensen. "Talking suicide on Twitter: Linguistic style and language processes of suicide-related posts." European Psychiatry 33, S1 (March 2016): s274. http://dx.doi.org/10.1016/j.eurpsy.2016.01.727.
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IntroductionSuicide is a leading cause of death worldwide and is largely preventable. The social media site Twitter is used by individuals to express suicidal intentions. It is not yet feasible to contact each Twitter user to confirm risk. Instead, it may be possible to validate risk by linguistic analysis. Psychological linguistic theory suggests that language is a reliable way of measuring people's internal thoughts and emotions; however, the linguistics of suicidality on Twitter is yet to be fully explored.Objectives & aimThe aim of this study is to characterise the linguistic styles of suicide-related posts on Twitter for the purposes of predicting suicide risk.MethodsThe Linguistic Inquiry and Word Count (LIWC) program was used to compare the linguistic features of suicide-related tweets previously coded for suicide risk by humans with a set of matched controls. Logistic regression was then used for predictive modelling.ResultsThe suicide-related tweets had significantly different linguistic profiles to the control tweets. The “strongly concerning” suicide tweets were found to have fewer words than all other tweets and not surprisingly, references to ‘death’ were significantly higher in this group. A number of other results were found. The final model which distinguished “strongly concerning” suicide risk from the controls was found to have 97.7% sensitivity and 99.8% specificity.ConclusionsThis study confirms that the linguistic features of suicide-related Twitter posts are different from general Twitter posts and that these linguistic profiles may be used to predict suicide risk in Twitter users.Disclosure of interestThe authors have not supplied their declaration of competing interest.
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Suherman, Suherman. "INITIAL STUDY OF LINGUISTIC; VERBAL AND NONVERBAL SIGN OF ATTEMPTED SUICIDE AMONG ADOLESCENTS." Elevate The International Journal of Nursing Education, Practice and Research 1, no. 1 (July 24, 2018): 29–32. http://dx.doi.org/10.25077/elevate.1.1.29-32.2018.
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Increasing number of suicide cases, especially in adolescents, becomes problems that require serious treatment. Adolescence is a period of transition and hormonal development that can affect the emotions or mood. It is known that before attempting suicide, there are signs of language or linguistic such as verbal and nonverbal as an indication of the suicidal behavior action. This systematic review aims to identify these signs based on the results of several studies. There were 12 articles that have reviewed, the results showed there are three aspect that can be identified: used language from the suicider; perception of suicider toward the behaviour; and observerd behaviours. Most of the suicider express the feeling of Hopeless, Self-balming, feeling depressed and lonely, and also withdraw from society. It is expectedthat the result can be used as basic data toindentify signs and symptoms of suicide in adolescents.
Keywords: observed behaviors, suicide language; emotional expression
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Adam-Troian, Jais, and Thomas Arciszewski. "Absolutist Words From Search Volume Data Predict State-Level Suicide Rates in the United States." Clinical Psychological Science 8, no. 4 (May 28, 2020): 788–93. http://dx.doi.org/10.1177/2167702620916925.
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Suicide continues to be a major public health issue, especially in the United States. It is a well-established fact that depression and suicidal ideation are risk factors for suicide. Drawing on recent research that shows that absolutist words (e.g., “completely,” “totally”) constitute linguistic markers of suicidal ideation, we created an online index of absolutist thinking (ATI) using search query data (i.e., Google Trends time series). Mixed-model analyses of age-adjusted suicide rates in the United States from 2004 to 2017 revealed that ATI is linked with suicides, β = 0.22, 95% CI = [0.12, 0.31], p < .001, and predicts suicides within 1 year, β = 0.16, 95% CI = [0.05, 0.28], p = .006, independently of state characteristics and historical trends. It is the first time that a collective measure of absolutist thinking is used to predict real-world suicide outcomes. Therefore, the present study paves the way for novel research avenues in clinical psychological research.
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Van den Nest, Miriam, Benedikt Till, and Thomas Niederkrotenthaler. "Comparing Indicators of Suicidality Among Users in Different Types of Nonprofessional Suicide Message Boards." Crisis 40, no. 2 (March 2019): 125–33. http://dx.doi.org/10.1027/0227-5910/a000540.
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Abstract. Background: Little is known about linguistic differences between nonprofessional suicide message boards that differ in regard to their predominant attitude to suicide. Aims: To compare linguistic indicators potentially related to suicidality between anti-suicide, neutral, and pro-suicide message boards, and between the types of posters (primary posters, who initiate the thread, and the respective respondents). Method: In all, 1,200 threads from seven German-language nonprofessional suicide message boards were analyzed using the software Linguistic Inquiry and Word Count (LIWC) with regard to wording related to suicidal fantasies, aggression, and indicators of so-called suicidal constriction. Data were analyzed with ANOVA. Results: There were fewer words related to affective, social, cognitive, and communicative processes in pro-suicide message boards than in other boards. Death-related wording and aggression as well as tentative wording appeared more prevalent in pro-suicide boards. Limitations: Complex language structures cannot be analyzed with LIWC. Conclusion: The results suggest fewer emotion words and wording related to social circumstances among primary posters and respondents in pro-suicide boards as compared with other boards, and a higher use of death- and aggression-related words. These findings might signal a higher degree of suicidality or sheer differences in matters of interest or social desirability. The differences require attention in practice and research.
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Ermakova, L., and S. Ermakov. "Linguistic Approach to Suicide Detection." Proceedings of the Institute for System Programming of RAS 26, no. 4 (2014): 113–22. http://dx.doi.org/10.15514/ispras-2014-26(4)-9.
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Handelman, Lori D., and David Lester. "The Content of Suicide Notes from Attempters and Completers." Crisis 28, no. 2 (March 2007): 102–4. http://dx.doi.org/10.1027/0227-5910.28.2.102.
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Abstract. A study of the content of suicide notes from attempted suicides and completed suicides was conducted using the Linguistic Inquiry and Word Count (LIWC) text analysis program. Notes from completed suicides had fewer metaphysical references, more future tense verbs, more social references (to others) and more positive emotions than did the notes from attempted suicides. The implications of these results were discussed.
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Li, Tim M. H., Michael Chau, Paul S. F. Yip, and Paul W. C. Wong. "Temporal and Computerized Psycholinguistic Analysis of the Blog of a Chinese Adolescent Suicide." Crisis 35, no. 3 (May 1, 2014): 168–75. http://dx.doi.org/10.1027/0227-5910/a000248.
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Background: Text analysis of personal documents provides insight into the cognition of those who complete suicide. Many personal documents are digitalized and easily found on the Internet, which can be used to advance suicide research. Aims: (1) To examine the temporal relationships between posting intensity and language use to sketch the suicidal process of a young man on the basis of his blog entries. (2) To investigate whether digitalized personal documents and paper documents of suicide cases have similar or different language patterns. Method: Firstly, 193 blog entries of a 13-year-old boy posted during the year prior to his suicide were analyzed using the Chinese Linguistic Inquiry and Word Count (CLIWC) program. The temporal relationships between posting intensity and language use were illustrated by time series visualization. Secondly, the findings of this case study were compared with previous case studies from a systematic search of three Ovid databases. Results: Posting frequency and language use in the blog helped sketch the suicidal process of the young boy. In this case study, the ratio of positive to negative emotion words was associated with the posting trend. Progressive self-referencing appeared to be a primary predictive sign of suicide. However, the comparison did not show other clearly consistent patterns. Conclusion: Digitalized personal documents, when interpreted with other information of the individual, provide insight into the suicidal process of completed suicides. This study extends the findings of psycholinguistic analyses of suicides to the Chinese social context and online document form.
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O'Dea, Bridianne, Mark E. Larsen, Philip J. Batterham, Alison L. Calear, and Helen Christensen. "A Linguistic Analysis of Suicide-Related Twitter Posts." Crisis 38, no. 5 (September 2017): 319–29. http://dx.doi.org/10.1027/0227-5910/a000443.
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Abstract. Background: Suicide is a leading cause of death worldwide. Identifying those at risk and delivering timely interventions is challenging. Social media site Twitter is used to express suicidality. Automated linguistic analysis of suicide-related posts may help to differentiate those who require support or intervention from those who do not. Aims: This study aims to characterize the linguistic profiles of suicide-related Twitter posts. Method: Using a dataset of suicide-related Twitter posts previously coded for suicide risk by experts, Linguistic Inquiry and Word Count (LIWC) and regression analyses were conducted to determine differences in linguistic profiles. Results: When compared with matched non-suicide-related Twitter posts, strongly concerning suicide-related posts were characterized by a higher word count, increased use of first-person pronouns, and more references to death. When compared with safe-to-ignore suicide-related posts, strongly concerning suicide-related posts were characterized by increased use of first-person pronouns, greater anger, and increased focus on the present. Other differences were found. Limitations: The predictive validity of the identified features needs further testing before these results can be used for interventional purposes. Conclusion: This study demonstrates that strongly concerning suicide-related Twitter posts have unique linguistic profiles. The examination of Twitter data for the presence of such features may help to validate online risk assessments and determine those in need of further support or intervention.
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Kilincaslan, Ayse, Adem Gunes, Mehmet Eskin, and Alok Madan. "Linguistic adaptation and psychometric properties of the Columbia-Suicide Severity Rating Scale among a heterogeneous sample of adolescents in Turkey." International Journal of Psychiatry in Medicine 54, no. 2 (July 30, 2018): 115–32. http://dx.doi.org/10.1177/0091217418791454.
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Objective The Columbia-Suicide Severity Rating Scale is a semistructured, interview-based assessment tool, which is increasingly being used for clinical and research purposes across the globe, despite its limited psychometric evaluation outside of English-speaking populations. The aim of this study was to linguistically adapt the measure and investigate reliability, validity, and factor structure of the Turkish version of the Columbia-Suicide Severity Rating Scale in a heterogeneous sample of psychiatric and nonpsychiatric outpatient adolescents. Method The study included four clinical groups: two psychiatric, nonsuicidal outpatient groups (depression group (N = 50) and nondepression group (N = 50)), suicidal group (N = 43), and nonpsychiatric general practitioners’ group (N = 70). All participants were interviewed with the Columbia-Suicide Severity Rating Scale and suicidality module of the Mini International Neuropsychiatric Interview for children and adolescents. They also completed the Suicide Probability Scale, Child Depression Inventory, Beck Hopelessness Scale, and their parents filled in the Child Behavior Checklist. Results The scale was found to be a solidly reliable measure with good internal consistency and agreement among interviewers. It correlated in the expected direction with self- and parent-report measures of associated constructs (e.g., depression) as well as suicidality. Consistent with the developers’ intent of theoretical subscales, a three-factor solution (i.e., the severity of suicidal ideation, the intensity of suicidal ideation, and suicidal behavior) fit the data well, and it fit the data significantly better than the alternative models. Last, the Turkish Columbia-Suicide Severity Rating Scale successfully discriminated the adolescents with a recent history of suicide attempts from other clinical groups. Conclusion The Turkish version of the Columbia-Suicide Severity Rating Scale is a reliable and valid instrument to assess suicide risk among adolescents.
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Yeh, Aiden, and Pham Thi Minh Trang. "Avicii’s S.O.S.: A psychobiographical approach and corpus-based discourse analysis on suicidal ideation." Psychology of Language and Communication 26, no. 1 (January 1, 2022): 207–41. http://dx.doi.org/10.2478/plc-2022-0010.
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Abstract This study explored the linguistic patterns and discourse on suicide of the Swedish artist Avicii. Focusing on key events in his life, career, and compositions, a triangulation of data sources was employed grounded on psychobiographical research framework and corpus-based discourse analysis. Texts with reference to suicidal risk factors were then evaluated based on the interpersonal-psychological theory of suicide to establish linguistic representations of emotional distress and suicidal ideation. The findings suggest that lexical features associated with mental health struggles, that is, high volume of first-person deixis and death-themed linguistic references, were evident in his writing. There were substantial implications of his predisposition to mental stress and his call for help, his S.O.S. This study helps in further understanding the language and discourse of artists like Avicii on the immense dislocation of emotions and the complexities of navigating (inter)personal relationships.
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Li, Ang, Dongdong Jiao, and Tingshao Zhu. "Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo." Journal of Medical Internet Research 24, no. 4 (April 8, 2022): e36489. http://dx.doi.org/10.2196/36489.
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Background The new reality of cybersuicide raises challenges to ideologies about the traditional form of suicide that does not involve the internet (offline suicide), which may lead to changes in audience’s attitudes. However, knowledge on whether stigmatizing attitudes differ between cybersuicides and offline suicides remains limited. Objective This study aims to consider livestreamed suicide as a typical representative of cybersuicide and use social media data (Sina Weibo) to investigate the differences in stigmatizing attitudes across cybersuicides and offline suicides in terms of attitude types and linguistic characteristics. Methods A total of 4393 cybersuicide-related and 2843 offline suicide-related Weibo posts were collected and analyzed. First, human coders were recruited and trained to perform a content analysis on the collected posts to determine whether each of them reflected stigma. Second, a text analysis tool was used to automatically extract a number of psycholinguistic features from each post. Subsequently, based on the selected features, a series of classification models were constructed for different purposes: differentiating the general stigma of cybersuicide from that of offline suicide and differentiating the negative stereotypes of cybersuicide from that of offline suicide. Results In terms of attitude types, cybersuicide was observed to carry more stigma than offline suicide (χ21=179.8; P<.001). Between cybersuicides and offline suicides, there were significant differences in the proportion of posts associated with five different negative stereotypes, including stupid and shallow (χ21=28.9; P<.001), false representation (χ21=144.4; P<.001), weak and pathetic (χ21=20.4; P<.001), glorified and normalized (χ21=177.6; P<.001), and immoral (χ21=11.8; P=.001). Similar results were also found for different genders and regions. In terms of linguistic characteristics, the F-measure values of the classification models ranged from 0.81 to 0.85. Conclusions The way people perceive cybersuicide differs from how they perceive offline suicide. The results of this study have implications for reducing the stigma against suicide.
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Joh, Gi-Hyun, and Yonghun Lee. "A Linguistic Analysis on Suicide Notes." Modern Studies in English Language & Literature 63, no. 2 (May 31, 2019): 133–52. http://dx.doi.org/10.17754/mesk.63.2.133.
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Preti, Antonio, Francesca De Biasi, and Paola Miotto. "Musical Creativity and Suicide." Psychological Reports 89, no. 3 (December 2001): 719–27. http://dx.doi.org/10.2466/pr0.2001.89.3.719.
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The different abilities involved in artistic creativity may be mirrored by differences among mental disorders prevalent in each artistic profession, taking poets, painters, and composers as examples. Using suicide rates as a proxy for the prevalence of mental disorders in groups of artists, we investigated the percentage of deaths by suicide in a sample of 4,564 eminent artists who died in the 19th and 20th centuries. Of the sample, 2,259 were primarily involved in activities of a linguistic nature, e.g., poets and writers; 834 were primarily visual artists, such as painters and sculptors; and 1,471 were musicians (composers and instrumentalists). There were 63 suicides in the sample (1.3% of total deaths). Musicians as a group had lower suicide rates than literary and visual artists. Beyond socioeconomic reasons, which might favour interpretations based on effects of health selection, the lower rate of suicides among musicians may reflect some protective effect arising from music.
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Lester, David. "The Final Hours: A Linguistic Analysis of the Final Words of a Suicide." Psychological Reports 106, no. 3 (June 2010): 791–97. http://dx.doi.org/10.2466/pr0.106.3.791-797.
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A journal, two suicide notes, and two tape recordings from a young man who took his own life were analyzed by applying a computer program to analyze texts. The analysis indicates a calming trend from the journal entries to the suicide notes to the tape recordings, with an additional increase in positive emotions expressed from the first recorded message to the second recording made just an hour or two before his death. The usefulness of this approach for understanding the psychodynamics of suicidal behavior is discussed.
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Lester, David. "Linguistic Analysis of a Blog from a Murder–Suicide." Psychological Reports 106, no. 2 (April 2010): 342. http://dx.doi.org/10.2466/pr0.106.2.342-342.
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Safuanov, F. S., and T. N. Sekerage. "Activities aimed at encouraging children to suicidal behavior: judicial-psychological examination." Psychology and Law 7, no. 2 (2017): 33–45. http://dx.doi.org/10.17759/psylaw.2017060203.
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Federal law of June 7, 2017 g. № 120-FZ "On amendments to the criminal code of the Russian Federation and article 151 of the Criminal procedure code of the Russian Federation in the part of establishing additional mechanisms to counter activities aimed at encouraging children to suicidal behavior" establishes criminal liability for inducement to commit suicide or assist in its Commission (article 110.1 of the criminal code), as well as for the organization of activities aimed at encouraging citizens to commit suicide (article 110.2 of the criminal code). Two additions to the criminal code include using a publicly performed work, the media or information and telecommunications networks (including network "Internet"). There are new legal consequences relevant to forensic psychological assessment related to suicide. The article analyzes the legal situation (pre-investigation check of materials and incitement to suicide) that define the subject of judicial-psychological or psychological and psychiatric examinations as the mental state of the subject in the period preceding the suicide (death). Legislative innovations require expertise in psychology and linguistics. One of the subjects of psychological-linguistic expertise is the focus of the information material (text, graphic, together verbal and non-verbal information) or the communicative activity of the subject to encourage the addressee to co-concluding suicide. Formulate possible questions for the ex-experts and psychologists.
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Fernández-Cabana, Mercedes, Julio Jiménez-Féliz, María Teresa Alves-Pérez, Raimundo Mateos, Ignacio Gómez-Reino Rodríguez, and Alejandro García-Caballero. "Linguistic analysis of suicide notes in Spain." European Journal of Psychiatry 29, no. 2 (June 2015): 145–55. http://dx.doi.org/10.4321/s0213-61632015000200006.
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Lao, Cecilia, Jo Lane, and Hanna Suominen. "Analyzing Suicide Risk From Linguistic Features in Social Media: Evaluation Study." JMIR Formative Research 6, no. 8 (August 30, 2022): e35563. http://dx.doi.org/10.2196/35563.
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Background Effective suicide risk assessments and interventions are vital for suicide prevention. Although assessing such risks is best done by health care professionals, people experiencing suicidal ideation may not seek help. Hence, machine learning (ML) and computational linguistics can provide analytical tools for understanding and analyzing risks. This, therefore, facilitates suicide intervention and prevention. Objective This study aims to explore, using statistical analyses and ML, whether computerized language analysis could be applied to assess and better understand a person’s suicide risk on social media. Methods We used the University of Maryland Suicidality Dataset comprising text posts written by users (N=866) of mental health–related forums on Reddit. Each user was classified with a suicide risk rating (no, low, moderate, or severe) by either medical experts or crowdsourced annotators, denoting their estimated likelihood of dying by suicide. In language analysis, the Linguistic Inquiry and Word Count lexicon assessed sentiment, thinking styles, and part of speech, whereas readability was explored using the TextStat library. The Mann-Whitney U test identified differences between at-risk (low, moderate, and severe risk) and no-risk users. Meanwhile, the Kruskal-Wallis test and Spearman correlation coefficient were used for granular analysis between risk levels and to identify redundancy, respectively. In the ML experiments, gradient boost, random forest, and support vector machine models were trained using 10-fold cross validation. The area under the receiver operator curve and F1-score were the primary measures. Finally, permutation importance uncovered the features that contributed the most to each model’s decision-making. Results Statistically significant differences (P<.05) were identified between the at-risk (671/866, 77.5%) and no-risk groups (195/866, 22.5%). This was true for both the crowd- and expert-annotated samples. Overall, at-risk users had higher median values for most variables (authenticity, first-person pronouns, and negation), with a notable exception of clout, which indicated that at-risk users were less likely to engage in social posturing. A high positive correlation (ρ>0.84) was present between the part of speech variables, which implied redundancy and demonstrated the utility of aggregate features. All ML models performed similarly in their area under the curve (0.66-0.68); however, the random forest and gradient boost models were noticeably better in their F1-score (0.65 and 0.62) than the support vector machine (0.52). The features that contributed the most to the ML models were authenticity, clout, and negative emotions. Conclusions In summary, our statistical analyses found linguistic features associated with suicide risk, such as social posturing (eg, authenticity and clout), first-person singular pronouns, and negation. This increased our understanding of the behavioral and thought patterns of social media users and provided insights into the mechanisms behind ML models. We also demonstrated the applicative potential of ML in assisting health care professionals to assess and manage individuals experiencing suicide risk.
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Zadorozhnyi, Nazar. "Criminological and criminal law aspects of the definition of suicide." ScienceRise: Juridical Science, no. 1(19) (March 31, 2022): 64–69. http://dx.doi.org/10.15587/2523-4153.2022.253666.
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The article analyses the basic approaches to the definition of suicide, used in Ukraine and throughout the world. The importance of modelling the definition of suicide in the context of scientific analysis of this phenomenon is emphasized. The linguistic nature of the terms "self-killing" and "suicide" is studied. Suicide definitions, used by international and reputable health organizations and institutions, are collected. The available scientific definitions of Ukrainian researchers, which were formulated in the past, are presented and analysed. The inexpediency of considering all suicides violent is justified. Arguments in favour of conciseness and clarity of the recommended definition of suicide are presented and attention is focused on the negative impact of overloaded definitions. A claim that self-killing as a result of mental disorders cannot be considered suicide is criticised. As a result, a distinctive vision of the problem of suicide has been formulated and substantiated, recommendations, considering its definition, have been provided. In addition, an analysis of the essence of the definition of suicide with the use of corpus delicti modelling is performed. The controversial position that suicide can be committed by inaction is discussed. Emphasis is placed on intent as an integral part of the definition of suicide. The so-called "demonstrative" suicides are analysed and the criminal law concepts of direct, indirect intent and negligence are designed in the context. It is stated, that committing suicide by negligence is impossible. The position that intentional self-killing of minors cannot be considered suicide and such actions should be qualified as an "accident" has been analysed. This position is criticized
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Lester, David. "Learning About Suicide from the Diary of Cesare Pavese." Crisis 30, no. 4 (July 2009): 222–24. http://dx.doi.org/10.1027/0227-5910.30.4.222.
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Background: The study of the diaries of suicides presents an opportunity for greater insight into the psychodynamics of suicide than does the study of suicide notes. Aims: The present study analyzed the last year of the published diary of the Italian writer, Cesare Pavese (1908–1950), to identify changes in the content over the last year of his life. Methods: The last year of the published diary was analyzed using the Linguistic Word Count program. Results: The proportion of words related to positive emotions and optimism increased over the last year of Pavese’s life, and the entries became less complex and more self-oriented. Conclusions: The results confirm the changes in mood documented in diaries and letters from suicides in previous research, and extend the research to published diaries of famous individuals and in transition.
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Lv, Meizhen, Ang Li, Tianli Liu, and Tingshao Zhu. "Creating a Chinese suicide dictionary for identifying suicide risk on social media." PeerJ 3 (December 15, 2015): e1455. http://dx.doi.org/10.7717/peerj.1455.
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Introduction.Suicide has become a serious worldwide epidemic. Early detection of individual suicide risk in population is important for reducing suicide rates. Traditional methods are ineffective in identifying suicide risk in time, suggesting a need for novel techniques. This paper proposes to detect suicide risk on social media using a Chinese suicide dictionary.Methods.To build the Chinese suicide dictionary, eight researchers were recruited to select initial words from 4,653 posts published on Sina Weibo (the largest social media service provider in China) and two Chinese sentiment dictionaries (HowNet and NTUSD). Then, another three researchers were recruited to filter out irrelevant words. Finally, remaining words were further expanded using a corpus-based method. After building the Chinese suicide dictionary, we tested its performance in identifying suicide risk on Weibo. First, we made a comparison of the performance in both detecting suicidal expression in Weibo posts and evaluating individual levels of suicide risk between the dictionary-based identifications and the expert ratings. Second, to differentiate between individuals with high and non-high scores on self-rating measure of suicide risk (Suicidal Possibility Scale, SPS), we built Support Vector Machines (SVM) models on the Chinese suicide dictionary and the Simplified Chinese Linguistic Inquiry and Word Count (SCLIWC) program, respectively. After that, we made a comparison of the classification performance between two types of SVM models.Results and Discussion.Dictionary-based identifications were significantly correlated with expert ratings in terms of both detecting suicidal expression (r= 0.507) and evaluating individual suicide risk (r= 0.455). For the differentiation between individuals with high and non-high scores on SPS, the Chinese suicide dictionary (t1:F1= 0.48; t2:F1= 0.56) produced a more accurate identification than SCLIWC (t1:F1= 0.41; t2:F1= 0.48) on different observation windows.Conclusions.This paper confirms that, using social media, it is possible to implement real-time monitoring individual suicide risk in population. Results of this study may be useful to improve Chinese suicide prevention programs and may be insightful for other countries.
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Na, Kyoung-Sae, Seon-Cheol Park, Sun-Jung Kwon, Minjae Kim, Hyoung-Jun Kim, Myungjae Baik, Jinmi Seol, et al. "Contents of the Standardized Suicide Prevention Program for Gatekeeper Intervention in Korea, Version 2.0." Psychiatry Investigation 17, no. 11 (November 25, 2020): 1149–57. http://dx.doi.org/10.30773/pi.2020.0271.
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Objective Suicide is a huge nationwide problem that incurs a lot of socio-economic costs. Suicide also inflicts severe distress on the people left behind. The government of the Republic of Korea has been making many policy efforts to reduce suicide rate. The gatekeeper program, ‘Suicide CARE’, is one of the meaningful modalities for preventing suicide.Methods Multidisciplinary research team collaborated to update the ‘Suicide CARE’ to version 2.0.Results In the ‘Introductory part’, the authors have the time to think about the necessity and significance of the program before conducting full-scale gatekeeper training. In the ‘Careful observation’ part, trainees learn how to understand and recognize the various linguistic, behavioral, and situational signals that a person shows before committing suicide. In the ‘Active listening’ part, trainees learn how to ask suicide with a value-neutral attitude as well listening empathetically. In the ‘Risk evaluation and Expert referral’ part, trainees learn intervening strategies to identify a person’s suicidal intention, plan, and past suicide attempts, and connect the person to appropriate institutes or services.Conclusion Subsequent studies should be conducted to verify the efficacy of the gatekeeper program.
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Ji, Shaoxiong, Celina Ping Yu, Sai-fu Fung, Shirui Pan, and Guodong Long. "Supervised Learning for Suicidal Ideation Detection in Online User Content." Complexity 2018 (September 9, 2018): 1–10. http://dx.doi.org/10.1155/2018/6157249.
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Early detection and treatment are regarded as the most effective ways to prevent suicidal ideation and potential suicide attempts—two critical risk factors resulting in successful suicides. Online communication channels are becoming a new way for people to express their suicidal tendencies. This paper presents an approach to understand suicidal ideation through online user-generated content with the goal of early detection via supervised learning. Analysing users’ language preferences and topic descriptions reveals rich knowledge that can be used as an early warning system for detecting suicidal tendencies. Suicidal individuals express strong negative feelings, anxiety, and hopelessness. Suicidal thoughts may involve family and friends. And topics they discuss cover both personal and social issues. To detect suicidal ideation, we extract several informative sets of features, including statistical, syntactic, linguistic, word embedding, and topic features, and we compare six classifiers, including four traditional supervised classifiers and two neural network models. An experimental study demonstrates the feasibility and practicability of the approach and provides benchmarks for the suicidal ideation detection on the active online platforms: Reddit SuicideWatch and Twitter.
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Li, Jiacheng, Shaowu Zhang, Yijia Zhang, Hongfei Lin, and Jian Wang. "Multifeature Fusion Attention Network for Suicide Risk Assessment Based on Social Media: Algorithm Development and Validation." JMIR Medical Informatics 9, no. 7 (July 9, 2021): e28227. http://dx.doi.org/10.2196/28227.
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Background Suicide has become the fifth leading cause of death worldwide. With development of the internet, social media has become an imperative source for studying psychological illnesses such as depression and suicide. Many methods have been proposed for suicide risk assessment. However, most of the existing methods cannot grasp the key information of the text. To solve this problem, we propose an efficient method to extract the core information from social media posts for suicide risk assessment. Objective We developed a multifeature fusion recurrent attention model for suicide risk assessment. Methods We used the bidirectional long short-term memory network to create the text representation with context information from social media posts. We further introduced a self-attention mechanism to extract the core information. We then fused linguistic features to improve our model. Results We evaluated our model on the dataset delivered by the Computational Linguistics and Clinical Psychology 2019 shared task. The experimental results showed that our model improves the risk-F1, urgent-F1, and existence-F1 by 3.3%, 0.9%, and 3.7%, respectively. Conclusions We found that bidirectional long short-term memory performs well for long text representation, and the attention mechanism can identify the key information in the text. The external features can complete the semantic information lost by the neural network during feature extraction and further improve the performance of the model. The experimental results showed that our model performs better than the state-of-the-art method. Our work has theoretical and practical value for suicidal risk assessment.
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Fernández-Cabana, M., A. García-Caballero, M. T. Alves-Pérez, M. J. García-García, and R. Mateos. "Suicidal Traits in Marilyn Monroe’s Fragments." Crisis 34, no. 2 (March 1, 2013): 124–30. http://dx.doi.org/10.1027/0227-5910/a000183.
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Background: Linguistic inquiry and word count (LIWC), a computerized method for text analysis, is often used to examine suicide writings in order to characterize the quantitative linguistic features of suicidal texts. Aims: To analyze texts compiled in Marilyn Monroe’s Fragments using LIWC, in order to explore the use of different linguistic categories in her narrative over the years. Method: Selected texts were grouped into four periods of similar word count and processed with LIWC. Spearman’s rank correlation was used to assess changes in language use across the documents over time. The Kruskal-Wallis test was applied to compare means between periods and for each of the 80 LIWC output scores. Results: Significant differences (p < .05) were found in 11 categories, the most relevant being a progressive decrease in the use of negative emotion words, a reduction in the use of long words in the third period, and an increase in the proportion of personal pronouns used as Monroe approached the time of her death. Conclusions: The consistently elevated usage of first-person personal singular pronouns and the consistently diminished usage of first-person personal plural pronouns are in line with previous studies linking this pattern with a low level of social integration, which has been related to suicide according to different theories.
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Fata, Ika Apriani, Yunisrina Qismullah Yusuf, Rahmat Kamal, and Ehsan Namaziandost. "The characteristics of linguistic features enfolded in suicide notes." Journal of Language and Linguistic Studies 17, no. 2 (June 23, 2021): 720–35. http://dx.doi.org/10.52462/jlls.50.
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Fernández-Cabana, Mercedes, Francisco Ceballos-Espinoza, Raimundo Mateos, María Teresa Alves-Pérez, and Alejandro Alberto García-Caballero. "Suicide notes: clinical and linguistic analysis from the perspective of the Interpersonal Theory of Suicide." European Journal of Psychiatry 29, no. 4 (December 2015): 293–308. http://dx.doi.org/10.4321/s0213-61632015000400006.
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Pająk, Katarzyna, and Jerzy Trzebiński. "Escaping the World: Linguistic Indicators of Suicide Attempts in Poets." Journal of Loss and Trauma 19, no. 5 (June 3, 2014): 389–402. http://dx.doi.org/10.1080/15325024.2013.794663.
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Mathur, Puneet, Ramit Sawhney, and Rajiv Ratn Shah. "Suicide Risk Assessment via Temporal Psycholinguistic Modeling (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 10 (April 3, 2020): 13873–74. http://dx.doi.org/10.1609/aaai.v34i10.7209.
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Social media platforms are increasingly being used for studying psycho-linguistic phenomenon to model expressions of suicidal intent in tweets. Most recent work in suicidal ideation detection doesn't leverage contextual psychological cues. In this work, we hypothesize that the contextual information embedded in the form of historical activities of users and homophily networks formed between like-minded individuals in Twitter can substantially improve existing techniques for automated identification of suicidal tweets. This premise is extensively tested to yield state of the art results as compared to linguistic only models, and the state-of-the-art model.
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Yu, Ning, Sandra Kübler, Joshua Herring, Yu-Yin Hsu, Ross Israel, and Charese Smiley. "LASSA: Emotion Detection via Information Fusion." Biomedical Informatics Insights 5s1 (January 2012): BII.S8949. http://dx.doi.org/10.4137/bii.s8949.
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Due to the complexity of emotions in suicide notes and the subtle nature of sentiments, this study proposes a fusion approach to tackle the challenge of sentiment classification in suicide notes: leveraging WordNet-based lexicons, manually created rules, character-based n-grams, and other linguistic features. Although our results are not satisfying, some valuable lessons are learned and promising future directions are identified.
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Siu, Wanda Luen Wun. "News discourse of teachers’ suicide." Journal of Asian Pacific Communication 18, no. 2 (July 31, 2008): 247–67. http://dx.doi.org/10.1075/japc.18.2.12siu.
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This research reported findings from discourse analysis and content analysis on media coverage about a specific educational crisis on teachers’ suicide in Hong Kong. Overall, findings revealed that there was a great difference in sources being used by newspapers of different political ideology. The official position did not guarantee smooth access to the mass media via sources. Press ideology interfered in this process and determined what kind and how frequent news sources were used. Specifically, it was shown how linguistic choices in news texts accomplished the goal of framing the conflict, demarcating those supporting the education reform from those opposing the reform.
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Guan, Li, Bibo Hao, Qijin Cheng, Paul SF Yip, and Tingshao Zhu. "Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model." JMIR Mental Health 2, no. 2 (May 12, 2015): e17. http://dx.doi.org/10.2196/mental.4227.
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Background Traditional offline assessment of suicide probability is time consuming and difficult in convincing at-risk individuals to participate. Identifying individuals with high suicide probability through online social media has an advantage in its efficiency and potential to reach out to hidden individuals, yet little research has been focused on this specific field. Objective The objective of this study was to apply two classification models, Simple Logistic Regression (SLR) and Random Forest (RF), to examine the feasibility and effectiveness of identifying high suicide possibility microblog users in China through profile and linguistic features extracted from Internet-based data. Methods There were nine hundred and nine Chinese microblog users that completed an Internet survey, and those scoring one SD above the mean of the total Suicide Probability Scale (SPS) score, as well as one SD above the mean in each of the four subscale scores in the participant sample were labeled as high-risk individuals, respectively. Profile and linguistic features were fed into two machine learning algorithms (SLR and RF) to train the model that aims to identify high-risk individuals in general suicide probability and in its four dimensions. Models were trained and then tested by 5-fold cross validation; in which both training set and test set were generated under the stratified random sampling rule from the whole sample. There were three classic performance metrics (Precision, Recall, F1 measure) and a specifically defined metric “Screening Efficiency” that were adopted to evaluate model effectiveness. Results Classification performance was generally matched between SLR and RF. Given the best performance of the classification models, we were able to retrieve over 70% of the labeled high-risk individuals in overall suicide probability as well as in the four dimensions. Screening Efficiency of most models varied from 1/4 to 1/2. Precision of the models was generally below 30%. Conclusions Individuals in China with high suicide probability are recognizable by profile and text-based information from microblogs. Although there is still much space to improve the performance of classification models in the future, this study may shed light on preliminary screening of risky individuals via machine learning algorithms, which can work side-by-side with expert scrutiny to increase efficiency in large-scale-surveillance of suicide probability from online social media.
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Galasiński, Dariusz. "Context and goals: Suicide notes from a linguistic point of view." Death Studies 41, no. 7 (February 8, 2017): 461–62. http://dx.doi.org/10.1080/07481187.2017.1292815.
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Kim, Kyungil, Sunhee Choi, Joohyung Lee, and Jonghan Sea. "Differences in linguistic and psychological characteristics between suicide notes and diaries." Journal of General Psychology 146, no. 4 (April 22, 2019): 391–416. http://dx.doi.org/10.1080/00221309.2019.1590304.
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Makarova, Y. V. "Home and Family in the Novels “The White Guard” by M.A. Bulgakov and “The Suicide” by M.A. Aldanov: A Look at the Revolution from the “Inside” and the “Outside”." Uchenye Zapiski Kazanskogo Universiteta. Seriya Gumanitarnye Nauki 162, no. 5 (2020): 62–71. http://dx.doi.org/10.26907/2541-7738.2020.5.62-71.
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The sociocultural content of the concept of family hearth under the conditions of the revolutionary events of 1917 described in the novels “The Suicide” (‘Samoubiistvo’) by M.A. Aldanov and “The White Guard” (‘Belaya gvardiya’) by M.A. Bulgakov was revealed. The relevance of the study is determined by the fact that the concepts of home and family are the basic components of the sociocultural consciousness of any society. The study was performed with the aim of identifying key motifs in the description of home, as well as similarities and differences in the linguistic representation of this concept when describing two periods in the history of Russia (during the pre-revolutionary and revolutionary times) from the position of the author as an eyewitness to the events and the author as an emigrant. The following conclusions were made: in the descriptions of home of the pre-revolutionary Russia in the novels “The White Guard” by M.A. Bulgakov and “The Suicide” by M.A. Aldanov, the motifs of the well-being, stability, and continuity of generations are emphasized. In the episodes depicting the revolutionary events, the linguistic representation of home and family changes considerably: the motifs of doom, regret about the lost, surrealism, and tenuous imaginings become evident. The results obtained are important for linguistic analysis of some passages of the text needed for the adequate perception of the novels “The White Guard” by M.A. Bulgakov and “The Suicide” by M.A. Aldanov.
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Sawhney, Ramit, Harshit Joshi, Saumya Gandhi, Di Jin, and Rajiv Ratn Shah. "Robust suicide risk assessment on social media via deep adversarial learning." Journal of the American Medical Informatics Association 28, no. 7 (March 29, 2021): 1497–506. http://dx.doi.org/10.1093/jamia/ocab031.
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Abstract Objective The prevalence of social media for sharing personal thoughts makes it a viable platform for the assessment of suicide risk. However, deep learning models are not able to capture the diverse nature of linguistic choices and temporal patterns that can be exhibited by a suicidal user on social media and end up overfitting on specific cues that are not generally applicable. We propose Adversarial Suicide assessment Hierarchical Attention (ASHA), a hierarchical attention model that employs adversarial learning for improving the generalization ability of the model. Material and Methods We assess the suicide risk of a social media user across 5 levels of increasing severity of risk. ASHA leverages a transformer-based architecture to learn the semantic nature of social media posts and a temporal attention-based long short-term memory architecture for the sequential modeling of a user’s historical posts. We dynamically generate adversarial examples by adding perturbations to actual examples that can simulate the stochasticity in historical posts, thereby making the model robust. Results Through extensive experiments, we establish the face-value of ASHA and show that it significantly outperforms existing baselines, with the F1 score of 64%. This is a 2% and a 4% increase over the ContextBERT and ContextCNN baselines, respectively. Finally, we discuss the practical applicability and ethical aspects of our work pertaining to ASHA, as a human-in-the-loop framework. Discussion and Conclusions Adversarial samples can be helpful in capturing the diverse nature of suicidal ideation. Through ASHA, we hope to form a component in a larger human-in-the-loop infrastructure for suicide risk assessment on social media.
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Cohen, Shuki J. "Mapping the Minds of Suicide Bombers using Linguistic Methods: The Corpus of Palestinian Suicide Bombers' Farewell Letters (CoPSBFL)." Studies in Conflict & Terrorism 39, no. 7-8 (April 6, 2016): 749–80. http://dx.doi.org/10.1080/1057610x.2016.1141005.
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Lester, David. "Bereavement after Suicide: A Study of Memorials on the Internet." OMEGA - Journal of Death and Dying 65, no. 3 (November 2012): 189–94. http://dx.doi.org/10.2190/om.65.3.b.
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This study compared the written memorials on websites posted by survivors of suicide with those written by people who had lost a significant other from natural causes, using a computer program, the Linguistic Inquiry and Word Count. Thirteen significant differences were identified and, in addition, 13 differences that approach significance. Memorials written by survivors of suicide had longer sentences and used longer words. They had more death-related words, fewer references to the self or to the deceased (“you”), and more words reflective of anger and sadness. The results suggest the deaths from suicide had a more profound impact on the survivors than the natural deaths and results in greater emotional distress.
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Egnoto, Michael J., and Darrin J. Griffin. "Analyzing Language in Suicide Notes and Legacy Tokens." Crisis 37, no. 2 (March 2016): 140–47. http://dx.doi.org/10.1027/0227-5910/a000363.
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Abstract. Background: Identifying precursors that will aid in the discovery of individuals who may harm themselves or others has long been a focus of scholarly research. Aim: This work set out to determine if it is possible to use the legacy tokens of active shooters and notes left from individuals who completed suicide to uncover signals that foreshadow their behavior. Method: A total of 25 suicide notes and 21 legacy tokens were compared with a sample of over 20,000 student writings for a preliminary computer-assisted text analysis to determine what differences can be coded with existing computer software to better identify students who may commit self-harm or harm to others. Results: The results support that text analysis techniques with the Linguistic Inquiry and Word Count (LIWC) tool are effective for identifying suicidal or homicidal writings as distinct from each other and from a variety of student writings in an automated fashion. Conclusion: Findings indicate support for automated identification of writings that were associated with harm to self, harm to others, and various other student writing products. This work begins to uncover the viability or larger scale, low cost methods of automatic detection for individuals suffering from harmful ideation.
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Leonard Westgate, Christine, Brian Shiner, Paul Thompson, and Bradley V. Watts. "Evaluation of Veterans’ Suicide Risk With the Use of Linguistic Detection Methods." Psychiatric Services 66, no. 10 (October 2015): 1051–56. http://dx.doi.org/10.1176/appi.ps.201400283.
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Lyu, Yuwen, Julian Chun-Chung Chow, Ji-Jen Hwang, Zhi Li, Cheng Ren, and Jungui Xie. "Psychological Well-Being of Left-Behind Children in China: Text Mining of the Social Media Website Zhihu." International Journal of Environmental Research and Public Health 19, no. 4 (February 14, 2022): 2127. http://dx.doi.org/10.3390/ijerph19042127.
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China’s migrant population has significantly contributed to its economic growth; however, the impact on the well-being of left-behind children (LBC) has become a serious public health problem. Text mining is an effective tool for identifying people’s mental state, and is therefore beneficial in exploring the psychological mindset of LBC. Traditional data collection methods, which use questionnaires and standardized scales, are limited by their sample sizes. In this study, we created a computational application to quantitively collect personal narrative texts posted by LBC on Zhihu, which is a Chinese question-and-answer online community website; 1475 personal narrative texts posted by LBC were gathered. We used four types of words, i.e., first-person singular pronouns, negative words, past tense verbs, and death-related words, all of which have been associated with depression and suicidal ideations in the Chinese Linguistic Inquiry Word Count (CLIWC) dictionary. We conducted vocabulary statistics on the personal narrative texts of LBC, and bilateral t-tests, with a control group, to analyze the psychological well-being of LBC. The results showed that the proportion of words related to depression and suicidal ideations in the texts of LBC was significantly higher than in the control group. The differences, with respect to the four word types (i.e., first-person singular pronouns, negative words, past tense verbs, and death-related words), were 5.37, 2.99, 2.65, and 2.00 times, respectively, suggesting that LBC are at a higher risk of depression and suicide than their counterparts. By sorting the texts of LBC, this research also found that child neglect is a main contributing factor to psychological difficulties of LBC. Furthermore, mental health problems and the risk of suicide in vulnerable groups, such as LBC, is a global public health issue, as well as an important research topic in the era of digital public health. Through a linguistic analysis, the results of this study confirmed that the experiences of left-behind children negatively impact their mental health. The present findings suggest that it is vital for the public and nonprofit sectors to establish online suicide prevention and intervention systems to improve the well-being of LBC through digital technology.
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Canal-Rivero, Manuel, Caroline Silva, Jordi E. Obiols-Llandrich, Cristina García-Bernal, Cándido García-Sanchez, Tatiana Bustos-Cardona, Thomas E. Joiner, Benedicto Crespo-Facorro, and Miguel Ruiz-Veguilla. "Toward Understanding of Suicidality in a Spanish Clinical Population: Validation of the European Spanish Version of the Interpersonal Needs Questionnaire." Psychopathology 55, no. 1 (December 28, 2021): 16–27. http://dx.doi.org/10.1159/000519792.
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Introduction: Suicidal ideation (SI) represents one of the most prominent predictors of suicidal behavior (SB). The Interpersonal Needs Questionnaire (INQ) was developed from the Interpersonal Theory of Suicide (ITS) to assess the 2 core drivers of SI proposed by the theory. Despite the relevance of suicide-related ideations and ITS, there is a lack of psychometric measures validated in clinical Spanish population that adequately evaluate SI components of ITS. Thus, the main aim of the study was to validate INQ-10 in a Spanish clinical sample including the genuine cultural and linguistic characteristics of European Spanish. Methods: 315 participants were included in the analyses; 149 of them consulted mental health services for the presence of suicide-related behaviors. A series of exploratory and confirmatory factor analyses were carried out to identify the factor solution. Bivariate and multivariate analyses were used to analyze psychometric properties. Finally, sensitivity and specificity properties were explored through receiver-operating characteristic analyses which also provided the cut-off values of the questionnaire. Results: An 8-item version demonstrated a good fit to the 2-factor solution. Likewise, this 8-item version showed good psychometric properties. Sensitivity and specificity indices of the version validated as well as the calculated cut-off points were excellent. Conclusions: The current results demonstrate the utility of an 8-item INQ European Spanish version as a valid measure of the current SI in Spanish clinical population. In addition, the validated form reflects the theoretical framework on which it was built.
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Baddeley, Jenna L., Gwyneth R. Daniel, and James W. Pennebaker. "How Henry Hellyer’s Use of Language Foretold His Suicide." Crisis 32, no. 5 (September 1, 2011): 288–92. http://dx.doi.org/10.1027/0227-5910/a000092.
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Background: Henry Hellyer was an accomplished surveyor and explorer in Australia in the early 1800s whose apparent suicide at the age of 42 has puzzled historians for generations. He left behind several written works, including letters, journals, and reports. Aims: The current study assessed changes in the ways Hellyer used words in his various written documents during the last 7 years of his life. Methods: Hellyer’s writings were analyzed using the Linguistic Inquiry and Word Count program. Results: Hellyer showed increases in first-person singular pronoun use, decreases in first-person plural pronoun use, and increases in negative emotion word use. As this is a single, uncontrolled case study, caution is recommended in generalizing from the current results. Conclusions: Results suggest Hellyer’s increasing self-focused attention, social isolation, and negative emotion. Findings are consistent with increasing depression and suicidal ideation. Implications for using computerized text analysis to decode people’s psychological states from their written records are discussed.
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Overvad, Anna Therese, and Brady Wagoner. "Grief after suicide: A study of taboo and metaphor." Culture & Psychology 26, no. 3 (July 2, 2019): 369–83. http://dx.doi.org/10.1177/1354067x19861047.
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This article analyzes the negotiation of taboo surrounding grief after the suicide of a loved one. It draws on ethnographic fieldwork with a support group and individual interviews with its members. While the topic of taboo was prominent at group meetings, the same group members tended to claim in the interviews that they had not experienced it. To explore the issue of taboo, beyond affirmation or denial of its existence, we analyzed how the bereaved navigated the topic of suicide in language using Werner’s psychological theory of metaphor, which argues that metaphors arise to circumvent explicit reference to tabooed subjects. Members of the grief group clearly developed different strategies of metaphorical and other linguistic rephrasing to deal with the topics of death and suicide. Additionally, their language use differed depending on the person’s attitude toward the suicide, whether he or she was alone or with other group members, as well as whether the general public was being framed as an out-group.
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Добросельский, Александр. "Psychological and Linguistic Analysis of Concept «Unynie» as a Clue to the Framework of Suicides." Theological Herald, no. 4(35) (December 25, 2019): 130–51. http://dx.doi.org/10.31802/2500-1450-2019-35-130-151.
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Автор статьи ставит целью найти механизм суицида через анализ слова и понятия «уныние». В качестве методов используются этимологический анализ, анализ слова «уныние» на стыке богословия, психологии и лингвистики. Указанные методы позволяют понять, что «уныние» происходит от славянского слова «ныть (нытьё)», которое использовалось для описания неблагополучия телесного. С помощью приставки «у» было создано новое слово, имеющее тот же смысл неблагополучного состояния, но для духа человека, что подтверждается несколькими древними текстами. Общий для этих слов праиндоевропейский корень «nu» подразумевает бездеятельное, беспечное и бесперспективное предстояние перед исполненным нужды и мучений настоящим и отчаяние в будущем. Данный вывод весьма важен для изучения механизма суицидального поведения, дабы найти методы его разрушения, который могли бы взять на вооружение педагоги и психологи. Последнюю тему мы предложим читателю в следующей статье. In the act of suicide there is an enforcement mechanism that matures in low spirits and is triggered by despair. The key issue is finding a method to destroy such a mechanism in order to help educators and psychologists. This article is an attempt to find the framework of suicide through an analysis of the word and concept of «уныние». The etymological study of the word «уныние» shows that it has an artificial origin and occurs for any functions only in the Slavonic Church and languages it influenced on. The word «уныние» is used to name a sinful situation. The study of the word «уныние» is at the intersection of theology, psychology and linguistics and makes it possible to understand that the word «уныние» came into existent simultaneously with the Church Slavonic. There was a word «ныть (нытьё)» in the Slavic languages. It is used to describe physical ill-being. The new word was created by adding prefix «у» to describe spiritual ill-being. Some ancient texts corroborate it. Common for these words etymological proto-indo-european root «nu» fills the word «уныние» with the meaning of inactive, careless and hopeless status before the miserable and bitter, present and desolation in the future. This conclusion is highly significant to follow in the next article, studying the framework of suicidal behavior.
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Putri, Agustina Haryani, and Tadkiroatun Musfiroh. "News Discourse Analysis of Sexual Violence Causing Women to Commit Suicide in Online Media." International Journal of Linguistics, Literature and Translation 5, no. 11 (November 7, 2022): 101–9. http://dx.doi.org/10.32996/ijllt.2022.5.11.12.
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The study discusses cases of sexual violence causing women to commit suicide in online media news discourse based on Sara Mills's perspective. This research uses a descriptive qualitative approach. The research data is in the form of linguistic units in news discourse on sexual violence in online media. The source of the research data is several online media that discuss the discourse of news of sexual violence to the point of causing victims to commit suicide. The collection of research data is started by reading news discourses related to research topics. Recorded data was found from reading the discourse on sexual violence news in online media. Next was constructing data, reducing data, and validating data. The results of the analysis of the four discourses on news of sexual violence that cause victims of suicide in online media show that the author and the authorities as subjects who tell, the perpetrator and the victim are shown as objects told in each of the news discourses. The reader's position on news discourse 1 and news discourse 2 is shown partiality to the victim. The reader's position on news discourse 3 and news discourse 4 is not clearly displayed, so the author can identify for himself the position in the news discourse. In addition, it was found that some linguistic units contain certain meanings that are needed in research.
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Ajulo, Sunday Babalola. "Myth and reality of law, language and international organization in Africa: the case of African Economic Community." Journal of African Law 41, no. 1 (1997): 27–42. http://dx.doi.org/10.1017/s0021855300009967.
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The contemporary African international community is afflicted by a linguistic dilemma. On the one hand, the African elites are constrained to accept the imperative of adopting the inherited colonial languages in order to gain easy access to the global international community currently dominated by the linguistic condominium of the erstwhile imperial powers. On the other hand, these African elites, propelled by nationalistic sentiments, express in legal instruments a sanguine hope of promoting their indigenous tongues to the rank of official/working languages, not only on the national, but also on the continental scale. This would appear necessary in order to avoid cultural or linguistic suicide. However, in concept and practice, the whole idea seems to have remained in the realm of myth.
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Cui, QingXiao. "Meme genres and the art of the YouTube apology parody." Working papers in Applied Linguistics and Linguistics at York 2 (November 1, 2022): 65–88. http://dx.doi.org/10.25071/2564-2855.15.
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YouTube apology videos have been identified by some as a genre, and as such they have unique and recognizable features available for recontextualization and parody. The three parodies analyzed are of two videos: Logan Paul’s “So Sorry,” a response to his suicide forest controversy, and Travis Scott's video response to the Astroworld Tragedy. YouTube videos, as an audio-visual medium, are extremely multimodal, with many opportunities for linguistic and visual creativity. From a multimodal discourse analytic perspective, this paper examines some of the linguistic and non-linguistic strategies used by three YouTube apology parodies to mock and criticize both the original apology and the public figure issuing the apology. It further demonstrates how the genre of the YouTube apology parody has been codified by internet users.
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Biernesser, Candice, Jamie Zelazny, David Brent, Todd Bear, Christina Mair, and Jeanette Trauth. "Automated Monitoring of Suicidal Adolescents’ Digital Media Use: Qualitative Study Exploring Acceptability Within Clinical Care." JMIR Mental Health 8, no. 9 (September 15, 2021): e26031. http://dx.doi.org/10.2196/26031.
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Background Monitoring linguistic cues from adolescents’ digital media use (DMU; ie, digital content transmitted on the web, such as through text messages or social media) that could denote suicidal risk offers a unique opportunity to protect adolescents vulnerable to suicide, the second leading cause of death among youth. Adolescents communicate through digital media in high volumes and frequently express emotionality. In fact, web-based disclosures of suicidality are more common than in-person disclosures. The use of automated methods of digital media monitoring triggered by a natural language processing algorithm offers the potential to detect suicidal risk from subtle linguistic units (eg, negatively valanced words, phrases, or emoticons known to be associated with suicidality) present within adolescents’ digital media content and to use this information to respond to alerts of suicidal risk. Critical to the implementation of such an approach is the consideration of its acceptability in the clinical care of adolescents at high risk of suicide. Objective Through data collection among recently suicidal adolescents, parents, and clinicians, this study examines the current context of digital media monitoring for suicidal adolescents seeking clinical care to inform the need for automated monitoring and the factors that influence the acceptance of automated monitoring of suicidal adolescents’ DMU within clinical care. Methods A total of 15 recently suicidal adolescents (aged 13-17 years), 12 parents, and 10 clinicians participated in focus groups, qualitative interviews, and a group discussion, respectively. Data were recorded, transcribed, and analyzed using thematic analysis. Results Participants described important challenges to the current strategies for monitoring the DMU of suicidal youth. They felt that automated monitoring would have advantages over current monitoring approaches, namely, by protecting web-based environments and aiding adolescent disclosure and support seeking about web-based suicidal risk communication, which may otherwise go unnoticed. However, they identified barriers that could impede implementation within clinical care, namely, adolescents’ and parents’ concerns about unintended consequences of automated monitoring, that is, the potential for loss of privacy or false alerts, and clinicians’ concerns about liability to respond to alerts of suicidal risk. On the basis of the needs and preferences of adolescents, parents, and clinicians, a model for automated digital media monitoring is presented that aims to optimize acceptability within clinical care for suicidal youth. Conclusions Automated digital media monitoring offers a promising means to augment detection and response to suicidal risk within the clinical care of suicidal youth when strategies that address the preferences of adolescents, parents, and clinicians are in place.
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Malgaroli, Matteo, Thomas Derrick Hull, Niels Bantilan, Bonnie Ray, and Naomi Simon. "Suicide Risk Automated Detection Using Computational Linguistic Markers From Patients’ Communication With Therapists." Biological Psychiatry 87, no. 9 (May 2020): S444. http://dx.doi.org/10.1016/j.biopsych.2020.02.1131.
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