Content Analysis of Select YouTube Postings: Comparisons of Reactions to the Sandy Hook and Aurora Shootings and Hurricane Sandy

Sharing emotion while spectating video game play: Exploring Twitch users' emotional change after the outbreak of the COVID-19 pandemic

This paper examines how the COVID-19 pandemic associates with Twitch users' emotion, using natural language processing (NLP) as a method. Two comparable sets of text data were collected from Twitch internet relay chats (IRCs): one after the outbreak of the pandemic and another one before that. Positive emotion, negative emotion, and attitude to social interaction were tested by comparing the two text sets via a dictionary-based NLP program. Particularly regarding negative emotion, three negative emotions—anger, anxiety, and sadness—were measured given the nature of the pandemic. The results show that users' anger and anxiety significantly increased after the outbreak of the pandemic, while changes in sadness and positive emotion were not statistically significant. In terms of attitude to social interaction, users used significantly fewer “social” words after the outbreak of the pandemic than before. These findings were interpreted considering the nature of Twitch as a unique live mixed media platform, and how the COVID-19 pandemic is different from previous crisis events was discussed based on prior literature.

Commenting and connecting: A thematic analysis of responses to YouTube vlogs about borderline personality disorder

Borderline Personality Disorder (BPD) is an often misunderstood and stigmatized mental health difficulty. Increasingly, social media has been used as a forum to share dialogue on such difficulties. This research analysed YouTube comments in response to personal vlogs about living with BPD. The key term 'Living with Borderline Personality Disorder Vlog' was inputted into a YouTube Ireland search, results were displayed by relevance and the top four vlogs that met the criteria were chosen for analysis. A total of 1197 comments (approximately 55,574 words) were analysed using inductive thematic analysis (Braun and Clarke, 2006). Five distinct themes were identified: 1) Sharing advice, support and encouragement, 2) Vlogs destigmatizing, informing and educating, 3) Solidarity, relatability and personal connection, 4) Intense, unstable intrapersonal and interpersonal functioning, 5) Prompting disclosures about mental health struggles. The vlogs gave people insight and understanding, increasing empathy towards those suffering with BPD or with their mental health. The overall picture drawn from the data was one of solidarity, support, de-stigmatization, normalization, sharing, comfort and encouragement. Further research into people's attitudes towards BPD, their opinions and knowledge of the disorder, may help make important changes, inform policies and practice, and ultimately improve the lives of those living with the disorder.

YouTube Video Comments on Healthy Eating: Descriptive and Predictive Analysis

Background

Poor nutrition and food selection lead to health issues such as obesity, cardiovascular disease, diabetes, and cancer. This study of YouTube comments aims to uncover patterns of food choices and the factors driving them, in addition to exploring the sentiments of healthy eating in networked communities.

Objective

The objectives of the study are to explore the determinants, motives, and barriers to healthy eating behaviors in online communities and provide insight into YouTube video commenters’ perceptions and sentiments of healthy eating through text mining techniques.

Methods

This paper applied text mining techniques to identify and categorize meaningful healthy eating determinants. These determinants were then incorporated into hypothetically defined constructs that reflect their thematic and sentimental nature in order to test our proposed model using a variance-based structural equation modeling procedure.

Results

With a dataset of 4654 comments extracted from YouTube videos in the context of Malaysia, we apply a text mining method to analyze the perceptions and behavior of healthy eating. There were 10 clusters identified with regard to food ingredients, food price, food choice, food portion, well-being, cooking, and culture in the concept of healthy eating. The structural equation modeling results show that clusters are positively associated with healthy eating with all P values less than .001, indicating a statistical significance of the study results. People hold complex and multifaceted beliefs about healthy eating in the context of YouTube videos. Fruits and vegetables are the epitome of healthy foods. Despite having a favorable perception of healthy eating, people may not purchase commonly recognized healthy food if it has a premium price. People associate healthy eating with weight concerns. Food taste, variety, and availability are identified as reasons why Malaysians cannot act on eating healthily.

Conclusions

This study offers significant value to the existing literature of health-related studies by investigating the rich and diverse social media data gleaned from YouTube. This research integrated text mining analytics with predictive modeling techniques to identify thematic constructs and analyze the sentiments of healthy eating.

Where and How to Look for Help Matters: Analysis of Support Exchange in Online Health Communities for People Living with HIV

Research is scarce on how direct and indirect support seeking strategies affect support exchange in online health communities. Moreover, prior research has relied mostly on content analysis of forum posts at the post level. In order to generate a more fine-grained analysis of support exchange, we conducted content analysis at the utterance level, taking directness of support seeking, quality of provision, forum type, and seeker gender into account. Our analysis of four popular online support forums for people living with human immunodeficiency virus found that type of support sought and provided, support seeking strategy, and quality of emotional support provision differed in care provider/formal forums versus social/informal forums. Interestingly, indirect support seeking tended to elicit more supportive emotional responses than direct support seeking strategies in all forums; we account for this in terms of type of support sought. Practical implications for online support communities are discussed.