scholarly journals Post-Traumatic Growth and Identity Construction in Covid-19 Messages Delivered to the People of Ghana by President Nana Akuffo Addo

2021 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Cynthia Logogye ◽  
Bernard Asafo-Duho ◽  
Joseph B.A. Afful
Keyword(s):  
Cognitive Processing ◽  
Analysis Tool ◽  
Word Count ◽  
Emotion Words ◽  
Linguistic Markers ◽  
Post Traumatic Growth ◽  
The People ◽  
High Prevalence ◽  
Post Traumatic ◽  
Linguistic Inquiry

This work analyses post-traumatic growth in Covid-19 addresses delivered to the people of Ghana by President Nana Akuffo Addo. We draw on Post-Traumatic Growth Theory to explain how Akuffo Addo constructs a new identity for himself and the nation in order to navigate through the pandemic and forge an agenda of growth and prosperity for Ghana. The study employs a linguistic content analysis approach. The data consists of twenty different speeches from the president to the people. The speeches are first analysed and coded manually for the five main tenets of Post-Traumatic Growth (PTG) identified in the updates. Consequently, the linguistic markers that are used in reconstructing the Ghanaian identity in response to the pandemic are delineated and mapped to the goals of the president using the Linguistic Inquiry and Word Count 2015 (LIWC2015; Pennebaker et al., 2015) software; a vocabulary analysis tool. The analysis showed that there was a high prevalence of personal pronoun use, use of positive-emotion words, and cognitive-processing words. This confirms our hypothesis that linguistic markers can be used to detect PTG.

Emotion Word Use by Adolescents Who Stutter: An Exploratory Study

2013 ◽  
Vol 23 (1) ◽  
pp. 6-14
Author(s):  
Corrin G. Richels ◽  
Rogge Jessica
Keyword(s):  
Positive Emotion ◽  
Negative Emotion ◽  
Conversational Speech ◽  
Word Count ◽  
Word Use ◽  
Emotion Words ◽  
Emotion Word ◽  
Linguistic Inquiry ◽  
Positive Valence ◽  
Analyze Data

Purpose: Deficits in the ability to use emotion vocabulary may result in difficulties for adolescents who stutter (AWS) and may contribute to disfluencies and stuttering. In this project, we aimed to describe the emotion words used during conversational speech by AWS. Methods: Participants were 26 AWS between the ages of 12 years, 5 months and 15 years, 11 months-old (n=4 females, n=22 males). We drew personal narrative samples from the UCLASS database. We used Linguistic Inquiry and Word Count (LIWC) software to analyze data samples for numbers of emotion words. Results: Results indicated that the AWS produced significantly higher numbers of emotion words with a positive valence. AWS tended to use the same few positive emotion words to the near exclusion of words with negative emotion valence. Conclusion: A lack of diversity in emotion vocabulary may make it difficult for AWS to engage in meaningful discourse about negative aspects of being a person who stutters

Linguistic Inquiry and Word Count (LIWC)

2012 ◽  
pp. 206-229 ◽  
Author(s):  
Cindy K. Chung ◽  
James W. Pennebaker
Keyword(s):  
Group Dynamics ◽  
Language Processing ◽  
Behavioral Outcomes ◽  
Content Word ◽  
Analysis Tool ◽  
Word Count ◽  
Psychological States ◽  
Psychological Measures ◽  
Potential Applications ◽  
Linguistic Inquiry

Linguistic Inquiry and Word Count (LIWC; Pennebaker, Booth, & Francis, 2007) is a word counting software program that references a dictionary of grammatical, psychological, and content word categories. LIWC has been used to efficiently classify texts along psychological dimensions and to predict behavioral outcomes, making it a text analysis tool widely used in the social sciences. LIWC can be considered to be a tool for applied natural language processing since, beyond classification, the relative uses of various LIWC categories can reflect the underlying psychology of demographic characteristics, honesty, health, status, relationship quality, group dynamics, or social context. By using a comparison group or longitudinal information, or validation with other psychological measures, LIWC analyses can be informative of a variety of psychological states and behaviors. Combining LIWC categories using new algorithms or using the processor to assess new categories and languages further extend the potential applications of LIWC.

scholarly journals Effects of expressive writing and use of cognitive words on meaning making and post-traumatic Growth

2019 ◽  
Vol 13 ◽  
Author(s):  
Lei Zheng ◽  
Qian Lu ◽  
Yiqun Gan
Keyword(s):  
Cognitive Processing ◽  
Expressive Writing ◽  
Cognitive Process ◽  
Meaning Making ◽  
Self Report ◽  
Stress Regulation ◽  
Presence Of Meaning ◽  
Post Traumatic Growth ◽  
Post Traumatic ◽  
Writing Task

AbstractExpressive writing can enhance cognitive processing and improve stress regulation. Particularly, the use of cognitive words (i.e., insightful and causal words) in writing may be associated with the process of meaning making and promotion of post-traumatic growth (PTG). The aim of the present study was to determine how expressive writing and the use of causal and insightful cognitive words influenced meaning making and PTG during writing. In total, 52 traumatized university students were recruited and randomly assigned to one of two writing conditions involving either an expressive writing task or a neutral writing task. The results showed that participants who engaged in expressive (vs. neutral) writing showed higher scores on the presence of meaning and PTG in the post-writing, self-report questionnaires. Moreover, writing task (expressive or neutral) and frequency of causal and insightful cognitive words were both significant predictors of meaning, which in turn led to high levels of PTG. In conclusion, the use of causal and insightful words might be a fundamental cognitive process for developing meaning in writing, which is essential for our further understanding of meaning making and PTG.

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.

An Affective-Cognitive Processing Model of Post-Traumatic Growth

2012 ◽  
Vol 19 (4) ◽  
pp. 316-325 ◽  
Author(s):  
Stephen Joseph ◽  
David Murphy ◽  
Stephen Regel
Keyword(s):  
Cognitive Processing ◽  
Post Traumatic Growth ◽  
Post Traumatic

scholarly journals Linguistic Markers of Self-Disclosure: Using YouTube Coming Out Videos to Study Disclosure Language

2020 ◽  
Author(s):  
Patrick Charles Doyle ◽  
William Keith Campbell
Keyword(s):  
Coming Out ◽  
Text Analysis ◽  
Word Count ◽  
Analysis Software ◽  
Hiv Diagnosis ◽  
Self Disclosure ◽  
Linguistic Markers ◽  
Behavior Outcomes ◽  
Youtube Videos ◽  
Linguistic Inquiry

Traditional attempts at measuring self-disclosure actually measure self-reported perceptions of disclosure, which is conflated with individual difference characteristics, or rely on trained coders, which is time-consuming. Across a pilot and two studies and using a known-groups paradigm with repeated transcripts from YouTube videos in which creators express a concealable stigmatized identity(LGBTQ, HIV diagnosis, or mental illness), we measured self-disclosure with the Linguistic Inquiry and Word Count and found support for the utility of text-based analyses for operationalization of disclosure. This output was correlated with trained coders’ ratings and was effective for predicting audience behavior outcomes, including reciprocal disclosure. Finally, we discuss the utility of text-analysis software for theoretical and applied work.

Suicidal Traits in Marilyn Monroe’s Fragments

Crisis ◽  
2013 ◽  
Vol 34 (2) ◽  
pp. 124-130 ◽  
Author(s):  
M. Fernández-Cabana ◽  
A. García-Caballero ◽  
M. T. Alves-Pérez ◽  
M. J. García-García ◽  
R. Mateos
Keyword(s):  
Language Use ◽  
Negative Emotion ◽  
Rank Correlation ◽  
First Person ◽  
Word Count ◽  
Linguistic Features ◽  
Emotion Words ◽  
Spearman’S Rank Correlation ◽  
Linguistic Inquiry ◽  
Linguistic Categories

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.

scholarly journals Linguistic Markers of Grandiose Narcissism: A LIWC Analysis of 15 Samples

2019 ◽  
Vol 38 (5-6) ◽  
pp. 773-786 ◽  
Author(s):  
Nicholas S. Holtzman ◽  
Allison M. Tackman ◽  
Angela L. Carey ◽  
Melanie S. Brucks ◽  
Albrecht C. P. Küfner ◽  
...  
Keyword(s):  
Language Use ◽  
First Person ◽  
Word Count ◽  
Grandiose Narcissism ◽  
Second Person ◽  
Linguistic Markers ◽  
Linguistic Inquiry

Narcissism is unrelated to using first-person singular pronouns. Whether narcissism is linked to other language use remains unclear. We aimed to identify linguistic markers of narcissism. We applied the Linguistic Inquiry and Word Count to texts ( k = 15; N = 4,941). The strongest positive correlates were using words related to sports, second-person pronouns, and swear words. The strongest negative correlates were using anxiety/fear words, tentative words, and words related to sensory/perceptual processes. Effects were small (each | r| < .10).

The Stuff That Verbal Person-Centered Support Is Made of: Identifying Linguistic Markers of More and Less Supportive Conversations

2018 ◽  
Vol 37 (6) ◽  
pp. 656-679 ◽  
Author(s):  
Kaitlin E. Cannava ◽  
Andrew C. High ◽  
Susanne M. Jones ◽  
Graham D. Bodie
Keyword(s):  
Cognitive Process ◽  
Social Process ◽  
Word Count ◽  
Support Providers ◽  
Linguistic Markers ◽  
Computerized Analysis ◽  
Linguistic Inquiry ◽  
Different Levels ◽  
Linguistic Content

Although the functions of messages varying in verbal person centeredness (PC) are well-established, we know less about the linguistic content that differentiates messages with distinct levels of PC. This study examines the lexicon of different levels of PC comfort and seeks to ascertain whether computerized analysis can complement human coders when coding supportive conversations. Transcripts from support providers trained to enact low, moderate, or high levels of PC were subjected to the Linguistic Inquiry and Word Count (LIWC) dictionary. Results reveal that several categories in the LIWC dictionary vary systematically as a function of conversational PC level. LIWC categories, particularly pronouns, social process, cognitive process, anxiety, and anger words, reliably predict which level of the PC hierarchy an interaction represents based on whether a conversation was designed to be high, moderate, or low in PC. The implications are discussed in the context of the lexicon of conversations that vary in PC.

scholarly journals Changes in Language Style and Topics in an Online Eating Disorder Community at the Beginning of the COVID-19 Pandemic: Observational Study (Preprint)

2021 ◽  
Author(s):  
Johannes Feldhege ◽  
Markus Moessner ◽  
Markus Wolf ◽  
Stephanie Bauer
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Cognitive Processing ◽  
Social Life ◽  
Topic Model ◽  
Support Networks ◽  
Word Count ◽  
Recovery Orientation ◽  
Linguistic Inquiry ◽  
Mean Differences

BACKGROUND COVID-19 has affected individuals with lived experience of eating disorders (EDs), with many reporting higher psychological distress, higher prevalence of ED symptoms, and compensatory behaviors. The COVID-19 pandemic and the health and safety measures taken to contain its spread also disrupted routines and reduced access to familiar coping mechanisms, social support networks, and health care services. Social media and the ED communities on social media platforms have been an important source of support for individuals with EDs in the past. So far, it is unknown how discussions in online ED communities changed as offline support networks were disrupted and people spent more time at home in the first months of the COVID-19 pandemic. OBJECTIVE The aim of this study is to identify changes in language content and style in an online ED community during the initial onset of the COVID-19 pandemic. METHODS We extracted posts and their comments from the ED community on the social media website Reddit and concatenated them to comment threads. To analyze these threads, we applied top-down and bottom-up language analysis methods based on topic modeling with latent Dirichlet allocation and 13 indicators from the Linguistic Inquiry and Word Count program, respectively. Threads were split into prepandemic (before March 11, 2020) and midpandemic (after March 11, 2020) groups. Standardized mean differences were calculated to estimate change between pre- and midpandemic threads. RESULTS A total of 17,715 threads (n=8772, 49.5% prepandemic threads; n=8943, 50.5% midpandemic threads) were extracted from the ED community and analyzed. The final topic model contained 21 topics. CIs excluding zero were found for standardized mean differences of 15 topics and 9 Linguistic Inquiry and Word Count categories covering themes such as ED symptoms, mental health, treatment for EDs, cognitive processing, social life, and emotions. CONCLUSIONS Although we observed a reduction in discussions about ED symptoms, an increase in mental health and treatment-related topics was observed at the same time. This points to a change in the focus of the ED community from promoting potentially harmful weight loss methods to bringing attention to mental health and treatments for EDs. These results together with heightened cognitive processing, increased social references, and reduced inhibition of negative emotions detected in discussions indicate a shift in the ED community toward a pro-recovery orientation.

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