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5,666 results for “Social”
Assessing Factors of User Participation in Social Media During Crisis Events: An Analysis of Features and Practices
<p>This data is analyzed and presented in the publication: Assessing Factors of User Participation in Social Media During Crisis Events: An Analysis of Features and Practices</p><p><strong>Abstract</strong></p><p>The relevance of employing social media in crisis scenarios has aroused interest for researchers and teams responsible for crisis management. The aim of this study is to explore the experience and abilities of social media users related to such events. For this, we conducted an analysis of the functionalities of social media used in this context, followed by a survey with users of social media. The research included the participation of 159 individuals and queried whether the participants had previously witnessed crisis events, whether they habitually share information about these events, and whether they perceived the importance of this practice. The results suggest that participants actively use social media and are inclined to share information about crisis events, provided improvements are made to the existing features. This study offers contributions toward a more profound understanding of social media tools, user interaction, and information sharing while considering the challenges found during such events.</p>
OKG: A Knowledge Graph for Fine-grained Understanding of Social Media Discourse on Inequality
<p>The Observatory Knowledge Graph (OKG) is a knowledge graph with tweets on inequality in terms of the OBIO ontology (https://w3id.org/okg/obio-ontology/), which integrates social media metadata with various types of linguistic knowledge. The OKG can be used as the backbone of a social media observatory, to facilitate a deeper understanding of social media discourse on inequality.</p> <p>We retrieved tweets and retweets published from the end (30th) of May 2020 to the beginning (1st) of May 2023.</p> <p>In this version of the OKG, we use a sample of 85,247 tweets, published from May 30th to August 27th, 2020. To be compliant with Twitter's policies, we remove usernames and id's, as well as the tweet texts and sentences. We also replace user IRIs with skolem IRIs through skolemization. </p> <p>Access to the OKG as well as the SPARQL endpoint can be requested by sending a mail to the contact person (l.stork@uva.nl) with the following information: </p> <ol> <li>A description of the use case </li> <li>Affiliation of the researchers involved</li> <li>How their work is in line with Twitter's policies: https://developer.twitter.com/en/developer-terms/policy#4-d</li> </ol>
CHALLENGES IN COUNTERING AND PREVENTING SOCIAL MEDIA CALLS FOR MASS PUBLIC SAFETY VIOLATIONS
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CoMix social contact data for Switzerland (2021-2022)
<p><a href="https://www.uhasselt.be/en/aparte-sites-partner-en/epipose/the-comix-study">CoMix</a> is a social contact survey that followed households across Europe throughout the COVID-19 pandemic (<a href="https://doi.org/10.1186/s12916-021-02133-y">Verelst et al., 2021</a>). In Switzerland, we conducted a total of 24 survey waves from 22 January 2021 to 19 May 2022. The market research company Ipsos MORI recruited a nationally representative sample of study participants using quota sampling based on age, gender, region, and work status through a combination of social media, web advertising, and email campaigns. The survey included adults aged 18 or above and parents (at least 18 years old) who completed the surveys on behalf of their children (<18 years old). For parents, quotas were set on region only. </p><p>Participants reported their social contacts made on the day prior to survey participation. A contact was defined as anyone who met the participant in person with whom at least a few words were exchanged or physical contact was made. The design of the survey is largely based on the POLYMOD study (<a href="https://doi.org/10.1371/journal.pmed.0050074">Mossong et al., 2008</a>). Further details about the study design and methodology have been published elsewhere (<a href="https://doi.org/10.1186/s12916-021-02133-y">Verelst et al., 2021</a>; <a href="https://doi.org/10.1186/s12879-023-08214-y">Wong et al., 2022</a>).</p>
Dataset Building and Public Works compagnies and assessment of Corporate Social Responsibility 2021 Tshopo_DRCongo
<p><br>The data resulting from the assessment of attitudes and policies of construction companies in Kisangani is now available in a dedicated space. During the surveys conducted in August and September 2021, we used structured questionnaires focused on five key points.</p><p>These questionnaires allowed for the collection of qualitative and quantitative data, covering the identification of the company and the respondent, the presence of corporate social responsibility (CSR) policies, the existence of legal wood procurement policies, and the companies' perspectives on actions in this crucial area.</p><p>To facilitate data collection, we opted for digitalization through the Kobotoolbox application, effectively deployed on Android phones. The in-depth analysis of the data was then carried out using Excel 2016, based on the list of members of the Association of National Entrepreneurs of the Oriental Province (ASSENAPO) dated October 4, 2017.</p><p>Our survey covered all 51 listed construction structures, with 42 representatives of construction companies interviewed after discussions and based on their availability. Thus, our study provides a comprehensive perspective on the attitudes and policies of companies operating on the scale of the city of Kisangani.</p>
CBF-Based STL Motion Planning for Social Navigation in Crowded Environment
<p>Video of submitted paper entitled "CBF-Based STL Motion Planning for Social Navigation in Crowded Environment"</p><p> </p>
Analysis Titanic Survival through Graph-Based Node with Neo4j: Unraveling Social Dynamics (Dataset & Cypher)
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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>
Extended 2019 Social Accounting Matrix for Zambia
<p>This is a social accounting matrix produced by IFPRI, but extended to include a more detailed representation of the energy sector. </p> <p>The IFPRI reference is as follows - Pauw, K., Tembo, B., and Thurlow, J. (2021). 2019 Social Accounting Matrix for Zambia: A Nexus Project SAM. </p>
Initially Submitted Version of: Supporting Information S2: Assessing the Social Dimension in Strategic Network Design for a Sustainable Development: The Case of Bioethanol Production in the EU
<p>Supporting Information S2 to the manuscript <em>Assessing the Social Dimension in Strategic Network Design for a Sustainable Development: The Case of Bioethanol Production in the EU </em>handed in at the Journal of Industrial Ecology</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>
Data from: Genes associated with ant social behavior show distinct transcriptional and evolutionary patterns
[No abstract entered]
Using a real-world network to model the trade-off between stay-at-home restriction, vaccination, social distancing and working hours on COVID-19 dynamics
<p>These datasets have been obtained through thousands of well-carried simulations by using the agent-based model based on a time-dynamic graph with stochastic transmission events. </p> <p>These simulations have been conducted on MATLAB 2019a.</p>
Figure 1 of the paper "Multi-level structure of the First Tuesday communities after the 2000 dot-com crash: A social network analysis of economic actors based on web archives"
<p><span><span><span><span><span><span><span><span>The temporal evolution of the </span></span></span></span></span></span><span><span><span><span><span><span>firsttuesday.com </span></span></span></span></span></span><span><span><span><span><span><span>website </span></span></span></span></span></span><span><span><span><span><span><span>reconstructed from a collection of web archives by using the web cernes approach (Lobbé 2023). The website grows from the center of the figure in 1999</span></span></span></span></span></span><span><span><span><span><span><span>, </span></span></span></span></span></span><span><span><span><span><span><span>then splits into sub-sections. It </span></span></span></span></span></span><span><span><span><span><span><span>was gradually</span></span></span></span></span></span><span><span><span><span><span><span> abandoned after 2004 before being erased in 2010. The blue, green, and orange </span></span></span></span></span></span><span><span><span><span><span><span>sections </span></span></span></span></span></span><span><span><span><span><span><span>represent the sections where the First Tuesday meetings were announced.</span></span></span></span></span></span></span></span></p>
Spirituality Social Cure Survey
<p>The data set includes data on religious identity, spiritual bypassing, hope, and mental health during covid19 pandemic</p>
Effectiveness of Public Service Announcements in Promoting Social Causes
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Gut microbiome strain-sharing within isolated village social networks
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PRACTICAL SITUATION AND POSSIBILITIES OF IMPROVING THE SOCIAL ACTIVITY OF GIRLS WHO ARE ADULTS IN THE FAMILY THROUGH NATIONAL ARTS
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Dataset for Influence of ecological and social factors on huddling behaviour and cluster organisation in Japanese macaques (Macaca fuscata)
<p>Dataset for Influence of ecological and social factors on huddling behaviour and cluster organisation in Japanese macaques (Macaca fuscata)</p> <p><span>Huddling behaviour is present in many animal species. This behaviour involves maintaining close physical contact with conspecifics to minimise heat loss and, in general, reduce energy expenditure. Additionally, this behaviour also facilitates complex social interactions within a population. In Japanese macaques, this behaviour is observed in many populations across Japan, including Shodoshima, where huddling clusters can reach up to 100 individuals in winter. Based on several studies on this species, it appears that huddling, or <span> </span>in Japanese, is influenced by both meteorological factors and social relationships between individuals. The objective of this study is to understand the determinants that drive the expression, variation, and organisation of huddling behaviour. Two hypotheses were formulated. The first hypothesis posits that the formation and variations in the size and number of clusters are influenced by meteorological factors, while the second hypothesis suggests that the number and position of individuals within a cluster is related to existing relationships between individuals. To test these, data on the number, size, and individuals composing a cluster were collected, allowing building huddling social networks. Simultaneously, meteorological measurements were taken, along with observations on dominance and grooming interactions between individuals. This allowed us to create several statistical models and social networks for comparison. Our results suggest that the initiation of huddling is mainly related to solar radiation energy, while variations in number and size could be explained by temperature. Moreover, the organisation within a cluster is not random but reflects relationships between individuals. However, it is not a single parameter but rather a combination of social relationships that underpin the organisation of individuals within clusters.</span></p>
Data for research paper: Social transmission along multiple pathways promotes information fidelity and reduces divisiveness
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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)
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.