scholarly journals Automatic Exploitation of YouTube Data: A Study of Videos Published by a French YouTuber During COVID-19 Quarantine in France

2020 ◽  
Author(s):  
Gery Laurent ◽  
Benjamin Guinhouya ◽  
Marielle Whatelet ◽  
Antoine Lamer
Keyword(s):  
Meta Data ◽  
Automatic Collection

The objective of this study was to test the feasibility of automatically extracting and exploiting data from the YouTube platform, with a focus on the videos produced by the French YouTuber HugoDécrypte during COVID-19 quarantine in France. For this, we used the YouTube API, which allows the automatic collection of data and meta-data of videos. We have identified the main topics addressed in the comments of the videos and assessed their polarity. Our results provide insights on topics trends over the course of the quarantine and highlight users sentiment towards on-going events. The method can be expanded to large video sets to automatically analyse high amount of user-produced data.

scholarly journals Internet of Samples (iSamples): Toward an interdisciplinary cyberinfrastructure for material samples

GigaScience ◽  
2021 ◽  
Vol 10 (5) ◽  
Author(s):  
Neil Davies ◽  
John Deck ◽  
Eric C Kansa ◽  
Sarah Whitcher Kansa ◽  
John Kunze ◽  
...  
Keyword(s):  
Best Practices ◽  
Built Environment ◽  
21St Century ◽  
Natural Science ◽  
Natural World ◽  
The Internet ◽  
Data Standards ◽  
Meta Data ◽  
Cross Domain ◽  
Data Stewardship

Abstract Sampling the natural world and built environment underpins much of science, yet systems for managing material samples and associated (meta)data are fragmented across institutional catalogs, practices for identification, and discipline-specific (meta)data standards. The Internet of Samples (iSamples) is a standards-based collaboration to uniquely, consistently, and conveniently identify material samples, record core metadata about them, and link them to other samples, data, and research products. iSamples extends existing resources and best practices in data stewardship to render a cross-domain cyberinfrastructure that enables transdisciplinary research, discovery, and reuse of material samples in 21st century natural science.

scholarly journals Adopting standard variable labels solves many of the problems with sharing and reusing data

2021 ◽  
Vol 14 (2) ◽  
pp. 205979912110266
Author(s):  
Brett Buttliere
Keyword(s):  
Final Section ◽  
Meta Data ◽  
Question Wording ◽  
Variable Label ◽  
The Future ◽  
Simple Step

Datasets and analysis scripts are becoming more available online, but most datasets are still unclear and difficult to use due to poor meta-data. Adopting standard variable label solves most of these problems and is easily implemented if we set the labels at the time of publication, that is, for authors to also establish standard variable labels when they establish for example, question wording. This simple step involves little effort but facilitates the sharing of datasets and analysis scripts enormously. Current initiatives to improve meta-data rely on users spending much time creating new meta-data for each variable, which is time consuming, unenjoyable, and hinders adoption. Some suggestions are made on how brief, unique, and clear variable labels can be developed, especially using the last two digits of the year the scale was published in. Standards for dataset and analysis script etiquette are the future, and the final section of the manuscript examines other easy places simple standards can save time and frustration for (re)users.

Semi-automatic Collection of Marine Debris by Collaborating UAV and UUV

2020 ◽  
Author(s):  
Naoki Shirakura ◽  
Takuya Kiyokawa ◽  
Hikaru Kumamoto ◽  
Jun Takamatsu ◽  
Tsukasa Ogasawara
Keyword(s):  
Marine Debris ◽  
Automatic Collection

Extracting an image similarity index using meta-data content for image mining applications

1997 ◽  
Author(s):  
Srinivasan Raghavan ◽  
Robert F. Cromp ◽  
Sridhar Srinivasan ◽  
Raadhakrishnan Poovendran ◽  
William J. Campbell ◽  
...  
Keyword(s):  
Similarity Index ◽  
Image Similarity ◽  
Image Mining ◽  
Meta Data ◽  
Data Content
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