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434 results for “Social Media”
A comprehensive dataset of the Spanish research output and its associated social media and altmetric mentions (2016-2020)
<p>Data on research publications authored by Spanish institutions between 2016 and 2020 with their associated social media and altmetric mentions, and on researchers affiliated to Spanish institutions whose work is highly mentioned in social media and non-academic outlets.</p> <p>Variables of the publications dataset:</p> <ul> <li><strong>id</strong> - Unique publication identifier</li> <li><strong>title</strong> - Full title of the publication</li> <li><strong>year</strong> - Year of publication</li> <li><strong>type</strong> - Document type</li> <li><strong>journal</strong> - Name of the journal</li> <li><strong>esi</strong> - ESI category of the publication</li> <li><strong>influscore</strong> - AAS value on March 3, 2021</li> <li><strong>news</strong> - Number of mentions in news media</li> <li><strong>blogs</strong> - Number of mentions in blogs</li> <li><strong>policy</strong> - Number of mentions in policy reports</li> <li><strong>patent</strong> - Number of mentions in patent</li> <li><strong>twitter</strong> - Number of mentions in Twitter</li> <li><strong>post_peer</strong> - Number of mentions in PubPeer and Publons</li> <li><strong>weibo</strong> - Number of mentions in Weibo</li> <li><strong>facebook</strong> - Number of mentions in Facebook</li> <li><strong>wikipedia</strong> - Number of mentions in Wikipedia</li> <li><strong>google</strong> - Number of mentions in Google+</li> <li><strong>linkedin</strong> - Number of mentions in LinkedIn</li> <li><strong>reddit</strong> - Number of mentions in Reddit</li> <li><strong>pinterest</strong> - Number of mentions in Pinterest</li> <li><strong>f1000</strong> - Number of mentions in F1000</li> <li><strong>stack_overflow</strong> - Number of mentions in Stack Overflow</li> <li><strong>youtube</strong> - Number of mentions in YouTube</li> <li><strong>syllabus</strong> - Number of mentions in Open Syllabus Project</li> </ul> <p>Variables of the top authors dataset:</p> <ul> <li><strong>name</strong> - Full name of the researcher</li> <li><strong>orcid</strong> - ORCID record</li> <li><strong>organization</strong> - Name of the institution of affiliation</li> <li><strong>publications</strong> - List of publication identifiers (id) connecting with the publications dataset</li> </ul>
Propaganda and fake news on the war in Ukraine: data from Russian-speaking social media communities
<p>The data set contains posts from social media networks popular among Russian-speaking communities. Information was searched based on pre-defined keywords ("war", "special military operation", etc.) and is mainly related to the ongoing war in Ukraine with Russia. After a thorough review and analysis of the data, both propaganda and fake news were identified. The collected data is anonymized. Feature engineering and text preprocessing can be applied to obtain new insights and knowledge from this data set. The data set is useful for the study of information wars and propaganda identification.</p>
Exploring the generational influence on social media based tourist decision making in India
Open the record for dataset details and reuse information.
iDRAMA-Scored-2024: A Dataset of the Scored Social Media Platform from 2020 to 2023
<p>ABSTRACT<br>---------------<br>Online web communities often face bans for violating platform policies, encouraging their migration to alternative platforms. This migration, however, can result in increased toxicity and unforeseen consequences on the new platform. In recent years, researchers have collected data from many alternative platforms, indicating coordinated efforts leading to offline events, conspiracy movements, hate speech propagation, and harassment. Thus, it becomes crucial to characterize and understand these alternative platforms. To advance research in this direction, we collect and release a large-scale dataset from Scored -- an alternative Reddit platform that sheltered banned fringe communities, for example, c/TheDonald (a prominent right-wing community) and c/GreatAwakening (a conspiratorial community). Over four years, we collected approximately 57M posts from Scored, with at least 58 communities identified as migrating from Reddit and over 950 communities created since the platform's inception. Furthermore, we provide sentence embeddings of all posts in our dataset, generated through a state-of-the-art model, to further advance the field in characterizing the discussions within these communities. We aim to provide these resources to facilitate their investigations without the need for extensive data collection and processing efforts.</p> <ul> <li>Scored platform: <a href="https://scored.co">https://scored.co</a></li> <li>Link to paper: <a href="https://arxiv.org/abs/2405.10233">https://arxiv.org/abs/2405.10233</a></li> <li>License: <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en">CC BY-NC-SA 4.0</a></li> </ul> <h1>Repository links</h1> <ul> <li><strong>Zenodo:</strong> From Zenodo, researchers can download `lite` version of this dataset, which includes only 57M posts from Scored (not the sentence embeddings).</li> <li><strong>Github:</strong> The main repository of this dataset, where we provide code-snippets to get started with this dataset. <ul> <li>Link here: <a href="https://github.com/idramalab/iDRAMA-scored-2024">https://github.com/idramalab/iDRAMA-scored-2024</a></li> </ul> </li> <li><strong>Huggingface:</strong> On Huggingface, we provide complete dataset with senetence embeddings.<br> <ul> <li>Link here: <a href="https://hf.co/datasets/iDRAMALab/iDRAMA-scored-2024">https://hf.co/datasets/iDRAMALab/iDRAMA-scored-2024</a></li> </ul> </li> </ul> <h1>Dataset Info</h1> <table> <tbody> <tr> <td><strong>File-name</strong></td> <td><strong>Data-points</strong></td> </tr> <tr> <td>comments-2020</td> <td>12,774,203</td> </tr> <tr> <td>comments-2021</td> <td>16,097,941</td> </tr> <tr> <td>comments-2022</td> <td>12,730,301</td> </tr> <tr> <td>comments-2023</td> <td>8,919,159</td> </tr> <tr> <td>submissions-2020-to-2023</td> <td>6,293,980</td> </tr> </tbody> </table> <h1>Authorship</h1> <p>This dataset is published at "AAAI ICWSM 2024 (INTERNATIONAL AAAI CONFERENCE ON WEB AND SOCIAL MEDIA)" hosted at Buffalo, NY, USA.</p> <ul> <li><strong>Academic Organization: </strong><a href="https://idrama.science/people/">iDRAMA Lab</a></li> <li><strong>Affiliation:</strong> Binghamton University, Boston University, University of California Riverside</li> </ul> <h1>Licensing</h1> <p>This dataset is available for free to use under terms of the non-commercial license <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en">CC BY-NC-SA 4.0</a>.</p> <h1>Citation</h1> <blockquote> <p>@inproceedings{patel2024idrama,<br> title={iDRAMA-Scored-2024: A Dataset of the Scored Social Media Platform from 2020 to 2023},<br> author={Patel, Jay and Paudel, Pujan and De Cristofaro, Emiliano and Stringhini, Gianluca and Blackburn, Jeremy},<br> booktitle={Proceedings of the International AAAI Conference on Web and Social Media},<br> volume={18},<br> pages={2014--2024},<br> year={2024},<br> issn = {2334-0770},<br> doi = {10.1609/icwsm.v18i1.31444},<br>}</p> </blockquote>
Dataset: Global X Social Media ETF (SOCL) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Multicontextual Phenotype Models: Biomedical Database and Literature Phenotype and Social Media Phenotype
Open the record for dataset details and reuse information.
Disclosure Privacy Information Social Media on TikTok
<p><em><span>With the rapid development of technology, the use of social media by the public, especially among young people, is increasing. One of the social media platforms currently used by young people is the TikTok application. It is a video-based TikTok feature accompanied by music, writing, and pictures that are considered attractive, so teenagers like it to show their existence and self-disclosure. Therefore, this study aims to examine the intention of users to disclose their privacy. As the basis of the theory, this study deployed the privacy calculus theory, where the perceived benefits and perceived risks play crucial roles in the intention to disclose their privacy</span></em></p>
BRAIN Journal-The Presence and Activity on Facebook of the Informative Travel Organizations in Romania-Figure 3. Integration of Social Media elements on tourism organization's websites
<p>Currently, in Romania there are about 8 million Facebook users (Facebrands.ro). In the recent years there has been a spectacular increase of this phenomenon, which shows how important is the use of social networks for an economic and even for a non-profit entity in order to make the brand known or to promote an activity (DailyBusiness.ro). </p>
BRAIN Journal-Participative Teaching with Mobile Devices and Social Networks for K-12 Children-Figure 16. Social media postings
<p>After different stages of experimentation, we produced different statistical analysis of our results:</p> <p>a. concerning the most accessed social media. It indicated that Panoramio was the most visited, and Google+ had the majority of postings (Figure 16). </p> <p>The statistics indicate that the different social networks had different levels of impact on the children and that in the future developments the focus should be on those more frequently accessed. </p> <p>b. concerning the pedagogical content. A survey was done among teachers and children to evaluate the interest in our solutions and the quality of the educational content and therefore of the overall efficiency</p>
BRAIN Journal-Participative Teaching with Mobile Devices and Social Networks for K-12 Children-Figure 4. Augmented Reality with video movie and social media (a vertical loom in front of two reconstructed kilns and a wall of a Roman villa rustica)
<p>The third stage was represented by the 3D virtual reconstruction process of the historical contexts, in our case a prehistoric village and a complete Roman villa rustica, with the help of students from the Design Department, NUA, coordinated by Professor Arch. Andreea Hasnaş. The AR application was created and tested on two commercial AR platforms, Layar and Junaio, and recently moved on the Aurasma platform (https://www.aurasma.com/). The POIs were augmented with the 3D virtual reconstructions, and also with 2D images and videos representing 3D virtual tours and technological processes (Figures 3, 4, 5). The AR application was connected to teachers’ emails and to Twitter, Facebook and Google+ project’s pages. </p>
BRAIN Journal-Participative Teaching with Mobile Devices and Social Networks for K-12 Children-Figure 15. Social media visits
<p>We also point out the following the advantages of Google+: - Google+ is a more user-friendly than other social environments and very suitable for use by school children than other blogging environments (e.g. Wordpress); thus it stimulated the play-like learning. - Google+ is more customizable than other social environments; - By allowing teachers to post questionnaires and to share images and videos or links to content on the Time Maps website, the Google+ page acted as an aggregator of information and a for scaffolding the learning process. After different stages of experimentation, we produced different statistical analysis of our results: concerning the most accessed social media. It indicated that Panoramio was the most visited (Figure 15)</p> <p>The statistics indicate that the different social networks had different levels of impact on the children and that in the future developments the focus should be on those more frequently accessed. </p>
Social media statistics
<p>This data was collected/ generated through the periodic monitoring of the project’s social media statistics (including Facebook, Twitter and LinkedIn) with a view to measuring and assessing the performance and results of the project’s social media activity in terms of dissemination and communication.</p>
PERCEIVE The use of social media in EU policy communication and implications for the emergence of a European public sphere
<p>This data set contains the underlying data of the paper “<strong>The use of social media in EU policy communication and implications for the emergence of a European public sphere</strong>”, published by The Journal of Regional Research - Investigaciones Regionales (ISSN: 1695-7253; E-ISSN: 2340-2717) in 2019.</p> <p>Data openly available within this dataset are a subset of the two following data sets, which contains all the relevant data of Work Package 3 and Work Package 5 of PERCEIVE project:</p> <ul> <li>Data set:<strong> “PERCEIVE: WP3: Effectiveness of communication strategies of EU projects” </strong><a href="https://doi.org/10.5281/zenodo.3371133">https://doi.org/10.5281/zenodo.3371133</a></li> <li>Data set:<strong> “PERCEIVE: WP5: The multiplicity of shared meanings of EU and Cohesion Regional and Urban Policy at different discursive levels” </strong><a href="https://doi.org/10.5281/zenodo.3371174">https://doi.org/10.5281/zenodo.3371174</a></li> </ul> <p>For the paper we collected Facebook posts referred to EU CP policies. We don’t have the permission to share these data (as they are protected by copyright), but all the sources are described in Deliverable 5.2, which is public (see <a href="http://doi.org/10.6092/unibo/amsacta/5726">http://doi.org/10.6092/unibo/amsacta/5726</a> or <a href="http://doi.org/10.5281/zenodo.1318184">http://doi.org/10.5281/zenodo.1318184</a>). We analyzed the textual content of data to construct a database of discursive topics in Task5.4. Data set includes the results of topic modeling and of a sentiment analysis performed on the Facebook homepages of Local Management Authorities (LMA) of PERCEIVE case study regions. </p>
Detecting weak and strong Islamophobic hate speech on social media
<p>Data, code and annotation guidelines for our publication, 'Detecting weak and strong Islamophobic hate speech on social media' (2019).</p>
Figure 1 in The first record of the deep-sea jellyfish Stygiomedusa gigantea (Scyphozoa: Semaeostomeae) from the tropical Southwestern Atlantic found on social media
Figure 1. Image of Syigiomedusa gigantea individuals observed in (A) Brazil, 12°34'39"S, 38°00'19"W, at the water surface, present study; (B) Gulf of Mexico, 26°12.483'N, 91°26.583'W, at 1747 m, from Benfield and Graham (2010); (C) Gulf of California, 25°27.220'N, 109°50.170', at 1300 m, from Drazen and Robinson (2004). The scale (= 1 m) is only applicable for Fig. 1A.
Social Media Usage According to Different Locations
<p>This ai-generated dataset provides detailed information on how individuals allocate their time across various social media platforms, including Facebook, Twitter, Instagram, YouTube, Snapchat, TikTok, LinkedIn, WhatsApp, and Pinterest. Each entry represents the number of hours spent on each platform and includes location data to explore geographic trends in social media consumption.</p> <p>The dataset is ideal for analyzing:</p> <ul> <li>Time distribution across social platforms.</li> <li>Location-based patterns in social media usage.</li> <li>Comparative studies on platform preferences.</li> </ul> <p>Perfect for social behavior analysis and data-driven marketing insights!</p>
The Dynamics of Self-Disclosure on Social Media: Analyzing the Impact of Benefits, Concerns, and Experiences
<p><span>In the digital age, social media platforms have become integral to daily communication, providing users with unprecedented opportunities to share personal information and connect with others. This phenomenon, known as self-disclosure, involves the voluntary sharing of personal information, thoughts, and feelings with others. This study investigates the factors influencing self-disclosure behavior on social media, employing Social Cognitive Theory (SCT) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) as theoretical frameworks</span>.</p>
Dissecting Tiktok and social media for children and young adults
<p>This data is related to protocol for systematic literature review and the details of literatures selected for systematic review.</p>
Analysis of websites, social media pages and apps for the development of new strategies for increasing participation of women in clinical trials
<p>For T2.5 of the i-CONSENT project, an analysis was undertaken of the strategies used to effectively communicate with women on the topic of women’s health or women’s health research, considering aspects such as tone, format and audience interaction. A total of 42 websites, social media pages and apps were included in the analysis. The attached document presents the findings from the data generation stage of this analysis.</p>
Data for the paper, "Social media data for environmental sustainability: a critical review of opportunities, threats and ethical use"
<p>These data were collected for the paper, "Social media data for environmental sustainability: a critical review of opportunities, threats and ethical use" published in One Earth. It includes a database of studies applying social media data in environmental sustainability research, which were collected and reviewed in full by the authors. Rather than providing a comprehensive summary of all relevant literature like in a systematic review, our objective was to take stock and evaluate the previous body of work in the field in order to promote conceptual innovation from its critical examination. Building on a set of 169 studies collected in a previous systematic review of social media data applications in environmental research (Ghermandi and Sinclair 2019), the database includes additional relevant studies that were identified by snowballing previous references and adding further gray and scientific academic articles known to the authors. For studies to be included in our analysis, they had to involve the use of data from one or more social media platforms and investigate human interactions with and/or impacts on the environment. We relied on a broad definition of social media including any website or application that enables users to create and share content or to participate in social networking (e.g., blogging sites, recommendation sites, and online forums). We further strengthened the analysis by including insights from additional literature on social media that do not have a direct application to environmental sustainability (e.g., studies on biases in social media data). The final database consists of 415 studies, which were published between 2011 and 2021.</p> <p> </p> <p>Ghermandi, Andrea, and Michael Sinclair. "Passive crowdsourcing of social media in environmental research: A systematic map." <em>Global environmental change</em> 55 (2019): 36-47.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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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.