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 Development of the Japanese Version of the Linguistic Inquiry and Word Count Dictionary 2015 (J-LIWC2015)

2021 ◽  
Author(s):  
Tasuku Igarashi ◽  
Kazutoshi Sasahara
Keyword(s):  
Language Processing ◽  
Japanese Version ◽  
Computational Social Science ◽  
Cross Cultural ◽  
Word Count ◽  
Semantic Equivalence ◽  
Cultural Research ◽  
Frequency Of Use ◽  
Powerful Research Tool ◽  
Linguistic Inquiry

The Linguistic Inquiry and Word Count Dictionary 2015 (LIWC2015) is a standard text analysis dictionary that quantifies linguistic/psychometric properties of English words. The development of a Japanese version of the LIWC2015 dictionary (J-LIWC2015) has been expected in the fields of natural language processing and cross-cultural research. This study aims to create J-LIWC2015 through systematic investigations of the original dictionary and Japanese corpora. All words in the LIWC2015 dictionary were initially subjected to human and machine translation into Japanese. After verifying the frequency of use of the words in large corpora, frequent words and phrases that are unique to Japanese were added to the dictionary, followed by re-category assignments by psychologists. The updated dictionary indicated good internal consistency, semantic equivalence with the original LIWC2015 dictionary, and good construct validity in each category. The evidence suggests that the J-LIWC2015 dictionary is a powerful research tool in computational social science to scrutinize psychological processes behind Japanese texts and to promote standardized cross-cultural investigations in combination with the LIWC dictionaries in different languages.

The Effects of Social Environment on Pronouns as a Measure of Self-Awareness

2018 ◽  
Author(s):  
Nicole Persall
Keyword(s):  
Mental Disorders ◽  
Social Environment ◽  
Focus Of Attention ◽  
The Self ◽  
First Person ◽  
Self Awareness ◽  
Word Count ◽  
Group Setting ◽  
Psychological States ◽  
Linguistic Inquiry

By analyzing the types of words used in people’s writing, we can make inferences about the different psychological states individuals may be in. According to previous research, the types of pronouns people express in their language can give information about their focus of attention. Greater use of first person singular pronouns is indicative of higher levels of self-awareness. People's focus of attention can be shifted towards the self by placing a mirror in front of them, or shifted to others by having other people present. This study manipulated levels of self-awareness in individuals, and then measured the pronoun usage in their writing using Linguistic Inquiry and Word Count (LIWC2007). The results showed that the mirror condition displayed a significantly higher frequency of first person pronouns compared to the group condition. These results indicate that an individual setting with a mirror increases self-awareness, and that a group setting with no mirror reduces self-awareness. Researching self-awareness is important because it is a basic trait in humans, and a lack of, or excessive levels of self-awareness may indicate psychological problems, thus it can be applied to the study of mental disorders such as depression and mania.

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.

Assessment of Agreement Between Human Ratings and Lexicon-Based Sentiment Ratings of Open-Ended Responses on a Behavioral Rating Scale

Assessment ◽  
2021 ◽  
pp. 107319112199646
Author(s):  
Olivia Gratz ◽  
Duncan Vos ◽  
Megan Burke ◽  
Neelkamal Soares
Keyword(s):  
Sentiment Analysis ◽  
Language Processing ◽  
Rating Scales ◽  
Clinical Decision Making ◽  
Rating Scale ◽  
Clinical Decision ◽  
Assessment System ◽  
Word Count ◽  
Positive Correlation ◽  
Sentiment Score

To date, there is a paucity of research conducting natural language processing (NLP) on the open-ended responses of behavior rating scales. Using three NLP lexicons for sentiment analysis of the open-ended responses of the Behavior Assessment System for Children-Third Edition, the researchers discovered a moderately positive correlation between the human composite rating and the sentiment score using each of the lexicons for strengths comments and a slightly positive correlation for the concerns comments made by guardians and teachers. In addition, the researchers found that as the word count increased for open-ended responses regarding the child’s strengths, there was a greater positive sentiment rating. Conversely, as word count increased for open-ended responses regarding child concerns, the human raters scored comments more negatively. The authors offer a proof-of-concept to use NLP-based sentiment analysis of open-ended comments to complement other data for clinical decision making.

A Mixed Methods Analysis of Parental Perspectives on Diagnosis and Prognosis of Neonatal Intensive Care Unit Graduates With Cerebral Palsy

2020 ◽  
Vol 35 (5) ◽  
pp. 336-343
Author(s):  
Katherine Guttmann ◽  
John Flibotte ◽  
Sara B. DeMauro ◽  
Holli Seitz
Keyword(s):  
Intensive Care Unit ◽  
Cerebral Palsy ◽  
Content Analysis ◽  
Intensive Care ◽  
Neonatal Intensive Care Unit ◽  
Thematic Analysis ◽  
Neonatal Intensive Care ◽  
Free Text ◽  
Word Count ◽  
Linguistic Inquiry

This study aimed to evaluate how parents of former neonatal intensive care unit patients with cerebral palsy perceive prognostic discussions following neuroimaging. Parent members of a cerebral palsy support network described memories of prognostic discussions after neuroimaging in the neonatal intensive care unit. We analyzed responses using Linguistic Inquiry and Word Count, manual content analysis, and thematic analysis. In 2015, a total of 463 parents met eligibility criteria and 266 provided free-text responses. Linguistic Inquiry and Word Count analysis showed that responses following neuroimaging contained negative emotion. The most common components identified through the content analysis included outcome, uncertainty, hope/hopelessness, and weakness in communication. Thematic analysis revealed 3 themes: (1) Information, (2) Communication, and (3) Impact. Parents of children with cerebral palsy report weakness in communication relating to prognosis, which persists in parents’ memories. Prospective work to develop interventions to improve communication between parents and providers in the neonatal intensive care unit is necessary.

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

scholarly journals Human Gaze Assisted Artificial Intelligence: A Review

2020 ◽  
Author(s):  
Ruohan Zhang ◽  
Akanksha Saran ◽  
Bo Liu ◽  
Yifeng Zhu ◽  
Sihang Guo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cognitive State ◽  
Data Sets ◽  
Common Goal ◽  
Research Areas ◽  
Future Challenges ◽  
Potential Applications ◽  
High Level ◽  
And Robotics

Human gaze reveals a wealth of information about internal cognitive state. Thus, gaze-related research has significantly increased in computer vision, natural language processing, decision learning, and robotics in recent years. We provide a high-level overview of the research efforts in these fields, including collecting human gaze data sets, modeling gaze behaviors, and utilizing gaze information in various applications, with the goal of enhancing communication between these research areas. We discuss future challenges and potential applications that work towards a common goal of human-centered artificial intelligence.

Tweeting on dementia: A snapshot of the content and sentiment of tweets associated with dementia

First Monday ◽  
2021 ◽  
Author(s):  
David Robertshaw ◽  
Ivana Babicova
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Lewy Body Dementia ◽  
Future Research ◽  
Search Term ◽  
Word Count ◽  
Emotional Tone ◽  
Search Terms ◽  
Linguistic Inquiry ◽  
World List

This study aimed to record and characterise tweets related to dementia, to investigate their content and sentiment. Data were extracted from Twitter over a period of six weeks during February and March 2019 and then analysed using Linguistic Inquiry and Word Count (LIWC) and AntWordProfiler. Using five search terms related to dementia, this study collected 860,383 tweets (more than 27 million words). Results have shown that out of all the collected tweets, 48.63 percent of tweets related to the search term ‘dementia’, 49.95 percent to ‘Alzheimer’s disease’ and the remainder related to frontotemporal dementia, Lewy Body dementia and vascular dementia. People wrote more positively and personally about the term ‘dementia’ than the other terms, and more technically regarding the term ‘Alzheimer’s disease’. All search terms had a negative emotional tone overall. Dementia and related terms are commonly discussed on Twitter. The overall negative emotional tone associated with all dementia related search terms suggests that dementia is still largely stigmatised and talked about negatively. Recommendations for future research include the development of a health world list or a dementia world list, and to consider how the results of this research inform social change interventions going forwards.

Measuring Emotional Expression with the Linguistic Inquiry and Word Count

2007 ◽  
Vol 120 (2) ◽  
pp. 263 ◽  
Author(s):  
Jeffrey H. Kahn ◽  
Renée M. Tobin ◽  
Audra E. Massey ◽  
Jennifer A. Anderson
Keyword(s):  
Emotional Expression ◽  
Word Count ◽  
Linguistic Inquiry
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