Xinyu Zhang

Conversational AI, such as ChatGPT, is increasingly used for information seeking. However, little is known about how ordinary users actually prompt and how ChatGPT adapts its responses in real-world conversational information seeking (CIS). In this study, a nationally representative sample of 937 U.S. adults engaged in multi-turn CIS with ChatGPT on both controversial and non-controversial topics across science, health, and policy contexts. We analyzed both users’ prompting strategies and the communication styles of ChatGPT’s responses. The findings revealed behavioral signals of digital divide: only 19.1% of users employed prompting strategies, and these users were disproportionately more educated and Democrat-leaning. Further, ChatGPT demonstrated contextual adaptation: responses to controversial topics contain more cognitive complexity and more external references than to non-controversial topics. Notably, cognitively complex responses were perceived as less favorable but produced more positive issue-relevant attitudes. This study highlights disparities in user prompting behaviors and shows how user prompts and AI responses together shape information-seeking with conversational AI.

We examined whether bypassing and combined (correction with bypassing) strategies delivered through artificial intelligence (AI) chatbots can address contraceptive misinformation. In Study 1, we found through observational reddit data that bypassing, correction, and combined strategies were present in online discussions and were more engaging than other responses. In Study 2, an experiment employing AI chatbots found that the combined strategy improved recommendation intentions compared with the control conditions, while also reducing beliefs in misinformation. The combined strategy AI chatbot was viewed as warmer and more competent than the correction, invoking less reactance and increasing recommendation intentions. Practical and theoretical implications are discussed.

Network support remains an underexplored type of social support. We address this gap by exploring how people tell personal stories about challenges in network support processes. Specifically, we focus on the “friend problems”, in which a romantic relationship is hindered by friends. Mixed-methods analyses of 900 Reddit posts revealed three major themes: challenges in gaining support from a partner’s friends, in intermediating between one’s partner and friends, and in approving a friend’s relationship; significant differences in gender and couple type (i.e., different-sex vs. same-sex) were found. Linguistic and qualitative analysis revealed three narrative roles: the rejected newcomers, torn middlepersons, and judgmental friends. The findings show network support is a contested communicative process of managing exclusion, negotiating power, and sustaining relational legitimacy.

The digital age has fueled a surge in ADHD self-diagnosis as people turn to online platforms for mental health information. However, the relationship between validation-seeking behaviors and self-perception in these online communities and users’ self-perception has received limited scholarly focus. Drawing on self-verification theory and utilizing natural language processing to analyze 452,026 posts from the r/ADHD subreddit, our study uncovers distinct patterns in validation-seeking behaviors. Results show that (a) self-diagnosed individuals with ADHD are more likely to seek social validation and media validation and to report higher levels of negative self-image and internalized stigma than clinically diagnosed individuals, (b) social validation was strongly associated with both positive and negative self-perceptions; and (c) diagnosis status significantly moderated these relationships, such that the effects of social validation on self-image and stigma were consistently weaker for the self-diagnosed group. Theoretically, this study extends self-verification theory by demonstrating that professional verification hierarchically moderates self-verification effectiveness. This implies a practical need for clinicians to acknowledge online validation seeking and for digital communities to affirm user experiences while mitigating stigma.

Astrology on social media has emerged as an important influence in shaping personal self-concepts and relationships. Building on the sensemaking theory, this study employs semi-structured interviews to explore how individuals make sense of astrology short videos on Douyin to navigate identity and intimacy. Findings illustrate how individuals interpret these videos to construct an “Imagined Self” that merges collective meanings with personal interpretations. Douyin acts as a “Holy Technology,” enabling algorithmic interactions that reinforce spiritual narratives. In addition, the regulated nature of astrology content on Douyin prompts users to demonstrate agency in creatively negotiating and adapting astrological meanings within China’s unique sociopolitical context. This research advances sensemaking theory by demonstrating its applicability to the digitally mediated construction of identity and intimacy, contributing to our understanding of digital spirituality.

Background: Antidepressants are crucial for managing major depressive disorders; however, nonadherence remains a widespread challenge, driven by concerns over side effects, fear of dependency, and doubts about efficacy. Understanding patients’ experiences is essential for improving patient-centered care and enhancing adherence, which prioritizes individual needs in treatment. Objective: This study aims to gain a deeper understanding of patient experiences with antidepressants, providing insights that health care providers, families, and communities can develop into personalized treatment strategies. By integrating patient-centered care, these processes may improve satisfaction and adherence with antidepressants. Methods: Data were collected from AskaPatient and Reddit, analyzed using natural language processing and large language models. Analytical techniques included sentiment analysis, emotion detection, personality profiling, and topic modeling. Furthermore, demographic variations in patient experiences were also examined to offer a comprehensive understanding of discussions around antidepressants. Results: Sentiment and emotion analysis revealed that the majority of discussions (21,499/36,253, 59.3%) expressed neutral sentiments, with negative sentiments following closely (13,922/36,253, 38.4%). The most common emotions were fear (16,196/36,253, 44.66%) and sadness (12,507/36,253, 34.49%). The largest topic, “Mental Health and Relationships,” accounted for 11.69% (3755/36,253) of the discussions, which indicated a significant focus on managing mental health conditions. Discussions around nonadherence were marked by fear, followed by sadness, while self-care discussions showed a notable trend of sadness. Conclusions: These psychological insights into public perceptions of antidepressants provide a foundation for developing tailored, patient-centered treatment approaches that align with individual needs, enhancing both effectiveness and empathy of care.

Background: Adolescent substance use disorder is a pressing public health issue, with increasing prevalence as individuals age. Social media platforms like Reddit (Reddit Inc) serve as significant venues for teenagers to discuss and navigate substance use. Social media platforms, such as Reddit, serve as increasingly important spaces where teenagers discuss, share, and navigate their experiences with substance use, presenting unique opportunities and challenges for understanding and addressing this issue. Objective: This study aims to explore how teenagers frame substance-use discussions on the r/teenagers subreddit, focusing on their personal interpretations, causal attributions, and the social and psychological contexts that shape these online support groups. By identifying these interpretive frames, we aimed to better understand the complex drivers of adolescent substance use behavior and their potential interventions. Methods: Using natural language processing techniques, we analyzed 32,674 substance use–related posts from 2018 to 2022. A framing approach was used to identify and categorize prevalent themes, supplemented by emotional profiling using the EmoLLaMA-chat-13B model developed by Liu and colleagues. Results: In total, 7 primary frames emerged: normalization, risk awareness, social integration, autonomy and rebellion, coping mechanisms, media influence, and stigmatization. These frames varied in prevalence and were associated with distinct emotional profiles, highlighting the complex interplay between substance use and adolescent experiences. We observed that, for example, the normalization frame was often associated with a mix of sadness and anxiety, while the coping frame exhibited elevated levels of anger, sadness, and anxiety. These distinctive emotional landscapes associated with each frame reveal unique insights into the mental state of adolescents navigating substance use. Conclusions: The findings underscore the multifaceted nature of adolescent substance-use discussions on social media. Interventions must address underlying emotional and social factors as well as identity to effectively mitigate substance use disorder among adolescents. By understanding the frames teenagers use to interpret substance use, we can pave the way for more effective and personalized public health campaigns, and support services designed to resonate with adolescents’ unique lived experiences.

BACKGROUND Substance use among adolescents represents a significant public health concern. Despite research on the influence of contextual factors on teenage substance use, the nuances of these contexts and associated emotions remain underexplored, particularly within online communities. OBJECTIVE This study aims to decode the context factors, emotion tones, and topics discussed in substance use-related posts within the r/teenager subreddit. We introduce an innovative approach leveraging natural language processing to analyze discussions within a large online community of teenagers on Reddit. METHODS We collected 31,724 substance use-related posts from the r/teenagers subreddit in English, spanning from 2018 to 2023. A mixed methods was applied on these posts, including trend analysis to explore the dynamic context within the data. The BERT family of models was used to extract sentiment and topic features. RESULTS The analysis revealed that "drink" and "weed" were the most frequently mentioned substances among teenagers. Peaks in discussions occurred during summer months, particularly in July 2023. Substance use posts exhibited higher levels of negative emotions such as annoyance, sadness, and disappointment. Family dynamics significantly impacted the teenage substance use environment and behaviors. The term "Dad" was commonly associated with familial roles and the setting of examples within the household, particularly regarding habits and behaviors around substance consumption and addiction. The term "Mum" was often at the forefront of familial discussions about marijuana and smoking cessation. CONCLUSIONS The study's findings provide deeper insights into the multifaceted nature of substance use discussions among teenagers, informing potential intervention strategies and future research directions. The authors underscore the need for targeted interventions addressing peer influence, familial communication, and emotional well-being in mitigating adolescent substance use.

BACKGROUND Antidepressant medications are widely used to manage depression and anxiety disorders. Given that these medications have been around for many years, their side effects are well documented. Apart from common side effects, there are new emerging data reporting unexpected side effects or stress related challenges that clinicians should be aware of. OBJECTIVE The goal of this study to analyze the demographic profiles, symptomatology, and platform-specific differences in online discussions about antidepressant side effects. Exploring the antidepressant side effects in different gender and age, then the clinical with detailed information to improve the documentation and management of drug side effects. METHODS We collected dataset from Ask a patient and Reddit platform. A mixed methods approach including quantitative analysis and qualitative analysis. Which we leverage Natural Language Processing method to examine the demographic and symptoms comments, and exploring the language linguistic patterns on word, topic, and theme of posts. RESULTS The analysis highlighted significant gender-based differences in antidepressant side effects. Females reported more gastrointestinal, neurological, sleep, general physical, and emotional symptoms, while males reported more sexual health issues. Users frequently discussed withdrawal symptoms and challenges with switching medications, revealing anxiety about the withdrawal process. Unique symptoms such as toe infections, visual changes, and pulsatile tinnitus were also noted. The strong correlation between fear and neurological, gastrointestinal, and sleep-related symptoms suggests these physical symptoms significantly contribute to emotional distress. CONCLUSIONS These findings underscore the necessity for gender-sensitive healthcare approaches and highlight new concerns that are not typically covered in standard drug descriptions. Addressing these issues directly in consultations can improve patient outcomes by fostering better adherence to medication regimens and enhancing overall treatment satisfaction. Future research should focus on understanding the unique challenges faced by specific demographics, particularly women in reproductive age who use birth control, to provide more effective and personalized care.

Research on online pornography abstinence movements has predominantly focused on men’s perspectives, often within the context of the broader manosphere. This focus has overshadowed the unique experiences and viewpoints of women in these movements. Our study aimed to fill this gap by exploring women-centric perspectives in pornography abstinence forums, particularly Porn Free Women (r/pornfreewomen). Using a mixed methods approach, this study examined the sexual scripts presented in women-dominated pornography abstinence communities. Our structural topic modeling analysis delineated the interplay of therapeutic, heteronormative, and empowerment themes that were evident in women’s narratives and expressions. Further, our discourse analysis elucidated three specific scripts: the addiction script, the heterosexual script, and the liberation script. These interweaving narratives show that discussions of women’s pornography abstinence are multifaceted and include a variety of perspectives to negotiate. These results contribute to a nuanced understanding of the values of health and well-being, sexual liberation, and feminism within women’s pornography abstinence communities.