The Content of Suicide Notes from Attempters and Completers

Crisis ◽  
2007 ◽  
Vol 28 (2) ◽  
pp. 102-104 ◽  
Author(s):  
Lori D. Handelman ◽  
David Lester
Keyword(s):  
Text Analysis ◽  
Positive Emotions ◽  
Analysis Program ◽  
Word Count ◽  
Future Tense ◽  
Suicide Notes ◽  
Program Notes ◽  
Linguistic Inquiry

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.

A Text Analysis of the Poems of Sylvia Plath

2011 ◽  
Vol 109 (1) ◽  
pp. 73-76 ◽  
Author(s):  
David Lester ◽  
Stephanie McSwain
Keyword(s):  
Computer Program ◽  
Text Analysis ◽  
Positive Emotions ◽  
Sylvia Plath ◽  
Word Count ◽  
Linguistic Inquiry

Changes in the words used in the poems of Sylvia Plath were examined using the Linguistic Inquiry and Word Count, a computer program for analyzing the content of texts. Major changes in the content of her poems were observed over the course of Plath's career, as well as in the final year of her life. As the time of her suicide came closer, words expressing positive emotions became more frequent, while words concerned with causation and insight became less frequent.

scholarly journals Machine-translated texts as an alternative to translated dictionaries for LIWC

2021 ◽  
Author(s):  
Peter Boot
Keyword(s):  
Machine Translation ◽  
Text Analysis ◽  
Analysis Program ◽  
Word Count ◽  
Alternative Approach ◽  
Linguistic Inquiry ◽  
Better Than ◽  
Dictionary Translation

Linguistic Inquiry and Word Count (LIWC) is a text analysis program developed by James Pennebaker and colleagues. At the basis of LIWC is a dictionary that assigns words to categories. This dictionary is specific to English. Researchers who want to use LIWC on non-English texts have typically relied on translations of the dictionary into the language of the texts. Dictionary translation, however, is a labour-intensive procedure. In this paper, we investigate an alternative approach: to use Machine Translation (MT) to translate the texts that must be analysed into English, and then use the English dictionary to analyse the texts. We test several LIWC versions, languages and MT engines, and consistently find the machine-translated text approach performs better than the translated-dictionary approach. We argue that for languages for which effective MT technology is available, there is no need to create new LIWC dictionary translations.

Linguistic Markers in Women’s Discussions on Miscarriage and Abortion Illustrate Psychological Responses to Their Experiences

2020 ◽  
pp. 0261927X2096564
Author(s):  
Kate G. Blackburn ◽  
Weixi Wang ◽  
Rhea Pedler ◽  
Rachel Thompson ◽  
Diana Gonzales
Keyword(s):  
Emotion Regulation ◽  
Text Analysis ◽  
The Other ◽  
Psychological Responses ◽  
Word Count ◽  
Future Directions ◽  
Trauma Research ◽  
Linguistic Markers ◽  
Linguistic Inquiry Word Count ◽  
Linguistic Inquiry

This study analyzed thousands of women’s online conversations in relation to their miscarriage or abortion experiences, classified as unplanned and planned traumas, respectively. Linguistic Inquiry Word Count text analysis revealed that people experiencing a planned trauma use distancing language patterns in higher frequency and engage in emotion regulation more than those who experienced trauma unexpectedly. On the other hand, planned trauma conversations used more self-focused language and more social-based language. Implications and future directions for trauma research are discussed.

scholarly journals Creating and Testing Specialized Dictionaries for Text Analysis

2019 ◽  
Vol 6 (1) ◽  
pp. 65-75 ◽  
Author(s):  
Роман Тарабань ◽  
Джесіка Піттман ◽  
Талін Налбандян ◽  
Winson Fu Zun Yang ◽  
Вільям Марсі ◽  
...  
Keyword(s):  
Text Analysis ◽  
Latent Dirichlet Allocation ◽  
Naive Bayes ◽  
Qualitative Content Analysis ◽  
Naïve Bayes ◽  
Computer Application ◽  
Word Count ◽  
Constructive Feedback ◽  
Discourse Processes ◽  
Linguistic Inquiry

Practitioners in many domains–e.g., clinical psychologists, college instructors, researchers–collect written responses from clients. A well-developed method that has been applied to texts from sources like these is the computer application Linguistic Inquiry and Word Count (LIWC). LIWC uses the words in texts as cues to a person’s thought processes, emotional states, intentions, and motivations. In the present study, we adopt analytic principles from LIWC and develop and test an alternative method of text analysis using naïve Bayes methods. We further show how output from the naïve Bayes analysis can be used for mark up of student work in order to provide immediate, constructive feedback to students and instructors. References Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research 3, 993-1022. Boot, P., Zijlstra, H., & Geenen, R. (2017). The Dutch translation of the Linguistic Inquiry and Word Count (LIWC) 2007 dictionary. Dutch Journal of Applied Linguistics, 6(1), 65-76. Chung, C. K., & Pennebaker, J. W. (2008). Revealing dimensions of thinking in open-ended self-descriptions: An automated meaning extraction method for natural language. Journal of research in personality, 42(1), 96-132. Hsieh, H-F., & Shannon, S. E. (2005).Three approaches to qualitative content analysis. Qualitative health research, 15(9), 277-1288. Kintsch, W. (1998). Comprehension: A paradigm for cognition. New York: Cambridge University Press. Landauer, T. K., Foltz, P. W., & Laham, D. (1998). An introduction to latent semantic ana­lysis. Discourse processes, 25(2-3), 259-284. Lund, K., & Burgess, C. (1996). Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments, & Computers, 28(2), 203-208. Massó, G., Lambert, P., Penagos, C. R., & Saurí, R. (2013, December). Generating New LIWC Dictionaries by Triangulation. In Asia Information Retrieval Symposium (pp. 263-271). Springer, Berlin, Heidelberg. Newman, M., Groom, C.J., Handelman, L.D., & Pennebaker, J.W. (2008). Gender differences in language use: An analysis of 14,000 text samples. Discourse Processes, 45(3), 211-236. Pennebaker, J.W., Boyd, R.L., Jordan, K., & Blackburn, K. (2015). The development and psychometric properties of LIWC 2015. Austin, TX: University of Texas at Austin. Tausczik, Y. R., & Pennebaker, J. W. (2010). The psychological meaning of words: LIWC and computerized text analysis methods. Journal of language and social psychology, 29(1), 24-54. Van Wissen, L., & Boot, P. (2017, September). An Electronic Translation of the LIWC Dictionary into Dutch. In: Electronic lexicography in the 21st century: Proceedings of eLex 2017 Conference. (pp. 703-715). Lexical Computing.

Using LIWC to Analyze Participants’ Psychological Processing in Accounting JDM Research

2021 ◽  
Author(s):  
Sanaz Aghazadeh ◽  
Kris Hoang ◽  
Bradley Pomeroy
Keyword(s):  
Text Analysis ◽  
Affective States ◽  
Word Count ◽  
Psycholinguistic Research ◽  
Psychological Constructs ◽  
Written Responses ◽  
Linguistic Inquiry Word Count ◽  
Control Procedures ◽  
Linguistic Inquiry ◽  
Psychological Processing

This paper provides methodological guidance for judgment and decision-making (JDM) researchers in accounting who are interested in using the Linguistic Inquiry Word Count (LIWC) text analysis program to analyze research participants’ written responses to open-ended questions. We discuss how LIWC’s measures of psychological constructs were developed and validated in psycholinguistic research. We then use data from an audit JDM study to illustrate the use of LIWC to guide researchers in identifying suitable measures, performing quality control procedures, and reporting the analysis. We also discuss research design considerations that will strengthen the inferences drawn from LIWC analysis. The paper concludes with examples where LIWC analysis has the potential to reveal participants’ deep, complex, effortful psychological processing and affective states from their written responses.

An Analysis of Linguistic Styles by Inferred Age in TV Dramas

2006 ◽  
Vol 99 (2) ◽  
pp. 351-356 ◽  
Author(s):  
Chang H. Lee ◽  
Jongmin Park ◽  
Young Seok Seo
Keyword(s):  
Cognitive Development ◽  
Spoken Language ◽  
Analysis Program ◽  
Word Count ◽  
Negative Stereotypes ◽  
Psychological Variables ◽  
Language Analysis ◽  
Linguistic Inquiry ◽  
Aging People ◽  
The Relationship

A language analysis program, Linguistic Inquiry and Word Count (LIWC), was successful in identifying various psychological variables. This study investigated the relationship between spoken language and age inferred from drama scripts of 162 characters, analyzed by the Korean-LIWC across 4 age categories (10–19, 20–39, 40–59, and 60–79 years). Analysis indicated that younger characters use fewer phrases, morphemes, nouns, auxiliary words, and adverbs than older characters, suggesting less cognitive development of younger characters. In addition, younger characters used less positive words for emotion and achievement than older characters. These data appear contrary to the negative stereotypes of aging people.

Understanding the Role of Language in Conflict

2019 ◽  
Vol 64 (1) ◽  
pp. 97-117 ◽  
Author(s):  
William A. Donohue ◽  
Qi Hao ◽  
Richard Spreng ◽  
Charles Owen
Keyword(s):  
Text Analysis ◽  
Word Count ◽  
Data Set ◽  
Open Source Data ◽  
Communication Events ◽  
Source Data ◽  
Linguistic Inquiry ◽  
Mind Set ◽  
The Mind

The purpose of this article is to illustrate innovations in text analysis associated with understanding conflict-related communication events. Two innovations will be explored: LIWC (Linguistic Inquiry and Word Count), the text modeling program from the open-source data analysis software program R, and SPSS Modeler. The LIWC analysis revisits the 2009 study by Donohue and Druckman and the 2014 study by Donohue, Liang, and Druckman focusing on text analyses of the Oslo I Accords between the Palestinians and Israelis to illustrate this approach. The R and SPSS modeling of text analysis use the same data set as the LIWC analysis to provide a different set of pictures associated with each leader’s rhetoric during the period in which the Oslo I accords were being negotiated. Each innovation provides different insights into the mind-set of the two groups of leaders as the secret talks were emerging. The implications of each approach in establishing an understanding of the communication exchanges are discussed to conclude the article.

Learning About Suicide from the Diary of Cesare Pavese

Crisis ◽  
2009 ◽  
Vol 30 (4) ◽  
pp. 222-224 ◽  
Author(s):  
David Lester
Keyword(s):  
Positive Emotions ◽  
Word Count ◽  
Suicide Notes ◽  
Cesare Pavese ◽  
Insight Into

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.

scholarly journals The impact of perinatal loss in maternity units: A psycholinguistic analysis of health professionals’ reactions

2017 ◽  
Vol 25 (5) ◽  
pp. 640-651 ◽  
Author(s):  
Gabriella Gandino ◽  
Giulia Di Fini ◽  
Antonella Bernaudo ◽  
Marcello Paltrinieri ◽  
Marco Castiglioni ◽  
...  
Keyword(s):  
Health Professionals ◽  
Medical Staff ◽  
Perinatal Loss ◽  
Linguistic Analysis ◽  
Emotional Impact ◽  
Clinical Implications ◽  
Word Count ◽  
Future Tense ◽  
Linguistic Inquiry ◽  
The Impact

Perinatal loss has a strong emotional impact on health professionals working in maternity units. We aimed to study the impact of this experience on health professionals’ language. We analyzed the answers of 162 health professionals (physicians and non-medical staff) who described their reactions to perinatal loss. A linguistic analysis was performed using the Linguistic Inquiry and Word Count software. Associations between language and burnout were studied. Words typical of a psychological shock reaction were used more by non-medical staff than by physicians. Participants who used pronouns, optimistic words, future tense verbs, and cognitive words registered lower levels of burnout. Clinical implications of the results are discussed.

scholarly journals Usage of humor to Overshadow Islamophobia in the World

2018 ◽  
Vol 02 (02) ◽  
Author(s):  
Farzana Kausar ◽  
Dr. Wajid Zulqarnain
Keyword(s):  
United States ◽  
Positive Emotions ◽  
Qualitative Content Analysis ◽  
The United States ◽  
Word Count ◽  
Muslim Identity ◽  
American Muslim ◽  
The World ◽  
Linguistic Inquiry ◽  
The Impact

After the 9/11 incident in the United States, a hatred gap arose between the Americans and Americans Muslims. Many Muslim stand-up comedians started their efforts to decrease this tension through humorous performances and comic screenplays. Also, Muslim comedians are neutralizing negative social discrimination between Muslims and another world to reduce the impact of Islamophobia in the world. The purpose of the study is to examine the part of Muslim comedians and the sentiments of the listeners about their stand-up humor videos. This study is the qualitative content analysis of comments on videos of two American Muslim comedians Negin Farsad and Obeidallah Dean. For data analysis, Linguistic Inquiry & Word Count (LIWC) used to analyses the positive emotions, negative emotions, and emotional tone. Findings exhibit that Muslim comedians are playing a critical part to assist the Muslim community handle with the effect of Islamophobia. The study also investigated that Muslim stand-up comedians are contributing to lessen the stereotyping discernments and disliked comments about Muslim identity globally. It is concluded that comedy has also helped in comforting the audiences that Arab and Muslims are not unpatriotic and adversarial to the United States or to another world.

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