YouTube Research Articles

Digital content on YouTube channels: A boon or bane to teaching and learning in medical education

Digital content on YouTube channels: A boon or bane to teaching and learning in medical education

Analyzing the Merits and Drawbacks of Multilingual Text Detection Datasets for Videos

In recent years, video contents have observed a massive growth with online lecture, news channels, and media contents and with short clips. These contents have objects, texts in them. The majority of the time, multilingual datasets are not available as per the need and have to utilize YouTube videos with multiple languages as a source . This study proposes a systematic structure for the generation of multilingual datasets and explains the purpose for their creation. Additionally, the study demonstrated the difficulties in creating the data set, like segregating data that is multilingual, etc. Lastly, discusses the effects of creating multilingual datasets because of various difficulties. As a result, the research's contribution is the multilingual dataset that was created using the suggested systematic structure, which also practically shows its limitations and benefits. Key Words:, Data Set, Multilingual, Text detection, challenge, consequences

Analysis of the Use of Social Media as a Promotional Tool to Attract Tourists in the Village of Belitar Sebarang

The study aims to analyze the use of social media as a promotional tool to attract tourists to visit Belitar Seberang Village, Rejang Lebong Regency, Bengkulu. Researchers use a descriptive qualitative approach with data collection techniques of interviews, observations, and documentation studies. Informants were selected through purposive sampling techniques with informant criteria, namely Seberang Village tourism managers, tourism village social media managers, and Seberang Village tour visitors. The data was analyzed using the Miles and Huberman technique. Then the results of the study were analyzed using Herbert Blumer Symbolic Interactionism Theory. The results showed that promotions were carried out on several social media platforms such as Instagram with the account name @desawisatabelitarseberang whose number of followers was 4,065 with several posts 216. Then Facebook Desa Wisata Belitar Seberang which has 835 followers, YouTube channel Desa Wisata Belitar Seberang with 223 subscribers, and Twitter @belirang which only has 4 followers. When viewed from the content uploaded, the number of posts per month is 4 to 5 content and with the number of likes that are also more than other platforms, reaching more than 25 likes per content. All data is taken as of October 16, 2023. Based on these data, it can be seen that Instagram is the platform with the most followers or followers. This means that Instagram is the most effective platform for promoting Sabrang Village tourism to attract tourists.

Expanding research impact through engaging the maker community and collaborating with digital content creators.

This paper proposes a method for increasing the impact of academic research by providing materials for public use, thus engaging the maker community, and by collaborating with internet content creators to extend the reach. We propose a framework for engagement and report a multi-year study that evaluates short, intermediate, and long-term outcomes, with a second effort to demonstrate repeatability of the short-term outcomes. In the first study, we posted forty-one 3D printable compliant mechanisms on public repositories and collaborated with physicist and content creator Derek Muller (Veritasium YouTube channel). Outputs and outcomes from this interaction were measured over 3 years. The framework was exercised again with four new 3D printable mechanisms in collaboration with engineer and STEM influencer Mark Rober. The proposed methods aim to help researchers extend the reach of their work to broader audiences, including professional engineers, hardware designers, educators, students, researchers, and hobbyists. This work demonstrates promising impacts of the framework, including (1) extending public awareness of research findings to broader audiences by engaging the maker community and collaborating with content creators, (2) accelerating the pace of innovation and further hardware-based research through public application of research findings, (3) fostering a culture of open-source design and collaboration among other researchers, engineers, educators, and makers, and (4) increasing utilization of peer-reviewed published content. These outreach practices can be valuable tools for researchers to increase impact of and excitement for their research.

Female-to-male (FtM) transgender individuals’ multimodal and interactional practices in Japanese

Abstract This study explores the multimodal and interactional practices of female-to-male (FtM) transgender individuals in Japanese, focusing on their identity construction. Most previous studies on transgender identity in Japanese contexts examine male-to-female (MtF) transgender individuals’ linguistic practices, particularly the use of so-called Japanese women’s language. In contrast, this study explores how FtM individuals use not only linguistic but also other semiotic resources to construct and negotiate their gender and sexual identities. The study utilizes empirical data such as YouTube videos and draws on multimodal conversation analysis (CA) and membership categorization analysis (MCA) to analyze the participants’ accomplishment of social actions. The findings demonstrate the use of various resources for identity construction and how the participants challenge and/or conform to hegemonic gender ideologies. The study also unveils both the diversity among FtM transgender people (inter-individual variation) and the fluidity and complexity of identities that can exist within one person (intra-individual variation).

Effectiveness of language-related Youtube videos on EFL learning motivation

YouTube is a widely popular platform that offers a vast array of video content. This study aimed to explore the elements of YouTube videos that contribute to sustaining learners’ motivation. A survey was conducted among 349 young adult Indonesian learners. Statistical data analysis revealed that three types of language-related YouTube videos—language lessons, language tips, and language immersions—significantly influenced learners’ motivation to study English. However, language immersion videos exhibited a modestly lower level of effectiveness compared to the other video types. Additionally, it was observed that non-native English-speaker (NNES) videos were more effective in maintaining motivation across all proficiency levels, except for advanced learners, who responded better to native English speaker (NES) videos. Furthermore, the study concluded that videos ranging from 5 to 15 minutes were more effective in sustaining learners’ motivation, as opposed to shorter or longer videos. These findings explain that teachers consider incorporating explicit instruction or tips in their content to enhance learners’ motivation. The findings also indicate that teachers and designers should utilize NNES videos for beginners and intermediate learners, while NES videos may be more effective for advanced learners. Lastly, when choosing instructional videos, the video length should be considered to ensure that learners remain motivated.

Online video resources pertaining to cerebral palsy: A YouTube-based quality control study

Online video resources pertaining to cerebral palsy: A YouTube-based quality control study

Characteristics, reliability, and quality of YouTube videos on meralgia paresthetica: a descriptive cross-sectional study.

The purpose of this study was to evaluate YouTube videos on meralgia paresthetica (MP) for reliability, quality, and differences between quality levels. We analyzed 59 videos related to MP. We evaluated several video characteristics, including views, likes, dislikes, duration, and speaker profile. We used view ratio, like ratio, Video Power Index (VPI), Global Quality Scale (GQS), JAMA criteria, and modified DISCERN (mDISCERN) to assess viewer engagement, popularity, educational quality, and reliability. The videos received a total of 4,009,141 views (average 67,951.54), with 25.4% focused on exercise training and 23.7% focused on disease information. Mean scores were mDISCERN 2.4, GQS 2.8, and JAMA 2.1. Physician-led videos had higher mDISCERN scores, while allied health worker-led videos had more views, likes, dislikes, view ratios, and VPI. Poor and high-quality videos differed in views, likes, view ratio, VPI, and duration. Positive correlations existed among mDISCERN, JAMA, and GQS scores, with video duration positively correlated with GQS. The content of YouTube videos discussing diseases significantly influences viewer engagement and popularity. To enhance the availability of valuable content on YouTube, which lacks a peer review process, medical professionals must contribute high-quality educational materials tailored to their target audience.

Assessment of the Quality of Sinus Elevation with Lateral Window Approach Procedure Videos on YouTube: A Content-quality Analysis.

Although the lateral window approach allows for greater graft material delivery and bone formation, it is more challenging and invasive, prompting keen interest among dentists to master this method. YouTube is increasingly used for medical training; however, concerns regarding the quality of instructional videos exist. This study proposes new criteria for evaluating YouTube videos on maxillary sinus elevation with the aim of establishing standards for assessing instructional content in the field. We sourced 100 maxillary sinus elevation videos from YouTube and, following exclusion criteria, analyzed 65 remaining videos. The video characteristics, content quality, and newly developed criteria were evaluated. Statistical analyses, employing ordinal logistic regression, identified the factors influencing the quality of instructional videos and evaluated the significance of our new criteria. Although video interaction and view rate exhibited positive relations to content quality, they were not significant (P=0.818 and 0.826, respectively). Notably, videos of fair and poor quality showed a significant negative relation (P<0.001). Audio commentary, written commentary, and descriptions of preoperative data displayed positive but statistically insignificant relationships (P=0.088, 0.228, and 0.612, respectively). The comparison of video evaluation results based on the developed criteria with content quality scores revealed significant negative relationships for good, fair, and poor videos (P<0.001, Exp(B)=-4.306, -7.853, -10.722, respectively). Among the various video characteristics, only image quality showed a significant relationship with content quality. Importantly, our newly developed criteria demonstrated a significant relationship with video content quality, providing valuable insights for assessing instructional videos on maxillary sinus elevation and laying the foundation for robust standards.

Transcript Summarizer For YouTube

The YouTube Transcript Summarizer is a web application. The application provides users with a simple interface to summarize the transcript of a YouTube video. Users can paste a YouTube video link into the application, which then extracts the video's transcript and generates a concise summary. The summary includes key points from the video, enabling users to quickly grasp the content without watching the entire video. This project aims to improve the efficiency of consuming YouTube video content by providing users with a convenient summarization tool. The system is integrated with existing YouTube interfaces, making it user-friendly and accessible to a wide range of users. Overall, the YouTube Transcript Summarizer aims to save time, improve comprehension, increase accessibility, and facilitate research for YouTube content consumers. The YouTube Transcript Summarizer is poised to make YouTube content more accessible, saving users time and providing an effective way to quickly evaluate the content of videos before investing their time in watching them. This tool can be a game-changer for content creators, researchers, students, and anyone seeking to extract valuable information from the vast YouTube library Keywords: Summarization, Efficiency, Time Saving, Accessibility, User-Friendly, Information Extraction

AI-Enhanced evaluation of YouTube content on post-surgical incontinence following pelvic cancer treatment

BackgroundSeveral pelvic area cancers exhibit high incidence rates, and their surgical treatment can result in adverse effects such as urinary and fecal incontinence, significantly impacting patients' quality of life. Post-surgery incontinence is a significant concern, with prevalence rates ranging from 25 to 45% for urinary incontinence and 9–68% for fecal incontinence. Cancer survivors are increasingly turning to YouTube as a platform to connect with others, yet caution is warranted as misinformation is prevalent. ObjectiveThis study aims to evaluate the information quality in YouTube videos about post-surgical incontinence after pelvic area cancer surgery. MethodsA YouTube search for "Incontinence after cancer surgery" yielded 108 videos, which were subsequently analyzed. To evaluate these videos, several quality assessment tools were utilized, including DISCERN, GQS, JAMA, PEMAT, and MQ-VET. Statistical analyses, such as descriptive statistics and intercorrelation tests, were employed to assess various video attributes, including characteristics, popularity, educational value, quality, and reliability. Also, artificial intelligence techniques like PCA, t-SNE, and UMAP were used for data analysis. HeatMap and Hierarchical Clustering Dendrogram techniques validated the Machine Learning results. ResultsThe quality scales presented a high level of correlation one with each other (p < 0.01) and the Artificial Intelligence-based techniques presented clear clustering representations of the dataset samples, which were reinforced by the Heat Map and Hierarchical Clustering Dendrogram. ConclusionsYouTube videos on "Incontinence after Cancer Surgery" present a "High" quality across multiple scales. The use of AI tools, like PCA, t-SNE, and UMAP, is highlighted for clustering large health datasets, improving data visualization, pattern recognition, and complex healthcare analysis.

The impact of deplatforming the far right: an analysis of YouTube and BitChute

ABSTRACT The content moderation practice of deplatforming, i.e., the removal of undesired actors, has become common on social media platforms such as YouTube. Our study aims to examine the impact of deplatforming on prominent far-right channels on YouTube. In our study, we are particularly interested in the deplatforming of prominent far-right channels such as Alex Jones, James Allsup, or Red Ice TV to understand the impact deplatforming has on them. To do so, we analyze two datasets: We check whether 11,198 YouTube channels have been removed in 22 months between 2018 and 2019 and for what reason. We then focus on the far right and check whether the deplatformed far-right channels have found a new home on the alternative video platform BitChute. The time frame for this study includes the removal of some critically important far-right figures. Our analysis shows that deplatforming effectively minimizes the reach of disinformation and extreme speech, as alternative platforms allowing this kind of content cannot mitigate the negative effect of being deplatformed on YouTube.

YouTube Videos Are a Moderately Comprehensive, Reliable, and Quality Option to Learn About “Multiple Sclerosis and Sexuality”

Objectives This study aimed to evaluate the performance, comprehensiveness, reliability, and quality of English-language YouTube videos addressing the subject of multiple sclerosis and sexuality. Methods In August 2023, a search was conducted on a computer using the keywords “multiple sclerosis and sexuality,” “multiple sclerosis and sexual health,” “multiple sclerosis and sexual health problems,” and “multiple sclerosis and sexual dysfunction” for this descriptive study. According to predetermined inclusion and exclusion criteria, 38 videos that met the research purpose were examined. The related URLs were recorded. For each video, the following information was collected: content producers, performance with YouTube statistics, comprehensiveness with a form developed by researchers, reliability with Singh’s Reliability Evaluation Form, and quality with Global Quality Scale. Two researchers independently evaluated the videos. Results Eighty-nine and a half percent of the videos contained information presented by professionals. The average number of views was 2699.132 ± 3382.848, the comprehensiveness score was 4.2 ± 1.711, the reliability score was 3.184 ± 1.182, and the quality score was 3.421 ± 1.2. Nearly half (42.2%) contained good and useful information for viewers, and half (50%) had high video quality. The reliability and quality scores of videos containing each item in terms of comprehensiveness were higher compared to videos that did not include that item (p < 0.05). In addition, the videos with higher comprehensiveness scores had higher quality and reliability scores (p < 0.001). Conclusion These results underscore the constrained performance attributes of YouTube videos addressing multiple sclerosis and sexuality, with their content exhibiting a moderate level of comprehensiveness, reliability, and quality. These results may provide a basis for increasing the effectiveness of YouTube videos on multiple sclerosis and sexuality.

The Reliability and Quality of YouTube Videos About Isotretinoin Treatment and Suicide.

Seeking health information online has drastically increased. Isotretinoin is one of the agents used to treat acne. In this study, we aimed to investigate the reliability and quality of YouTube videos related to acne treatment, which have been misconception to increase suicide. We used the terms "isotretinoin suicide" and "acne treatment suicide" to search YouTube videos. Videos that were not in English, irrelevant, or devoid of audio were not included. The information in the videos was primarily categorized as reliable or unreliable based on its scientific validation. DISCERN and the Global Quality Score were used to evaluate the videos' overall quality. 200 videos in total were examined. 112 videos were included in the study. 39 videos (34.8 %) were found to be reliable, and 73 videos (65.2%) were found to be unreliable. DISCERN values of videos uploaded by physicians or professional organizations and health information websites were found to be significantly higher. There was a statistically significant negative correlation between DISCERN score and video length and the length of time the video was on YOUTUBE, while a positive correlation was observed between DISCERN score and subscriber. Although videos created by dermatologists have become widespread in recent years, it is still insufficient. Patient experience videos mostly contain information which does not reflect the reality and emphasize that isotretinoin increases the risk of suicide without evidence. As the number of dermatologists posting videos on YouTube increases, the chances of people accessing correct information will increase.

Video Summarization for Marathi Language

The Video Summarization Platform using Python Flask is a comprehensive tool designed to summarize Marathi and English videos while providing summaries in Hindi, Marathi, and English languages. Leveraging machine learning and natural language processing (NLP) techniques, this platform offers a sophisticated solution for efficiently extracting key information from videos. The platform begins by transcribing the audio content of the video into text using automatic speech recognition (ASR) technology. This transcription process ensures that the platform can accurately analyze and summarize the video's content. Next, the text is translated into the target languages, namely Hindi, Marathi, and English, enabling users from diverse linguistic backgrounds to access the summarized content. To generate concise and informative summaries, advanced NLP algorithm is applied. This algorithm analyze the transcribed text to identify the most significant phrases, sentences, and concepts. By considering factors such as keyword frequency, semantic relevance, and context, the platform effectively distils the video's content into digestible summaries. Additionally, machine learning models are employed to classify the type of video content. These models are trained on diverse datasets encompassing various video genres and topics. By recognizing patterns and features within the video content, the platform can accurately categorize videos into distinct types, such as news, interviews, tutorials, or entertainment. The platform's user interface, powered by Python Flask, offers a seamless experience for users to upload videos, select their preferred language for summarization, and receive concise summaries in their chosen languages. The intuitive design ensures accessibility and ease of use, catering to both novice and advanced users. Overall, the Video Summarization Platform serves as a valuable resource for individuals seeking efficient ways to consume multimedia content. Whether for educational, informational, or entertainment purposes, this platform empowers users to access summarized video content in multiple languages, facilitated by cutting-edge machine learning and NLP technologies. Key Words: Transcription, Marathi-speaking users, Marathi YouTube videos, video content, transcription, summary, translation, Natural Language Toolkit (NLTK), content comprehension, user interaction data, past summaries, recommendation

Orthodontic Elastics: A Multivariable Analysis of YouTubeTM Videos.

Whether YouTube videos contain precise and adequate information on certain orthodontic procedures remains unclear. This study aimed to investigate the content and quality of YouTube videos on orthodontic elastics and identify the predictors of high-level content YouTube videos. Two hundred YouTube videos were screened for eligibility, and after applying the inclusion criteria, 133 videos were excluded. Student's t-test was used to compare the characteristics, quality parameters, and total content of the low-level and high-level content videos. Chi-square or Fisher's exact tests were implemented to identify the source and content element differences across low-level and high-level content videos. Pearson's correlation coefficients were used to determine the relationship between the total content score, video information and quality index (VIQI), and YouTube characteristics. Stepwise linear multiple regressions with forward selection were used to test the association of the YouTube characteristics and VIQI with the total content score. Among 67 included videos, only 19.4% of videos were classified as high-level content videos. High-level content videos had significantly higher mean number of likes (MD = 4041.7; SD = 4680.7; P-value=0.0068), VIQI score (MD = 4.17; SD = 4.87; P-value=0.0073), and total content score (MD = 4.04; SD = 1.23; P-value=<0.0001). The adjusted linear regression model demonstrated a significant association between the total content score and VIQI, where 1 unit increase in the VIQI was significantly associated with a 0.16 increase in the total content score (B = 0.16; standard error [SE]=0.04; P = 0.0003). Further, a significant association was observed between the total content score and video duration, where 1 minute increase in the video duration was significantly associated with a 0.15 increase in the total content score (B = 0.15; SE = 0.05; P = 0.008). This study demonstrated that YouTube content quality concerning orthodontic elastics is poor. Thus, future implementation of online visual content provided by certified orthodontists will ensure accurate and thorough information delivery.

ANALYSIS OF IMPOLITENESS COMMENTS OF NETIZEN ON NAJWA SHIHAB YOUTUBE CHANNEL

This study is entitled "Analysis of Impoliteness Comments of Netizens on Najwa Shihab YouTube Channel". This study aims to examine the types of impoliteness strategies used by netizens in speaking in the comments column of Najwa Shihab's YouTube channel on the show "Ganjar Pranowo Bicara Gagasan" based on Jonathan Culpeper’s theory. In this study, the research design used is a qualitative descriptive method to analyze the types of impoliteness strategies used by netizens in commenting on the comment section of Najwa Shihab's YouTube channel on the "Ganjar Pranowo Bicara Gagasan" video uploaded in September 2023. Data will be obtained from transcripts of printed materials related to incivility, with Culpeper's theory as the basis of analysis. The results of this study identified four types of impoliteness strategies from 100 comments studied contain impoliteness strategies on the video, the four categories of impoliteness identified include: Bald on Record Impoliteness (25%), Positive Impoliteness (22%) with Insukting Others (3%), Rejecting Similarities with the Listener (1%), Diverting Topics that are Sensitive or do not want to be Discussed (5%), Using Inappropriate Code (1%), Not Interested in Conversation (6%), Look For Differences Opinion (4%), and Using Unclear and Confidential Language (2%), negative impoliteness (26%), and Sarcasm or Mock impoliteness (27%), while Withhold Politeness is not found because it can only be found in oral speech. Based on the analysis, Sarcasm or Mock Impoliteness (27%) is the most dominant type of impoliteness strategy. From these findings, it can be concluded that Indonesian netizens often express meanings that are opposite to the words they actually say, which aims to criticize or make fun of their interlocutors in a subtle way.

A Conversation with Nadina Hassan

Abstract: In a video interview with Journal of Singing Associate Editor Melissa Treinkman on May 19, 2023, musical theatre performer Nadina Hassan discussed her career and her experience playing Regina George in the first national tour of Mean Girls . She described what it felt like to be a role model for young performers of color, revealed the challenges of life on tour, and expressed her appreciation for her singing teachers. A QR code is included at the end of the article which contains the link to the recorded interview with Nadina Hassan, posted on the NATS YouTube channel.

Pengembangan Video Pembelajaran Bahri (Berkalimah Tayibah Sehari-hari) Berbasis Renderforest tentang Kalimat Tayibah di Sekolah Dasar

Learning in the modern era comes with a lot of progress, many skills that must be possessed by students so as to make teachers more innovative in creating a learning climate, one of which is by utilizing technology in learning. However, the fact shows that most teachers, especially in learning PAI subjects in elementary schools, are still very minimal in involving technology as a learning medium for example learning videos, even though as a teacher should have knowledge and skills about the use of technology to create innovative and fun learning. Therefore, the research and development of Renderforest-based learning videos is expected to be able to help teachers in delivering kalimah tayibah material to grade 3 elementary school students more interestingly and fun so that students can easily understand the material and then students practice it in everyday life. The method used by the researcher is the ADDIE model D&amp;D method which is combined with a Students and teachers can access these learning videos on the YouTube app anytime and anywhere. The use of learning videos in the learning process can increase student motivation and create a fun learning experience.students. The research instruments used are interviews and assessment instruments which are then analyzed through the stages of data collection, data reduction, and data verification. BAHRI (Calimah Tayibah Everyday) learning videos in their use have been able to help teachers in a more interesting teaching process and trigger teachers to continue to innovate by utilizing technology in learning. Students and teachers can access these learning videos on the YouTube app anytime and anywhere. The use of learning videos in the learning process can increase student motivation and create a fun learning experience.

Celebrity and influencer philanthropy: Debating MrBeast and China

AbstractThis article examines the philanthropy/marketing interface with reference to celebrity philanthropy, focusing on the American YouTube star, MrBeast, and the Chinese government regulation of celebrities and social media influencers. Celebrity nowadays can refer to film and music stars with international broadcast media visibility and to people who create their own fame through social media and appeals to niche markets/audiences (social media influencers). While the United States of America has historically used tax incentives to encourage elite philanthropy as a matter of individual choice, the Chinese government is regulating the cultural industries to promote and direct celebrity and influencer philanthropy towards government‐endorsed development goals. Comparing debates about MrBeast philanthropy with the operation of philanthropy in China highlights different ideas about celebrity/influencer philanthropy and the role it can play in supporting public welfare.