Anansi Masters - the story continuesThe Anansi Masters project is developed by Vista Far Reaching Visuals (Mr. Jean Hellwig) and partners. It is designed as a public digital platform at http://www.anansimasters.net and opened in 2007. At the website one can find information about the story character of Nanzi (or Anansi or Kweku Ananse), with English and Dutch subtitled video recordings of storytelling in several countries in different languages, educational modules about storytelling for use at schools and academies, and digital issues of the Anansi Masters Journal published since the beginning of the project. All storytelling videos and videos that were made for documentation or marketing purposes are published on Youtube. Since 2012 all films of Anansi Masters were uploaded to Youtube and linked to the Anansi Masters website. Their display is embedded in the website together with the respective metadata that are entered through a custom made content management system (CMS).In March 2012, public storytelling events were organized by Drs. Jean Hellwig (Hellwig Productions AV / Vista Far Reaching Visuals Foundation) on the islands of Curacao and Aruba. Any professional or non-professional storyteller was invited to tell a story in front of the Anansi Masters camera and the available audience. Storytellers were free to choose their story and language. Each storyteller had to agree that the video registration of their story could be made available for open access. Storytellers were asked in front of the camera to answer a few questions about who they are and how they selected the story that they told.The Anansi Masters project started in 2007 with the registration of Kweku Ananse stories in Ghana and The Netherlands. The storytelling events organized on Curacao and Aruba in 2012 were part of the second phase 'Anansi Masters - the story continues'. The project registers contemporary ways of storytelling from an old tradition and aims to stimulate and revitalize the Nanzi storytelling by making the storytelling videos available to a large international audience. In 2008 a dvd in Dutch was released with 22 stories from Ghana and The Netherlands. In 2013 a dvd in English is released with all 32 stories that were recorded on Curaçao and Aruba.The stories of the Anansi tradition originate in Africa and were exported to other parts of the world through slave trade and migration. In Anansi Masters, the similarities and differences between the stories and storytellers, who tell in their own language, can be found. Anansi Masters initiates different activities all over the world where stories from this oral tradition can be found. The founder has the ambition to film as many stories from this tradition as possible in as many countries as possible. Anansi Masters collaborates with writers, theatre makers, filmmakers, researchers, schools and of course with many many storytellers.This dataset contains the documentation, video files, documents and pictures that were made to document the second phase of the Anansi Masters project with the subtitle 'the story continues'. These files were produced to report the process and results to the sponsoring funds and to be used in marketing through Facebook.This dataset contains the following:- report in Dutch with separate appendices- videos with datasheets 0015 - 0022 reflecting some of performances in the media to market the storytelling events- short video impression with datasheet 0023 of a musical performance at the storytelling event in Curacao- a list with names and codes of the recorded stories and storytellersFor each storyteller and their stories a new dataset has been created. Links to these datasets can be found under 'Relations'.

YouTube-UGC is a large-scale UGC dataset, including 1,500 20-second videos on the official YouTube website, which are uploaded by users under the Creative Commons agreement, and can be used for research in the fields of video compression and quality assessment. Video content covers popular categories such as gaming and sports, as well as new features such as high dynamic range imaging (HDR). Quality assessment uses three reference indicators: Noise, Banding, SLEEQ.

We are publishing a dataset we created for the HTTPS traffic classification.

Since the data were captured mainly in the real backbone network, we omitted IP addresses and ports. The datasets consist of calculated from bidirectional flows exported with flow probe Ipifixprobe. This exporter can export a sequence of packet lengths and times and a sequence of packet bursts and time. For more information, please visit ipfixprobe repository (Ipifixprobe).

During our research, we divided HTTPS into five categories: L -- Live Video Streaming, P -- Video Player, M -- Music Player, U -- File Upload, D -- File Download, W -- Website, and other traffic.

We have chosen the service representatives known for particular traffic types based on the Alexa Top 1M list and Moz's list of the most popular 500 websites for each category. We also used several popular websites that primarily focus on the audience in our country. The identified traffic classes and their representatives are provided below:

Live Video Stream Twitch, Czech TV, YouTube Live

Video Player DailyMotion, Stream.cz, Vimeo, YouTube

Music Player AppleMusic, Spotify, SoundCloud

File Upload/Download FileSender, OwnCloud, OneDrive, Google Drive

Website and Other Traffic Websites from Alexa Top 1M list

Paper: Barari, Soubhik, and Tyler Simko. "LocalView, a database of public meetings for the study of local politics and policy-making in the United States." Nature: Scientific Data 10.1 (2023): 135. Abstract: Despite the fundamental importance of American local governments for service provision in areas like education and public health, local policy-making remains difficult and expensive to study at scale due to a lack of centralized data. This article introduces LocalView , the largest existing dataset of real-time local government public meetings – the central policy-making process in local government. In sum, the dataset currently covers 139,616 videos and their corresponding textual and audio transcripts of local government meetings publicly uploaded to YouTube – the world’s largest public video-sharing website – from 1,012 places and 2,861 distinct governments across the United States between 2006-2022. The data are processed, downloaded, cleaned, and publicly disseminated (at localview.net) for analysis across places and over time. We validate this dataset using a variety of methods and demonstrate how it can be used to map local governments’ attention to policy areas of interest. Finally, we discuss how LocalView may be used by journalists, academics, and other users for understanding how local communities deliberate crucial policy questions on topics including climate change, public health, and immigration.

Themes representing peer support.

URDU-Dataset

1. General information

URDU dataset contains emotional utterances of Urdu speech gathered from Urdu talk shows. It contains 400 utterances of four basic emotions: Angry, Happy, Neutral, and Emotion. There are 38 speakers (27 male and 11 female). This data is created from YouTube. Speakers are selected randomly.

The similar version of dataset is uploaded to DagsHub: URDU-Dataset, enabling you to preview the dataset before downloading it.

2. Structure

Nomenclature followed while naming the files in the dataset is to provide information about the speaker, gender, number of the file for that speaker and overall numbering of the file in particular emotion. Files are named as follows:

General Name: SGX_FXX_EYY

For more details about dataset, please refer the complete paper "Cross Lingual Speech Emotion Recognition: Urdu vs. Western Languages". https://arxiv.org/pdf/1812.10411.pdf

2.1 Audio files:

• [21M] Angry - of approximately 242 seconds of "clean" speech in .wav format (pushed to DagsHub)
• [21M] Happy - of approximately 244 seconds of "clean" speech .wav format (pushed to DagsHub)
• [21M] Neutral - of approximately 244 seconds of "clean" speech .wav format (pushed to DagsHub)
• [21M] Sad - of approximately 244 seconds of "clean" speech .wav format (pushed to DagsHub)

2.2 Organization of the Emotions dataset

The dataset is small (88MB) and simple to navigate as it has 4 folders based on emotions. Each folder contains 100 .wav audio files containing the emotions of Urdu speakers. The audio file range from 2~3 second of audio taken from a various video uploaded on YouTube. The following ASCII diagram depicts the directory structure.

How much time do people spend on social media? As of 2024, the average daily social media usage of internet users worldwide amounted to 143 minutes per day, down from 151 minutes in the previous year. Currently, the country with the most time spent on social media per day is Brazil, with online users spending an average of three hours and 49 minutes on social media each day. In comparison, the daily time spent with social media in the U.S. was just two hours and 16 minutes. Global social media usageCurrently, the global social network penetration rate is 62.3 percent. Northern Europe had an 81.7 percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with 10.1 and 9.6 percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flip side, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

During the first half of 2023, the majority of copyright claims received by YouTube were spotted by the platform's Content ID tool, which cross-checks uploaded videos against a larger file database. Over 2.75 million claims were submitted via Copyright Match Tool, while approximately of two million claims were submitted to the platform via webforms.