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89 results for “YouTube”
Survei Penggunaan Youtube sebagai Sarana Pembelajaran Daring
<p>Dataset survei Pengguna Youtube</p>
Figure 1 from: Olivero P, Robillard T (2017) Same-sex sexual behavior in Xenogryllus marmoratus (Haan, 1844) (Grylloidea: Gryllidae: Eneopterinae): Observation in the wild from YouTube. Journal of Orthoptera Research 26: 1-5. https://doi.org/10.3897/jor.26.14569
Figure 1 - Screenshots of the video showing same-sex sexual behavior between males of Xenogryllus marmoratus (Haan, 1844). For details, see the results section.
Figure 1 from: Olivero P, Robillard T (2017) Same-sex sexual behavior in Xenogryllus marmoratus (Haan, 1844) (Grylloidea: Gryllidae: Eneopterinae): Observation in the wild from YouTube. Journal of Orthoptera Research 26: 1-5. https://doi.org/10.3897/jor.26.14569
Figure 1 - Screenshots of the video showing same-sex sexual behavior between males of Xenogryllus marmoratus (Haan, 1844). For details, see the results section.
Initial delay dataset YouTube mobile app
<p>Dataset for researchers</p>
The content and quality of YouTube videos relating to interproximal reduction
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Poster_YouTube_as_Source_of_Open_Data_for_Traffic_Safety_Research
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Penerapan Latent Dirichlet Allocation dalam Analisis Konten Memasak pada Youtube Indonesia
<p>Youtube is a platform used to share videos. Since its founding in 2005, to date there are more than 20 million active users with 2 million videos uploaded every day. This is inseparable from the contribution of Indonesian content creators who also share videos with various types of content. One type of content that is loved by the Indonesian people is content about cooking or culinary belonging to food vloggers. In this study, the author wants to know what are the dominant topics related to the type of content created by food vloggers on their Youtube channel. This study uses the Latent Dirichlet Allocation (LDA) method. The research began by conducting text mining experiments on 3846 videos from the Youtube channel of nine food vloggers with more than one million subscribers. Then the LDA method is applied which is then analyzed to determine the optimal number of topics of content types by looking at the perplexity and topic coherence values. As a result, there are 5 topics of content types that often appear in videos belonging to food vloggers. Topics of this type of content include tips for making economical cakes, ingredients for making oven cakes, food business ideas, the process of cooking viral dishes, and easily available ingredients for making snacks.</p>
Improving Patient Understanding of the Surgical Hospital Experience: Use of YouTube Video Playlist
ClinicalTrials.gov study NCT02546180. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Data from: A systematic review of methods for studying consumer health YouTube videos, with implications for systematic reviews
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AGECovP: Identifying Ageism and Analyzing COVID-19 Discourse on Older Adults in YouTube
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YouTube Dataset of Arabic Learners' Discussions
<p>The dataset contains a large collection of comments extracted from various YouTube videos teaching Arabic. It is presented in an Excel format and consists of a single sheet with four columns: YouTube_URL, Views, Comment, and Label. The comments are labeled as follows: ArText for Arabic text, EngText for English text, NotEngNorAr for languages other than English or Arabic, and ArzText for Arabic words or phrases written in English characters. Researchers can identify patterns and trends in learners' engagement with educational videos. Additionally, this dataset can also be used to examine and experiment in the fields of Natural Language Processing and automated language-related tasks.<strong> </strong></p>
Supplementary material to 'Automatic Identification of Hate Speech – A Case-Study of Alt-Right YouTube Videos'
<p>The associated files have been created for and is analysed in a fortcoming article entitled <em>Automatic Identification of Hate Speech – A Case-Study of Alt-Right YouTube Videos'. </em>The material is divided into six tables as follows:</p> <table> <tbody> <tr> <td>Sentence top 5%</td> <td>The 19th 20-quantile predicted most hateful sentences</td> </tr> <tr> <td>Sentence bottom 5%</td> <td>The bottom 20-quantile predicted moste hatefull sentences (the least likely to contain hatespeech)</td> </tr> <tr> <td>Paragraphs</td> <td>Prediction and annotation of paragraphs</td> </tr> <tr> <td>Video top 10%</td> <td>Titles of the top decile predicted hateful videos</td> </tr> <tr> <td>Video bottom 10%</td> <td>Titles of the bottom decile predicted hateful videos</td> </tr> <tr> <td>Video bottom 10% - Alt right</td> <td>Titles of the bottom decile predicted hateful videos without History</td> </tr> </tbody> </table> <p>The data is uploaded in two formats:</p> <p><strong>Excel file: </strong>Automatic_Detection_of_Hate_Speech_a_Case-Study_of_Alt-Right_Videos.xlsx contains all six tables in one file, with a supplementary <em>codebook. </em></p> <p><strong>Tab Separated Values (TSV):</strong> Each file correspond to a single sheet from the excel file, and are named accordingly. UTF-8 Encoded.<strong><br></strong></p>
Reliability and usefulness of YouTube videos for information on penile prothesis
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Dataset of YouTube Comments on Prophet Muhammad's Lineage and the Ba Alawi Debate
<p>This dataset contains 4,000 YouTube comments collected from various videos discussing the theme of Prophet Muhammad's lineage and claims of descent related to the Ba Alawi debate. The data were gathered using the Apify YouTube Comments Scraper (<a href="https://apify.com/streamers/youtube-comments-scraper" target="_new" rel="noopener">https://apify.com/streamers/youtube-comments-scraper</a>). The comments, written in <strong>Indonesian</strong>, were extracted from videos uploaded by channels such as BILAL Channel, Panji Islam, KAJIAN SURGA OFFICIAL, and others. Metadata includes the comment text, anonymized username, publication date, and number of likes. The dataset underwent a cleaning process to remove duplicates, correct errors, and ensure data consistency. This dataset is suitable for critical discourse analysis or studies focusing on digital interactions in religious debates within the Indonesian context.</p>
x264 and x265 performance on eight videos of the Youtube UGC Dataset
<p>The measurements of 3125 configurations of two video encoders, namely <a href="https://www.videolan.org/developers/x264.html">x264</a> and <a href="https://www.videolan.org/developers/x265.html">x265</a>, on eight different videos of the <a href="https://media.withyoutube.com/">Youtube UGC Dataset</a></p>
YouTube data for "Early Prediction of the Future Popularity of Uploaded Videos"
<p>This file contains the YouTube data for "Early Prediction of the Future Popularity of Uploaded Videos" by Chen and Chang. Please refer to this study for the definition and description of the data.</p>
A popularização do conhecimento científico no Youtube é tema de pesquisa na UFSCar
<p>Felipe Adriano Alves de Oliveira, mestrando do Programa de Pós-Graduação em Ciência, Tecnologia e Sociedade da Universidade Federal de São Carlos (PPGCTS - UFSCar), fala de sua pesquisa a respeito da comunicação pública da ciência, a partir da análise de conteúdo do canal Nerdologia. Lattes: http://lattes.cnpq.br/3394354224029536</p> <p> </p> <p>A popularização do conhecimento científico no Youtube é tema de pesquisa na UFSCar de <a href="https://youtu.be/a3a8YnuB-Ps">https://youtu.be/a3a8YnuB-Ps</a> está licenciado com uma Licença <a href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons - Atribuição-NãoComercial-SemDerivações 4.0 Internacional</a>.<br> Podem estar disponíveis autorizações adicionais às concedidas no âmbito desta licença em <a href="https://www.labi.ufscar.br/">https://www.labi.ufscar.br/</a>.</p>
Using YouTube to Learn Anatomy: Perspectives of Mexican Medical Students
ClinicalTrials.gov study NCT05852834. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
A YouTube Curriculum for Children With Autism and Obesity
ClinicalTrials.gov study NCT06259539. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Artificial Intelligence in Healthcare: Advanced Evaluation of Medical Online Content. AI-driven Quality Assessment of YouTube Videos Providing Information on Incontinence After Cancer Surgery.
ClinicalTrials.gov study NCT05960734. IPD Sharing: YES. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.