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.

scholarly journals Plurality in the Measurement of Social Media Use and Mental Health: An Exploratory Study Among Adolescents and Young Adults

2021 ◽  
Vol 7 (3) ◽  
pp. 205630512110353
Author(s):  
Diamantis Petropoulos Petalas ◽  
Elly A. Konijn ◽  
Benjamin K. Johnson ◽  
Jolanda Veldhuis ◽  
Nadia A. J. D. Bij de Vaate ◽  
...  
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Young Adults ◽  
Media Effects ◽  
Exploratory Study ◽  
Social Life ◽  
Media Use ◽  
Quadratic Functions ◽  
Adolescents And Young Adults ◽  
Social Media Use

On a daily basis, individuals between 12 and 25 years of age engage with their mobile devices for many hours. Social Media Use (SMU) has important implications for the social life of younger individuals in particular. However, measuring SMU and its effects often poses challenges to researchers. In this exploratory study, we focus on some of these challenges, by addressing how plurality in the measurement and age-specific characteristics of SMU can influence its relationship with measures of subjective mental health (MH). We conducted a survey among a nationally representative sample of Dutch adolescents and young adults ( N = 3,669). Using these data, we show that measures of SMU show little similarity with each other, and that age-group differences underlie SMU. Similar to the small associations previously shown in social media-effects research, we also find some evidence that greater SMU associates to drops and to increases in MH. Albeit nuanced, associations between SMU and MH were found to be characterized by both linear and quadratic functions. These findings bear implications for the level of association between different measures of SMU and its theorized relationship with other dependent variables of interest in media-effects research.

scholarly journals Necessary connections: ‘Feelings photographs’ in criminal justice research

2020 ◽  
Vol 13 (2) ◽  
pp. 205979912092525
Author(s):  
Chrissie Rogers
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Social Life ◽  
Mental Health Problems ◽  
Life Story ◽  
Autism Spectrum ◽  
Visual Methods ◽  
Television Shows ◽  
Self Harm

Visual representations of prisons and their inmates are common in the news and social media, with stories about riots, squalor, drugs, self-harm and suicide hitting the headlines. Prisoners’ families are left to worry about the implications of such events on their kin, while those incarcerated and less able to understand social cues, norms and rules, are vulnerable to deteriorating mental health at best, to death at worst. As part of the life-story method in my research with offenders who are on the autism spectrum, have mental health problems and/or have learning difficulties, and prisoner’s mothers, I asked participants to take photographs, reflecting upon their experiences. Photographs, in this case, were primarily used to help respondents consider and articulate their feelings in follow-up interviews. Notably, seeing (and imagining) is often how we make a connection to something (object or feeling), or someone (relationships), such that images in fiction, news/social media, drama, art, film and photographs can shape the way people think and behave – indeed feel about things and people. Images and representations ought to be taken seriously in researching social life, as how we interpret photographs, paintings, stories and television shows is based on our own imaginings, biography, culture and history. Therefore, we look at and process an image before words escape, by ‘seeing’ and imagining. How my participants and I ‘collaborate’ in doing visual methods and then how we make meaning of the photographs in storying their feelings, is insightful. As it is, I wanted to enable my participants to make and create their own stories via their photographs and narratives, while connecting to them, along with my own interpretation and subjectivities.

scholarly journals A Corpus Linguistic Analysis of Pro-Anorexia Public Tumblr Posts Written in Spanish

2019 ◽  
Author(s):  
Kristeen Elrod ◽  
Cass Dykeman
Keyword(s):  
Mental Health ◽  
Early Adulthood ◽  
Future Research ◽  
Evidence Based ◽  
Word Count ◽  
Trauma Narratives ◽  
Evidence Based Treatment ◽  
Corpus Linguistic ◽  
Pronoun Use ◽  
Linguistic Inquiry

Eating disorders have the highest mortality rate of any mental illness, affecting all races and ethnicities, and with symptoms typically beginning in adolescence and early adulthood. Still, little is known about the language markers of mental health for materials written in Spanish. This study collected pro-anorexia (pro-ana) public Tumblr blog posts written in Spanish and analyzed their content using Linguistic Inquiry and Word Count software. Pro-ana-specific words, pronoun use, and psychological linguistic properties were analyzed, and results indicated that reasons for anorexia was the most frequently occurring category within pro-ana posts. Words in this category were associated with intense and negative emotions commonly found in trauma narratives in the dominant language (Spanish). Users’ pronoun use suggested an increased focus on people and objects, which has been linked to decreased likelihood of recovery. The psychological properties of the posts had a negative emotional tone and were marked by significant use of ingestion and health words, signaling the symptoms of anorexia. This research points to benefits in assessing bilingual clients for anorexia behaviors, symptoms, and online-posting behaviors, while also revealing the need for improved evidence-based treatment for trauma in bilingual individuals, as well as the need for Spanish and code-switching blog norms to inform and advance future research.

scholarly journals Predicting Cardiovascular Risk Using Social Media Data: Performance Evaluation of Machine-Learning Models

JMIR Cardio ◽  
10.2196/24473 ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. e24473
Author(s):  
Anietie U Andy ◽  
Sharath C Guntuku ◽  
Srinath Adusumalli ◽  
David A Asch ◽  
Peter W Groeneveld ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Learning Model ◽  
Discriminatory Power ◽  
Risk Scores ◽  
Atherosclerotic Cardiovascular Disease ◽  
Word Count ◽  
Machine Learning Model ◽  
Linguistic Inquiry ◽  
Ascvd Risk

Background Current atherosclerotic cardiovascular disease (ASCVD) predictive models have limitations; thus, efforts are underway to improve the discriminatory power of ASCVD models. Objective We sought to evaluate the discriminatory power of social media posts to predict the 10-year risk for ASCVD as compared to that of pooled cohort risk equations (PCEs). Methods We consented patients receiving care in an urban academic emergency department to share access to their Facebook posts and electronic medical records (EMRs). We retrieved Facebook status updates up to 5 years prior to study enrollment for all consenting patients. We identified patients (N=181) without a prior history of coronary heart disease, an ASCVD score in their EMR, and more than 200 words in their Facebook posts. Using Facebook posts from these patients, we applied a machine-learning model to predict 10-year ASCVD risk scores. Using a machine-learning model and a psycholinguistic dictionary, Linguistic Inquiry and Word Count, we evaluated if language from posts alone could predict differences in risk scores and the association of certain words with risk categories, respectively. Results The machine-learning model predicted the 10-year ASCVD risk scores for the categories <5%, 5%-7.4%, 7.5%-9.9%, and ≥10% with area under the curve (AUC) values of 0.78, 0.57, 0.72, and 0.61, respectively. The machine-learning model distinguished between low risk (<10%) and high risk (>10%) with an AUC of 0.69. Additionally, the machine-learning model predicted the ASCVD risk score with Pearson r=0.26. Using Linguistic Inquiry and Word Count, patients with higher ASCVD scores were more likely to use words associated with sadness (r=0.32). Conclusions Language used on social media can provide insights about an individual’s ASCVD risk and inform approaches to risk modification.

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.

Developing and validating the A-B-C framework of information diffusion on social media

2016 ◽  
Vol 20 (1) ◽  
pp. 272-292 ◽  
Author(s):  
Yuhua (Jake) Liang ◽  
Kerk F Kee
Keyword(s):  
Social Media ◽  
Information Diffusion ◽  
Instructional Material ◽  
Original Research ◽  
Word Count ◽  
Operational Strategies ◽  
Social Media Platforms ◽  
Linguistic Inquiry ◽  
Communication Material ◽  
Blog Posts

This research addresses the problem of promoting information diffusion, the extent to which information spreads, on social media platforms. Utilizing the number of views, comments, and shares as indicators of diffusion, we developed and validated an original research framework based on the big data approach (using all the blog posts in a university in the year 2013; N = 4120). This A-B-C framework (1) analyzes the textual features of blog posts using linguistic inquiry and word count (Study 1), (2) applies the former results to build message concepts (Study 2), and (3) creates validated instructional material based on message concepts to promote message diffusion among blog readers (Study 3). This framework supports operational strategies for developing strategic and corporate communication material aimed at increasing diffusion.

Pro- and anti-opioid use posts on Reddit: A Content Analysis (Preprint)

2020 ◽  
Author(s):  
Shreya Godishala ◽  
Anna Jolliff
Keyword(s):  
United States ◽  
Social Media ◽  
Content Analysis ◽  
Health Risks ◽  
Online Community ◽  
The United States ◽  
Word Count ◽  
Opioid Use ◽  
Linguistic Inquiry ◽  
Variable Focus

BACKGROUND Opioid use is a leading cause of injury-related deaths in the United States. Past studies have shown that analyzing opioid-related social media has the potential to reveal patterns of opioid abuse offline. OBJECTIVE The purpose of this study is to examine how users are posting about pro and anti- opioid use on Reddit. METHODS There were 100 posts selected from the Reddit online community r/Opioids. The comments and upvotes for each of the posts were collected. The posts were also run through Linguistic Inquiry and Word Count software with 16 variables. RESULTS There were on average more comments for anti- opioid posts (M= 9.06 , SD =12.22) than for the average number of comments for pro- opioid posts (M=14.88, SD= 17.89) t(81)= (2.79), p = 0.0065 < 0.05. There were on average more upvotes for anti- opioid posts (M= 1.58 , SD =1.98) than for the average number of comments for pro- opioid posts (M= 41.67, SD= 16.36), t(81)= (16.84), p = 0.0001. For LIWC variable Focus Present was found to be more significant in anti- opioid posts (M= 11.19, SD =5.79) than for pro- opioid posts (M= 15.58, SD=9.81), t(98)= (2.82), p =.0207. Focus future was also found to be more significant in anti- opioid posts (M= 1.63 , SD =1.86) than for pro- opioid posts (M=1.63, SD= 1.86), t(98)= (2.84), p = .0244. CONCLUSIONS Although there were on average more pro-opioid use posts in the online community, there seemed to be more engagement and support for the anti-opioid use posts. For the LIWC variables that were analyzed, Focus Present and Focus Future were found to be significant. This suggests that some users may be more likely to use vocabulary pertaining to future and present situations while looking at the health risks of opioids.

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