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48 results for “social media data”
DeepCube: Post-processing and annotated datasets of social media data
<p>Researcher(s): Alexandros Mokas, Eleni Kamateri</p> <p>Supervisor: Ioannis Tsampoulatidis</p> <p>This repository contains 3 social media datasets:</p> <p><strong>2 Post-processing datasets:</strong> These datasets contain post-processing data extracted from the analysis of social media posts collected for two different use cases during the first two years of the <a href="https://deepcube-h2020.eu/">Deepcube </a>project. More specifically, these include:</p> <ul> <li>The UC2 dataset containing the post-processing analysis of the Twitter data collected for the <a href="https://deepcube-h2020.eu/">DeepCube</a> use case (UC2) dealing with the climate induced migration in Africa. This dataset contains in total 5,695,253 social media posts collected from the Twitter platform, based on the initial version of search criteria relevant to UC2 defined by Universitat De Valencia, focused on the regions of Ethiopia and Somalia and started from 26 June, 2021 till March, 2023.</li> <li>The UC5 dataset containing the post-processing analysis of the Twitter and Instagram data collected for the <a href="https://deepcube-h2020.eu/">DeepCube</a> use case (UC5) related to the sustainable and environmentally-friendly tourism. This dataset contains in total 58,143 social media posts collected from the Twitter and Instagram platform (12,881 collected from Twitter and 45,262 collected from Instagram), based on the initial version of search criteria relevant to UC5 defined by MURMURATION SAS, focused on the regions of Brasil and started from 26 June, 2021 till March, 2023.</li> </ul> <p><strong>1 Annotated dataset: </strong>An additional anottated dataset was created that contains post-processing data along with annotations of Twitter posts collected for UC2 for the years 2010-2022. More specifically, it includes:</p> <ul> <li>The UC2 dataset contain the post-processing of the Twitter data collected for the <a href="https://deepcube-h2020.eu/">DeepCube</a> use case (UC2) dealing with the climate induced migration in Africa. This dataset contains in total 1721 annotated (412 relevant and 1309 irrelevant) by social media posts collected from the Twitter platform, focused on the region of Somalia and started from 1 January, 2010 till 31 December, 2022.</li> </ul> <p>For every social media post retrieved from Twitter and Instagram, a preprocessing step was performed. This involved a three-step analysis of each post using the appropriate web service. First, the location of the post was automatically extracted from the text using a location extraction service. Second, the images included in the post were analyzed using a concept extraction service, which identified and provided the top ten concepts that best described the image. These concepts included items such as "person," "building," "drought," "sun," and so on. Finally, the sentiment expressed in the post's text was determined by using a sentiment analysis service. The sentiment was classified as either positive, negative, or neutral.</p> <p>After the social media posts were preprocessed, they were visualized using the <a href="https://deepcube.infalia.com/">Social Media Web Application</a>. This intuitive, user-friendly online application was designed for both expert and non-expert users and offers a web-based user interface for filtering and visualizing the collected social media data. The application provides various filtering options, an interactive map, a timeline, and a collection of graphs to help users analyze the data. Moreover, this application provides users with the option to download aggregated data for specific periods by applying filters and clicking the "Download Posts" button. This feature allows users to easily extract and analyze social media data outside of the web application, providing greater flexibility and control over data analysis.</p> <p>The dataset is provided by <a href="https://infalia.eu/">INFALIA</a>. <br><br><a href="https://infalia.eu/">INFALIA</a>, being a spin-off of the <a href="https://www.certh.gr/root.en.aspx">CERTH</a> institute and a partner of a research EU project, releases this dataset containing Tweets IDs and post pre-processing data for the sole purpose of enabling the validation of the research conducted within the <a href="https://deepcube-h2020.eu/">DeepCube</a>. Moreover, Twitter Content provided in this dataset to third parties remains subject to the Twitter Policy, and those third parties must agree to the Twitter Terms of Service, Privacy Policy, Developer Agreement, and Developer Policy (<a href="https://developer.twitter.com/en/developer-terms">https://developer.twitter.com/en/developer-terms</a>) before receiving this download.</p>
Data on: The role of technical characteristics in blockchain adoption: survey data from German social media network users
<p><span>Blockchain has become a hyped emerging technology that is predicted to be heavily influential in all our lives. Yet, until now, it has failed to deliver most of its advertised benefits. To tackle this problem and provide an explanation for the missing wider success, this study focuses on the role of technology features in the adoption of blockchain. Thus, this research integrates the view on technological characteristics, represented by aspects of the mindfulness concept, with the sociological aspects influencing technology adoption decisions based on the widely used unified theory of acceptance and use of technology (UTAUT). The resulting research model is evaluated using the partial least squares structural equation modelling (PLS-SEM) estimation approach with German social media network. The findings indicate that only high-level knowledge of distinct technology features (uniqueness) is influencing adoption decisions while the missing deeper understanding of these features hinders a careful evaluation of its benefits and meaningful use. This research expands the technology adoption literature by highlighting the role of technical characteristics and combining social, psychological and technological factors into one model. Further, it helps practitioners to understand the causes for the limited success of blockchain and advances the general knowledge on technology adoption.</span></p>
Time series data and codes from: Quantifying social media predictors of violence during the 6 January US Capitol insurrection using Granger causality
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Data on: The role of technical characteristics in blockchain adoption: survey data from German social media network users
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Data for 'How Centralized is Political Communication on Social Media?'
<p>This file contains the .Rdata files used for the analyses in the manuscript 'How Centralized is Political Communication on Social Media?'.</p>
Time series data and codes from: Quantifying links between social media and the duration and escalation of violence during January 6th US Capitol insurrection
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The Arc de Triomphe, Wrapped social media data
<p>A dataset with Instagram and Twitter post data concerning the Arc de Triomph in and the Arc de Triomph Wrapped, an art installation by Christo and Jeanne-Claude.</p> <p>It includes four csv files: two files with information about Instagram posts (comments, likes, media etc.) for Arc de Triomph as unwrapped and as wrapped respectively and two for Twitter posts.</p> <p>Related publication:</p> <p>Vlachou, S.; Panagopoulos, M. The Arc de Triomphe, Wrapped: Measuring Public Installation Art Engagement and Popularity through Social Media Data Analysis. <em>Informatics</em> <strong>2022</strong>, <em>9</em>, 41. https://doi.org/10.3390/informatics9020041</p> <p> </p> <p> </p>
RePAST social media data
<p>RePAST social media data</p>
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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)
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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.