Comprehensive Content Research Articles

An Analysis of Primary School Classroom Teaching Evaluation Strategies Based on Chinese Core Literacy

As an important part of primary school Chinese education activities, the evaluation form of primary school Chinese classroom teaching determines the effect of Chinese teaching to a large extent. In response to the problems in the current Chinese classroom teaching evaluation, this paper explores the evaluation of Chinese classroom teaching from the starting point of Chinese core literacy, and proposes to use language construction and application literacy, thinking development and improvement literacy, aesthetic appreciation and creative literacy, cultural inheritance and understanding literacy as evaluation guidelines. It explores the primary school Chinese curriculum teaching evaluation strategy from the aspects of comprehensive evaluation content, diversified evaluation subjects, and standardized evaluation indicators, so as to give full play to the effectiveness of Chinese classroom teaching evaluation and improve primary school students' Chinese core literacy.

The Cultural and Social Impact of Poet Pattukottai Kalyanasundaram's Lyrics in Tamil Cinema: A Hermeneutic Analysis

Music and songs have long been integral to Tamil culture, particularly in the realm of cinema. Tamil film song lyrics, a significant component of mass communication and entertainment in the twentieth century, have captivated audiences with their narratives and melodies. Among the eminent lyricists in Tamil cinema history, Pattukottai Kalyanasundaram (13 April 1930 – 8 October 1959), known as "Makkal Kavingnar", stands out as an iconic figure. His profound impact on global Tamil communities through his cinematic compositions is widely acknowledged. Kalyanasundaram's lyrics not only entertained but also conveyed powerful social messages, encompassing diverse facets of human life. This paper is considered to be the first to explore Poet Kalyanasundaram (“Siruvar Seerthirutham, Arasiyal Aram, Naatu Nalam”) in English, although several articles have been written in the Tamil language. Employing hermeneutics as a qualitative research methodology, the study conducts a comprehensive content analysis of his songs, revealing thematic insights relevant to personal development and cultural enrichment.

Enron’s Collapse and the Emergence of a New Magnitude of Ethics within Corporate Governance

In this study, it is argued that the collapse of a single company – Enron – in the USA represented one of the most crucial factors underlying the emergence of ethics with a new dimension in the global business strategy. Enron, one of the most profitable companies in the USA in 1990s, experienced a completely unprecedented disaster and the ensuing investigations revealed that a lack of ethical integrity among the high officials was one of the most crucial reasons for the downfall of such an established company. Shortly after Enron collapse, a number of companies in different countries faced similar consequences and a crucial factor that they all appeared to share was unethical practices. The core aim of this study is to explore how the think-tanks in the corporate world made a quick response regarding the development of the ethical practices within the activities of corporations and how ethics gained greater magnitude within the administration of business activities. To achieve this aim, we undertook a comprehensive content analysis of the relevant secondary data substantiated by a Focus Group Discussion (FGD) attended by academics working in the field of corporate governance, in order to gain relevant insights in the study objectives. The scholarly views of the individuals who participated in the FGD, we believe, can add value to our results by enriching the study. The study findings suggest that the downfall of Enron immediately and hugely contributed towards raising the profile of ethics and the introduction of a series of ethical codes regarding corporate performances.

Advancing automatic text summarization: Unleashing enhanced binary multi-objective grey wolf optimization with mutation.

Automatic Text Summarization (ATS) is gaining popularity as there is a growing demand for a system capable of processing extensive textual content and delivering a concise, yet meaningful, relevant, and useful summary. Manual summarization is both expensive and time-consuming, making it impractical for humans to handle vast amounts of data. Consequently, the need for ATS systems has become evident. These systems encounter challenges such as ensuring comprehensive content coverage, determining the appropriate length of the summary, addressing redundancy, and maintaining coherence in the generated summary. Researchers are actively addressing these challenges by employing Natural Language Processing (NLP) techniques. While traditional methods exist for generating summaries, they often fall short of addressing multiple aspects simultaneously. To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. The performance of this enhanced algorithm is assessed by comparing it with state-of-the-art algorithms using the DUC2002 dataset. Experimental results demonstrate that the proposed algorithm significantly outperforms the compared approaches.

Content Analysis Of Textbook Evaluation: Assessing Everyday English For Hospitality Professionals

This study conducts a comprehensive content analysis of the textbook titled "Everyday English for Hospitality Professionals". Through the lens of textbook evaluation, the research aims to assess the effectiveness and suitability of the content in meeting the learning needs of professionals in the hospitality industry. Utilizing established criteria, the analysis scrutinizes the relevance, clarity, and practicality of the material, particularly in facilitating language skill development tailored to the demands of the hospitality profession. The findings of this study offer valuable insights for curriculum development and instructional material selection, contributing to the enhancement of English language learning experiences for hospitality professionals.

Analysis and Improvement Strategies of Gansu Youth League Official Short Video Content from the Perspective of Recognition

How to enhance the recognition of new media Official Short Videos among users? This paper selects the Douyin account of the Youth League of Gansu Province for analysis. Based on the literature on evaluating the effectiveness of communication of short videos, this article has developed a model for measuring video identity, and provided content analysis for the 9% of Gansu Youth League members with the highest degree of identity using this model. In the research, this article found that video materials tend to be official and original videos, and tends to focus on comprehensive organization, local content, and positive emotions. High quality video content in the form of video, plus the popular sound effect of only music, and videos with tags to participate in topics or Douyin challenges that last between 1 and 15 seconds, have the greatest chance of gaining user recognition. At the same time, official video sources, original videos, and videos from local sources have the highest correlation with recognition. Therefore, this article believes that in order to gain recognition for future Official Short Videos, more efforts should be made in these three aspects.

Summary of best evidence for rehabilitation management of patients with motor dysfunction after stroke.

The rehabilitation work for patients with motor dysfunction after stroke is crucial. However, there is currently a lack of summarized evidence regarding the rehabilitation management of stroke patients in rehabilitation wards, communities, and at home. This study aims to compile relevant evidence on the rehabilitation management of patients with motor dysfunction after stroke, providing a reference for clinical and community health professionals to carry out rehabilitation interventions. A systematic search was conducted in BMJ Best Practice, UpToDate, National Guidebook Clearinghouse, American Heart Association/American Stroke Association, Canadian Medical Association, National Institute for Health and Clinical Excellence, United States Department of Veterans Affairs/ Department of Defense, Registered Nurses Association of Ontario, JBI Evidence-Based Healthcare Center Database, The Cochrane Library, PubMed, Web of Science, Embase, CINAHL, CNKI, Wanfang Database, SinoMed, and other databases for all literature on the rehabilitation management of patients with motor dysfunction after stroke. This included clinical decision-making, guidelines, expert consensuses, recommended practices, systematic reviews, and evidence summaries, with the search period spanning from the establishment of each database to October 2023. Two researchers independently evaluated the quality of the literature. A total of twenty-one documents were included, consisting of 11 guidelines, 2 expert consensus, and 8 systematic reviews. Evidence was extracted and integrated from the included literature, summarizing forty-five pieces of evidence across nine areas: rehabilitation management model, rehabilitation institutions, rehabilitation teams, timing of rehabilitation interventions, rehabilitation assessment, rehabilitation programs, rehabilitation duration and frequency, rehabilitation intensity, and rehabilitation support These covered comprehensive rehabilitation management content for stroke patients in the early, subacute, and chronic phases. The best evidence summarized in this study for the rehabilitation management of patients with motor dysfunction after stroke is comprehensive and of high quality. It provides important guidance for clinical and community healthcare professionals in carrying out rehabilitation interventions. When applying the evidence, it is recommended to consider the current condition of the stroke patient, the extent of motor dysfunction, environmental factors, and the patient's preferences. Then, select the most appropriate rehabilitation plan, and adjust the type and intensity of training according to each patient's specific needs and preferences.

Nyerere’s Philosophy of Education for Self-Reliance and Its Implications for Enhancing the Socio-Economic Dimension of Current Kenyan University Education

While considerable attention has been devoted to exploring the potential of higher education in driving economic development, comparatively less focus has been directed towards its role in nurturing social imperatives associated with education. In the same vein, the economic benefits of a university degree in Kenya have been emphasised, while the social relevance of serving society has not received enough attention. In order to strengthen the social and economic paradigms of higher education in Kenya, the article examine the unique contribution of Nyerere's philosophy of education for self-reliance in the realm of African educational philosophies. The purpose of this study was to analyse what educational implications Kenyan universities can adopt from Nyerere's education for self-reliance philosophy using a literature-based research approach. The methodology of the study used was a multifaceted technique that comprised a literature review, conceptual analysis, a comprehensive content analysis and triangulation for evaluating relevant books, research studies, scholarly works and official papers about the socio-economic role of university education and Nyerere's philosophy of education. The study's findings indicated that the Nyerere educational philosophy, which is characterized by its invaluable lessons on the roles of the teacher, curriculum development, and the purpose of university education, may have beneficial implications on Kenyan university education. The socio-economic dimensions of university education emphasize enhancing society through problem-solving, community engagement, and career-oriented learning. The study also underscored the vital need for training for jobs in both white-collar and blue-collar fields by universities, the incorporation of problem-solving skills relevant to the 21st century, on-going professional development, and benchmarking. These recommendations could be the cornerstone of socio-economic education reforms at Kenyan universities, which could prepare its youth for the dynamic opportunities of the twenty-first century, positioning Kenya as a forerunner in the global advancement of socio-economic dimension of university education.

An Android Application on EduConnect

EduConnect is an Android application designed to bridge the gap between traditional learning methods and the convenience of mobile technology. It empowers students by providing them with a centralized platform to access essential academic resources, including syllabuses, notes, and question papers. This research paper delves into the functionalities, potential benefits, and considerations for the EduConnect application. Findings indicate that EduConnect positively influences students' study habits and academic performance by providing convenient access to syllabi, notes, and question papers. Users appreciate the platform's user-friendly interface, comprehensive content repository, and collaborative features for sharing study materials. However, challenges such as content quality, relevance, and platform stability are identified as areas for improvement. Overall, this research contributes to the understanding of how mobile applications can support and augment educational experiences in the digital era. Insights gleaned from this study can inform the design and development of future iterations of EduConnect, as well as similar educational technology solutions, to better meet the evolving needs of students and educators in the modern learning landscape

AGILE WORK CULTURES IN IT: A CONCEPTUAL ANALYSIS OF HR'S ROLE IN FOSTERING INNOVATION SUPPLY CHAIN

This study systematically examines the role of Human Resources (HR) in fostering agile work cultures within the Information Technology (IT) sector, with a focus on enhancing the innovation supply chain. Through a comprehensive literature review and content analysis, this research explores how HR practices can support and drive the adoption of agile methodologies, thereby contributing to organizational flexibility, innovation, and competitive advantage. The methodology involved sourcing data from academic databases and grey literature, employing a strategic search strategy, and applying strict inclusion and exclusion criteria to identify relevant literature. The analysis highlighted the critical role of HR in developing agile leadership, fostering a culture of continuous learning and psychological safety, and leveraging HR technologies to enhance workforce agility. Key findings reveal that HR's strategic interventions in leadership development, learning and development frameworks, and the promotion of agile team dynamics are essential in cultivating an agile work culture. Furthermore, the study anticipates future challenges and opportunities in agile work cultures, including the integration of remote work models, artificial intelligence, and ensuring diversity and inclusion. Strategic recommendations for HR leaders and IT executives emphasize the importance of investing in agile leadership, enhancing team dynamics, and promoting a culture of continuous improvement. Finally, the study underscores the pivotal role of HR in enabling agile transformations within IT sectors. Future research directions include exploring the impact of emerging technologies on agile methodologies and the role of HR in fostering inclusive and diverse agile teams. This research contributes to the understanding of how agile practices supported by HR innovations can drive organizational success in the rapidly evolving digital landscape.
 Keywords: Agile Work Cultures, Human Resources (HR), Information Technology (IT) Innovation, Agile Leadership Development.

Educators’ Academic Insights on Artificial Intelligence: Challenges and Opportunities

The study on " Educators’ Academic Insights on Artificial Intelligence – Challenges and Opportunities" was conducted to gain a deeper understanding of the rapidly evolving phenomenon of AI in education. This research serves multiple objectives. Firstly, it aims to foster awareness regarding the integration of AI into teaching and learning practices by providing clear definitions of AI and explaining key AI-related terms. It also seeks to illustrate AI's diverse applications within a broader context, with a special focus on AI-supported research and learning platforms. Additionally, the study delves into the current discourse surrounding chatbots, contributing to address the central research question. Lastly, this initiative aims to provide valuable recommendations for effectively harnessing AI in education, enhancing the teaching and learning experience. The researchers conducted a review of literature concerning artificial intelligence. They adopted a qualitative method, using open-ended questions to collect feedback from educators globally, including those from the University of Technology and Applied Sciences, Al Musannah, and participants in the online discussion forum at Oxford English Learning Exchange.com. The qualitative data was analysed, leading to the identification of key themes and subthemes derived from the responses of research participants. The study's findings incorporated a wide range of concerns expressed by educators, comprising ten key subthemes. These concerns ranged from doubts about AI's ability to replace human educators and fears of its potential to hinder student development to worries about its hyped popularity and its perceived futuristic nature. Educators stressed the importance of effective AI training while emphasizing the need to prioritize human expertise over excessive reliance on AI. They were also acutely aware of both the advantages and disadvantages of AI, viewing it as both a potential boon and a looming threat. Furthermore, educators recognized the potential for enjoyable experiences with AI and acknowledged the pivotal role of users in determining the extent of AI adoption. Content analysis revealed additional apprehensions, such as concerns about job displacement, AI's impact on critical thinking, teacher frustration in assessing AI-assisted student writing, the use of AI-generated content for assessments, potential erosion of human services, stifling of user and learner creativity by AI, the risk of errors in AI-generated information, opportunities for cheating in exams, and concerns about the overreliance on and overrating of AI platforms. Positively, the findings included an array of opportunities that AI platforms offer. Study participants highlighted various aspects of these opportunities that surpassed their concerns and associated risks. The opportunities are categorized into twenty subthemes: enhancing learner motivation, facilitating template creation, utilizing AI as an educational aid, promoting proper training and fostering positive AI usage, harnessing AI for teaching challenging subjects, enabling personalized learning experiences, offering an interactive tutoring experience, supporting remote learning, facilitating self-study, providing comprehensive educational content overviews, giving instantaneous feedback and evaluation, functioning as search engines and chatbots, enabling content validation, efficiency in terms of cost and time, streamlining material preparation, facilitating skill and language enhancement, promoting familiarity with topics and vocabulary, enabling text-to-speech and speech-to-text conversions, editing multimedia elements, and facilitating content generation.

Selection of Spectral Parameters and Optimization of Estimation Models for Soil Total Nitrogen Content during Fertilization Period in Apple Orchards

The rapid and accurate diagnosis of nitrogen content in apple orchard soil is of great significance for the rational application of nitrogen fertilizer in orchards to improve apple yield and quality. An apple orchard in Shuangquan Town, Changqing District, Jinan City, Shandong Province, was taken as the experimental area. The optimal method for extracting spectral characteristic bands and screening spectral characteristic indices (SCIs) of soil total nitrogen (TN) for independent and comprehensive fertilization periods was explored. Independent and comprehensive soil TN content estimation models were constructed and optimized for each and the entire fertilization period, respectively. The results show that compared with the correlation coefficient method, stepwise multiple linear regression (SMLR) performs better in extracting hyperspectral characteristic bands of soil TN content. It helps to achieve a higher modeling accuracy, smaller root mean square error (RMSE), and is more conducive to avoiding the influence of multicollinearity of model variables. The sensitive areas of soil TN content in the SCI do not undergo significant changes due to different fertilization periods. Among them, the ratio spectral indices (RSIs) are in the range of 800–900 nm, 1900–1950 nm, and 2200–2300 nm, while the sensitive areas of the difference spectral index (DI) and Normalized difference spectral index (NDSI) are in the range of 1900–1950 nm and 2200–2300 nm. The combination of SCI and characteristic bands significantly improves the prediction accuracy of soil TN estimation models. The independent and comprehensive estimation models for each fertilization period based on the BP (back propagation) neural network optimized by the Mind Evolution Algorithm (MEA-BPNN) can achieve a more stable and accurate estimation of soil TN. Finally, using soil spectral characteristic bands selected through continuum removal (CR) transformation and SMLR, combined with SCI, the model based on the MEA-BPNN (CR-SCI-MEA-BPNN) has the best prediction performance. The modeling determination coefficients R2 for each fertilization period reached 0.94, 0.95, 0.92, and 0.94, respectively, with RMSE of 0.0032, 0.0024, 0.0035, and 0.0027. The R2 and RMSE of the modeling and validation set of the entire fertilization period comprehensive model are 0.899, 0.0038, and 0.89, 0.0041, respectively. The results of this article provide technical support for promoting the timely monitoring of soil TN content and guiding rational fertilization in apple orchards.

A big little fiction form: last decade of production and circulation of made-for-TV movies in Europe

ABSTRACT Made-for-television movies, originating as popular television forms in the 1960s, have historically received scant scholarly attention and faced persistent devaluation within the film industry. However, the contemporary landscape witnesses a resurgence in interest, catalyzed by the focus of VOD services on long-form fiction tailored for streaming, commonly referred to as “originals.” This paper conducts a retrospective examination of the past decade, scrutinizing the presence of made-for-television movies within general television and accentuating their intrinsic value by investigating intra-European circulation flows. Through comprehensive content analysis of general-interest channel schedules in five prominent European countries, this study explores the nuances of production, circulation dynamics, and the influence of public corporations in this scenario. The findings reveal distinctive circulation patterns characterized by continual European exchanges, setting made-for-TV movies apart from TV series, particularly on public channels. Notably, a select cluster of large European countries emerges as pivotal players dominating these intra-European flows.

A comprehensive bibliometric and content analysis of artificial intelligence in language learning: tracing between the years 2017 and 2023

The rising pervasiveness of Artificial Intelligence (AI) has led applied linguists to combine it with language teaching and learning processes. In many cases, such implementation has significantly contributed to the field. The retrospective amount of literature dedicated on the use of AI in language learning (LL) is overwhelming. Thus, the objective of this paper is to map the existing literature on Artificial Intelligence in language learning through bibliometric and content analysis. From the Scopus database, we systematically explored, after keyword refinement, the prevailing literature of AI in LL. After excluding irrelevant articles, we conducted our study with 606 documents published between 2017 and 2023 for further investigation. This review reinforces our understanding by identifying and distilling the relationships between the content, the contributions, and the contributors. The findings of the study show a rising pattern of AI in LL. Along with the metrics of performance analysis, through VOSviewer and R studio (Biblioshiny), our findings uncovered the influential authors, institutions, countries, and the most influential documents in the field. Moreover, we identified 7 clusters and potential areas of related research through keyword analysis. In addition to the bibliographic details, this review aims to elucidate the content of the field. NVivo 14 and Atlas AI were used to perform content analysis to categorize and present the type of AI used in language learning, Language learning factors, and its participants.

Sensitive and Obscene Content Blocker (SOCB)

Abstract: In today’s digital age, the internet is a vast and diverse platform that offers a wealth of information and entertainment. However, this openness also exposes users to sensitive and obscene content, which can have a detrimental impact on individuals, particularly children and vulnerable populations. To mitigate the exposure to such content, a Sensitive and Obscene Content Blocker has been developed and tested. This paper explores the design, development, and evaluation of a comprehensive content filtering system that is aimed at identifying and blocking sensitive and obscene content across various online platforms. The system employs advanced algorithms, machine learning techniques, and real-time content analysis to ensure a reliable and robust filtering mechanism. The paper outlines the key components of the blocker, including content analysis methods, their detection and classification methods. The study presents the results of extensive testing, demonstrating the system’s efficiency in blocking inappropriate content while minimizing false positives. The Sensitive and Obscene Content Blocker serves as a powerful tool to protect individuals from harmful online content, promoting a safer and more secure digital environment. This paper provides valuable insights into the development and implementation of content blockers and their role in enhancing online safety and security.

Analyzing the Portrayal of Political Leadership in Leading Pakistani News Channels : A Critical Analysis

This study focuses on the framing theory as a lens to analyze the coverage and frames of political parties by two prominent news channels, Dunya News and Geo News. A comprehensive content analysis spanning over three months was conducted to assess the frequency, story types, frames, and tone of news coverage related to political leaders from 1st Sep 2023 to 20th Dec 2023 through purposive sampling. For this purpose, five themes, party manifesto, and plans, leader’s character, past performance of the party, voting worth, bias, and victimization were designed to explore the study’s objectives. The findings indicate a notable disparity in the salience given to political parties, with both news channels showing a higher emphasis on PMLN compared to PTI and PPP. Furthermore, the results reveal that Nawaz Sharif, received more favorable coverage from both news channels, followed by Imran Khan. Bilawal Bhutto Zardari receives comparable coverage to Imran Khan on Dunya News but notably less on Geo News. Additionally, the majority of the stance from these news channels leans in favor of PMLN leader Nawaz Sharif, while PTI leader Imran Khan tends to receive a more negative stance across both channels. A frames-wise analysis uncovers that Dunya News provides a more diverse range of perspectives when portraying political leaders, encompassing frames such as party manifesto, party previous performance, and voting worth, in contrast to Geo News, which maintains a more consistent distribution of emphasis across different frames. Findings also revealed that Nawaz Sharif’s frames prominently centered on the manifesto category. On the other hand, Imran Khan received coverage under the attributes of leaders’ character while party performance was a common attribute covered related to politicians.

Experimental investigation on thermal modification and burnout of residual carbon in coal gasification fine slag

Disposal of coal gasification fine slag (CGFS) has caused environmental pollution and resource waste. Its decarbonization is the bottleneck of aluminum and silicon resource utilization. A fluidization-melting combustion system is proposed in this study to realize the decarbonization. The fluidized thermal modification and burnout characters of residual carbon in CGFS were investigated experimentally on a bench-scale test rig. A two-stage decarburization path of CGFS was concluded and verified. The fluidized modification of CGFS is first conducted to decrease the particle size and improve the specific surface area and combustion reactivity. So, the modified exposed carbon in CGFS rapidly burns in the melting furnace to generate the condition above the fluid temperature of minerals. Then the mineral shell of the amorphous mineral covered carbon in CGFS is molten and damaged, and the carbon appears and burns out. The decrease in the thermal modification temperature induced deceases in melting combustion temperature and decarbonization efficiency. Efficient decarbonization of CGFS produced by three different entrained bed gasifiers was realized by the fluidization-melting combustion, the decarburization efficiencies are all above 95% and the comprehensive carbon contents of ash and slag are all below 5%.

The Quality of COVID-19 Coverage: Investigating Relevance and Viewpoint Diversity in German Mainstream and Alternative Media

ABSTRACT The COVID-19 pandemic was a major challenge for journalism. In the case of Germany, critics very early on voiced concerns over the quality of mainstream media coverage. Mainstream media were attacked for the intensity of their coverage, for reporting too much and unnecessarily frightening audiences, for not presenting a diversity of viewpoints on the pandemic and the measures taken to mitigate it, and for being one-sided and too close to the government. Against this background, this paper examines the intensity and viewpoint diversity of the coverage of 13 mainstream and two alternative media in Germany in 2020 and 2021. Based on a comprehensive manual content analysis of almost 9000 news stories, we conclude that the mainstream media did not cover the pandemic in a fundamentally exaggerated or one-sided way. However, they did not always report intensively when the pandemic was particularly severe, and they tended to warn against the pandemic rather than criticize the measures taken. In contrast, alternative media coverage tended to be more one-sided and generally biased against government measures.

ChatGPT revisited: Using ChatGPT-4 for finding references and editing language in medical scientific articles

The attainment of academic superiority relies heavily upon the accessibility of scholarly resources and the expression of research findings through faultless language usage. Although modern tools, such as the Publish or Perish software program, are proficient in sourcing academic papers based on specific keywords, they often fall short of extracting comprehensive content, including crucial references. The challenge of linguistic precision remains a prominent issue, particularly for research papers composed by non-native English speakers who may encounter word usage errors. This manuscript serves a twofold purpose: firstly, it reassesses the effectiveness of ChatGPT-4 in the context of retrieving pertinent references tailored to specific research topics. Secondly, it introduces a suite of language editing services that are skilled in rectifying word usage errors, ensuring the refined presentation of research outcomes. The article also provides practical guidelines for formulating precise queries to mitigate the risks of erroneous language usage and the inclusion of spurious references. In the ever-evolving realm of academic discourse, leveraging the potential of advanced AI, such as ChatGPT-4, can significantly enhance the quality and impact of scientific publications.

“Anxiety is not cute” analysis of twitter users’ discourses on romanticizing mental illness

BackgroundThe proliferation of social media platforms has provided a unique space for discourse on mental health, originally intended to destigmatize mental illness. However, recent discourses on these platforms have shown a concerning shift towards the romanticization of mental health issues. This research focuses on Twitter (now called X) users’ authentic discussions on the phenomenon of romanticizing mental health, aiming to uncover unique perspectives, themes, and language used by users when engaging with this complex topic.MethodsA comprehensive content analysis was conducted on 600 relevant tweets, with the application of topic modeling techniques. This methodology allowed for the identification and exploration of six primary themes that emerged from Twitter users’ discussions. Statistical tests were not applied in this qualitative analysis.ResultsThe study identified six primary themes resulting from Twitter users’ discussions on the romanticization of mental health. These themes include rejecting/critiquing the glamorization of mental health, monetization of mental health by corporate organizations, societal misconceptions of mental health, the role of traditional media and social media, unfiltered realities of depression, and the emphasis on not romanticizing mental health.ConclusionsThis study provides valuable insights into the multifaceted discourses surrounding the romanticization of mental health on Twitter. It highlights users’ critiques, concerns, and calls for change, emphasizing the potential harm caused by romanticizing mental illness. The findings underscore the importance of fostering responsible and empathetic discussions about mental health on social media platforms. By examining how Twitter users interact with and respond to the romanticization of mental health, this research advances our understanding of emerging perspectives on mental health issues among social media users, particularly young adolescents. The study also underscores the effects of this phenomenon on individuals, society, and the mental health community. Overall, this research emphasizes the need for more responsible and knowledgeable discussions around mental health in the digital age.