Preliminary Analysis of Language Styles in a Sample of Schizophrenics

2007 ◽  
Vol 101 (2) ◽  
pp. 392-394 ◽  
Author(s):  
Chang H. Lee ◽  
Myungju Lee ◽  
Sungwoo Ahn ◽  
Kyungil Kim
Keyword(s):  
Preliminary Analysis ◽  
Language Use ◽  
Emotional Experience ◽  
Analysis Program ◽  
Word Count ◽  
Personal Pronouns ◽  
Normal People ◽  
Language Analysis ◽  
Linguistic Inquiry ◽  
Language Styles

Language use of schizophrenics and normal people was compared by applying the language analysis program, Korean Linguistic Inquiry and Word Count. Participants were asked to write a story about the most emotional experience of their lives on A4 size paper. 28 schizophrenics ( M age: 26 yr.) and 32 normal people (Ai age: 23 yr.) participated. Analysis showed normal people used more words about jobs and achievements and fewer words about sex and food. The schizophrenics used fewer pronouns, personal pronouns, and adverbs than the normal group. Some aspects of clinical mechanism are manifest in language uses.

Distinctive Linguistic Styles in Children with ADHD

2009 ◽  
Vol 105 (2) ◽  
pp. 365-371 ◽  
Author(s):  
Kyungil Kim ◽  
Chang Hwan Lee
Keyword(s):  
Cognitive Processes ◽  
Language Use ◽  
Control Group ◽  
Adhd Group ◽  
Word Count ◽  
Children With Adhd ◽  
Hyperactivity Disorder ◽  
Language Analysis ◽  
Dependent Variables ◽  
Linguistic Inquiry

To assess whether the writing styles of children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) combined type differ significantly from those of children in a nonclinical control group, writing samples from 17 children with ADHD combined type and 18 children in a nonclinical control group were compared using the language analysis program Korean Linguistic Inquiry and Word Count. These writing samples, produced in response to instructions, served as dependent variables. Analysis showed that children with ADHD used fewer linguistic variables (e.g., sentences, phrases, and morphemes) than the control group. In addition, the ADHD group used fewer words reflecting cognitive processes and fewer pronouns than members of the control group. Also, the ADHD group showed a different pattern in the use of words referring to friends. This study provides preliminary descriptive data on language use among children diagnosed with a main subtype of ADHD.

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.

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.

scholarly journals Detecting Recovery Problems Just in Time: Application of Automated Linguistic Analysis and Supervised Machine Learning to an Online Substance Abuse Forum (Preprint)

2018 ◽  
Author(s):  
Rachel Kornfield ◽  
Prathusha K Sarma ◽  
Dhavan V Shah ◽  
Fiona McTavish ◽  
Gina Landucci ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Trees ◽  
Real Time ◽  
Language Use ◽  
Discussion Forum ◽  
Supervised Machine Learning ◽  
Bag Of Words ◽  
Word Count ◽  
Trained Staff ◽  
Linguistic Inquiry

BACKGROUND Online discussion forums allow those in addiction recovery to seek help through text-based messages, including when facing triggers to drink or use drugs. Trained staff (or “moderators”) may participate within these forums to offer guidance and support when participants are struggling but must expend considerable effort to continually review new content. Demands on moderators limit the scalability of evidence-based digital health interventions. OBJECTIVE Automated identification of recovery problems could allow moderators to engage in more timely and efficient ways with participants who are struggling. This paper aimed to investigate whether computational linguistics and supervised machine learning can be applied to successfully flag, in real time, those discussion forum messages that moderators find most concerning. METHODS Training data came from a trial of a mobile phone-based health intervention for individuals in recovery from alcohol use disorder, with human coders labeling discussion forum messages according to whether or not authors mentioned problems in their recovery process. Linguistic features of these messages were extracted via several computational techniques: (1) a Bag-of-Words approach, (2) the dictionary-based Linguistic Inquiry and Word Count program, and (3) a hybrid approach combining the most important features from both Bag-of-Words and Linguistic Inquiry and Word Count. These features were applied within binary classifiers leveraging several methods of supervised machine learning: support vector machines, decision trees, and boosted decision trees. Classifiers were evaluated in data from a later deployment of the recovery support intervention. RESULTS To distinguish recovery problem disclosures, the Bag-of-Words approach relied on domain-specific language, including words explicitly linked to substance use and mental health (“drink,” “relapse,” “depression,” and so on), whereas the Linguistic Inquiry and Word Count approach relied on language characteristics such as tone, affect, insight, and presence of quantifiers and time references, as well as pronouns. A boosted decision tree classifier, utilizing features from both Bag-of-Words and Linguistic Inquiry and Word Count performed best in identifying problems disclosed within the discussion forum, achieving 88% sensitivity and 82% specificity in a separate cohort of patients in recovery. CONCLUSIONS Differences in language use can distinguish messages disclosing recovery problems from other message types. Incorporating machine learning models based on language use allows real-time flagging of concerning content such that trained staff may engage more efficiently and focus their attention on time-sensitive issues.

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).

scholarly journals Performing Multilingual Analysis With Linguistic Inquiry and Word Count 2015 (LIWC2015). An Equivalence Study of Four Languages

2021 ◽  
Vol 12 ◽  
Author(s):  
Diana Paula Dudău ◽  
Florin Alin Sava
Keyword(s):  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Classification Problem ◽  
Word Count ◽  
Intraclass Correlation Coefficients ◽  
Language Standardization ◽  
Language Analysis ◽  
Linguistic Inquiry ◽  
Parallel Texts ◽  
Large Corpus

Today, there is a range of computer-aided techniques to convert text into data. However, they convey not only strengths but also vulnerabilities compared to traditional content analysis. One of the challenges that have gained increasing attention is performing automatic language analysis to make sound inferences in a multilingual assessment setting. The current study is the first to test the equivalence of multiple versions of one of the most appealing and widely used lexicon-based tools worldwide, Linguistic Inquiry and Word Count 2015 (LIWC2015). For this purpose, we employed supervised learning in a classification problem and computed Pearson's correlations and intraclass correlation coefficients on a large corpus of parallel texts in English, Dutch, Brazilian Portuguese, and Romanian. Our findings suggested that LIWC2015 is a valuable tool for multilingual analysis, but within-language standardization is needed when the aim is to analyze texts sourced from different languages.

scholarly journals Linguistic Markers of Narcissism: An Exploratory LIWC Analysis of 15 Samples

2018 ◽  
Author(s):  
Nicholas S. Holtzman ◽  
Allison Mary Tackman ◽  
Albrecht Kuefner ◽  
Fenne große Deters ◽  
Mitja Back ◽  
...  
Keyword(s):  
Language Use ◽  
First Person ◽  
Word Count ◽  
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| &lt; .10).

scholarly journals Language of Criminal Confessions

2021 ◽  
Vol 2 (3) ◽  
pp. 205-225
Author(s):  
Lucrezia Rizzelli ◽  
Saul Kassin ◽  
Tammy Gales
Keyword(s):  
High Frequency ◽  
National Registry ◽  
False Confessions ◽  
Word Count ◽  
Personal Pronouns ◽  
Linguistic Features ◽  
Model Sample ◽  
Linguistic Inquiry ◽  
Innocence Project ◽  
Impersonal Pronouns

Confession evidence is powerfully persuasive, and yet many wrongful convictions involving false confessions have surfaced in recent years (Innocence Project, 2021; National Registry of Exonerations, 2021). Although police are trained to corroborate admissions of guilt, research shows that most false confessions contain accurate details and other content cues suggesting credibility as well as extrinsic evidence of guilt. Hence, a method is needed to help distinguish true and false confessions. In this study, we utilized a corpus-based approach to outline the linguistic features of two sets of confessions: those that are presumed true (n = 98) and those that have been proven false (n = 37). After analyzing the two corpora in LIWC (Linguistic Inquiry and Word Count) to identify significant categories, we created a logistic regression model that distinguished the two corpora based on three identified predictors: personal pronouns, impersonal pronouns, and conjunctions. In a first sample comprised of 25 statements per set, the model correctly categorized 37 out of 50 confessions (74%); in a second out-of-model sample, the predictors accurately classified 20 of 24 confessions (83.3%). A high frequency of impersonal pronouns was associated with confessions proven false, while a high frequency of conjunctions and personal pronouns were associated with confessions presumed to be true. Several patterns were observed in the corpora. In the latter set of confessions, for example, “I” was often followed by a lexical verb, a pattern less frequent in false confessions. Although these data are preliminary and not to be used for practical diagnostic purposes, the findings suggest that additional research is warranted.

scholarly journals News media representations of women who kill their newly born children

2021 ◽  
Author(s):  
B. Eisenwort ◽  
P. Fernandez Arias ◽  
C. M. Klier ◽  
B. Till
Keyword(s):  
News Media ◽  
Preliminary Analysis ◽  
Media Representations ◽  
Word Count ◽  
Emotional Words ◽  
The Media ◽  
Linguistic Inquiry ◽  
Media Reports ◽  
Representations Of Women ◽  
Comparative Examination

AbstractThis paper presents a first quantitative analysis of language in media reports of neonaticide and a comparative examination of language use within the reports. One thousand twenty-seven Austrian print media reports from 2004 to 2014 were retrieved; after exclusion, 331 were analysed using the Linguistic Inquiry and Word Count (LIWC) software. After a preliminary analysis, a comparative analysis was carried out between reports on the Graz case and all other cases. The preliminary analysis revealed that a majority of media reports were related to one repeat neonaticide case (Graz) despite not being clinically different from other cases identified for the same period. The comparative linguistic analysis shows some statistically significant differences relating to the domains of emotional words (less words of anxiety, sadness) and family and in the category of insight and certainty (more words). The unexpected media attention on the Graz case and the ensuing verdict, which was in contradiction with the Austrian infanticide act, might have been influenced by the way language was used by journalists and the media. The authors suggest guidelines on sensitive media reporting are required.

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