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5,666 results for “Social”
Entendiendo la vulnerabilidad social: una mirada desde sus principales teóricos
<p><strong>Coordinador del Seminario: </strong>Carlos A. Navarrete Ulloa.<br> <strong>Expositor</strong>: Ramona Esmeralda Velázquez García</p> <p><strong>Comité Ejecutivo PRONACE-Vivienda</strong><br> Fernando Córdova Canela, Centro Universitario de Arte, Arquitectura y Diseño, Universidad de Guadalajara (UdeG).<br> Francisco Javier Porras Sánchez, Instituto de Investigaciones Dr. José María Luis Mora.<br> Gabriel Castañeda Nolasco, Universidad Autónoma de Chiapas (UNACH).<br> Carlos A. Navarrete Ulloa, Centro Universitario de Tonalá, (UdeG).</p> <p>Exposición realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:<br> Ramos, D. (2019). Entendiendo la vulnerabilidad social: una mirada desde sus principales teóricos. Revista Estudios del Desarrollo Social: Cuba y América Latina, 7(1), 139-154. <br> http://scielo.sld.cu/scielo.php?script=sci_abstract&pid=S2308-01322019000100139</p>
Producción social de la vivienda y el hábitat
<p><strong>Coordinador del Seminario</strong>: Carlos A. Navarrete Ulloa.<br> <strong>Expositor</strong>: Hiram Eduardo Urias Barrera</p> <p><strong>Comité Ejecutivo PRONACE-Vivienda</strong></p> <p>Fernando Córdova Canela, Centro Universitario de Arte, Arquitectura y Diseño, Universidad de Guadalajara (UdeG).<br> Francisco Javier Porras Sánchez, Instituto de Investigaciones Dr. José María Luis Mora.<br> Gabriel Castañeda Nolasco, Universidad Autónoma de Chiapas (UNACH).<br> Carlos A. Navarrete Ulloa, Centro Universitario de Tonalá, (UdeG).</p> <p>Exposición realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:</p> <p>Ortiz Flores, E. (2012). Producción social de la vivienda y el hábitat. Bases conceptuales y correlación con los procesos habitacionales. Habitat International Coalition HIC, Oficina Regional para América Latina. <a href="https://hic-al.org/2018/12/28/produccion-social-de-la-vivienda-y-el-habitat-bases-conceptuales-y-correlacion-con-los-procesos-habitacionales/">https://hic-al.org/2018/12/28/produccion-social-de-la-vivienda-y-el-habitat-bases-conceptuales-y-correlacion-con-los-procesos-habitacionales/</a></p>
Comprender la vida social urbana una propuesta a partir de las estrategias y tácticas de los agente
<p>Coordinador del Seminario: Carlos A. Navarrete Ulloa.<br> Expositor: Hiram Eduardo Urias Barrera.</p> <p>Comité Ejecutivo PRONACE-Vivienda</p> <ul> <li>Fernando Córdova Canela, Centro Universitario de Arte, Arquitectura y Diseño, Universidad de Guadalajara (UdeG).</li> <li>Francisco Javier Porras Sánchez, Instituto de Investigaciones Dr. José María Luis Mora.</li> <li>Gabriel Castañeda Nolasco, Universidad Autónoma de Chiapas (UNACH).</li> </ul> <p>Carlos A. Navarrete Ulloa, Centro Universitario de Tonalá, (UdeG).</p> <p>Exposición realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:</p> <p>Lange, C. (2013). Comprender la vida social urbana: una propuesta a partir de las estrategias y tácticas de los agentes sociales urbanos.En: A. Garrido y G. Gándara (coords.), Nuestras ciudades del futuro. ¿Cómo hacer sostenibles los espacios urbanos, 155-168.</p> <p><a href="https://repositorio.uchile.cl/handle/2250/133111">https://repositorio.uchile.cl/handle/2250/133111</a></p> <p> </p>
Nationally Representative Social Contact Patterns among U.S. adults, August 2020-September 2021
<p>The CovidVu study is a national probability survey that collected data on SARS-CoV-2 infection in the U.S. in three rounds: August-December 2020, March-April 2021, and July-September 2021. The goal of this study was to estimate cumulative incidence of SARS-CoV-2 infection in the United States. Surveys were mailed to randomly sampled households in the U.S., and one adult member of the household filled out the questionnaire and sent back SARS-CoV-2 specimens for testing. The data collected included information on social contacts by age, location, and whether they were physical or nonphysical contacts, as well as key demographic information on participants. Survey weights were used to determine unbiased estimates of key parameters, and were based on the population of noninstitutionalized, housed adults (>=18 years of age) in the U.S. Weights were calculated with respect to gender, age, race/ethnicity, education, income, marital status, and census division. For more in-depth information, please visit https://prismhealth.emory.edu/covidvu/ to view recent publications using this data.</p>
Neurons for infant social behaviors in the mouse zona incerta
<p><strong>Neurons for infant social behaviors in the mouse zona incerta</strong></p> <p>Repository containing datasets supporting the study.</p> <p>Github link to related analysis code: https://github.com/yxl95/zona_incerta_infant_social_behavior</p>
Dataset: Sex differences in the impact of social relationships on individual vocal signatures in grey mouse lemurs
<p>Dataset used in the statistical analysis of the publication "Sex differences in the impact of social relationships on individual vocal signatures in grey mouse lemurs (<em>Microcebus murinus</em>)"</p> <p><strong>Abstract</strong></p> <p>Vocali<span>z</span>ations coordinate social interactions between conspecifics by conveying information concerning the individual or group identity of the sender. Social accommodation is a form of vocal learning where social affinity is signalled by converging or diverging vocali<span>z</span>ations to those of conspecifics. To investigate whether social accommodation is linked to the social lifestyle of the sender, we investigated sex-specific differences in social accommodation in a dispersed living primate, the grey mouse lemur, where females form stable sleeping groups whereas males live solitarily. We used 482 trill calls of 36 individuals from our captive breeding colony to compare acoustic dissimilarity between individuals with genetic relatedness, social contact time and body weight. Our results showed that female trills become more similar the more time females spen<span>d</span> with each other independent of genetic relationship, suggesting vocal convergence. In contrast, male trills were affected more by genetic than social factors. However, focus<span>s</span>ing only on sociali<span>z</span>ed males, male trills diverged from each other the more time males were cage partners. Thus, grey mouse lemurs show the capacity for social accommodation, with females converging their trills to signal social closeness to sleeping group partners, whereas males do not adapt or diverge their trills to signal individual distinctiveness. </p> <p> </p> <p>For details concerning the recording of the trills confer to the publication at doi: 10.1098/rstb.2023.0193</p>
Knowledge of Social Networks for Health is Associated with COVID-19 Health Protective Behaviors
<p>This is the dataset and stata code for the paper "Knowledge of Social Networks for Health is Associated with COVID-19 Health Protective Behaviors” submitted to Plos One May 1st, 2024.</p>
Methods of promoting modern theater on social media / Методи популяризації сучасного театру у соціальних мережах
<p>The dataset "Methods of promoting contemporary theatre on social media", based on a survey of 105 respondents, includes answers to the following questions:</p> <ul> <li>How often do you go to the theatre?</li> <li>What social media do you use to find out about theatre events?</li> <li>What type of content on social media is most effective in drawing your attention to theatre events? - Has social media ever prompted you to buy theatre tickets?</li> <li>What factors influence your decision to attend a theatre performance you saw on social media?</li> <li>How do you assess the overall effectiveness of social media in promoting theatre events?<br>Data downloaded in .csv format.</li> </ul>
MIRA-KG: A Knowledge Graph of Hypotheses and Findings for Social Demography Research
<p>A shift in scientific publishing from paper-based to knowledge-based practices promotes reproducibility, machine actionability and knowledge discovery. This is important for disciplines like social science, as study indicators are often social constructs such as race or education; hypothesis tests are challenging to compare in demographic research due to their limited temporal and spatial coverage; and natural language in research papers is often imprecise and ambiguous. Therefore, we present the MIRA-KG, consisting of: (1) an ontology for capturing social demography research, which links hypotheses and findings to evidence, (2) annotations of papers on health inequality in terms of the ontology, gathered by (i) prompting a Large Language Model to annotate paper abstracts using the ontology, (ii) mapping concepts to terms from NCBO BioPortal ontologies and GeoNames, and (iii) refining the final graph by a set of SHACL constraints, developed according to data quality criteria. The utility of the resource lies in its use for formally representing social demography research hypotheses, discovering research biases, discovery of knowledge, and the derivation of novel questions.<br><br>This dataset was generated using the code available on Github at <a href="https://w3id.org/mira/">https://w3id.org/mira/</a> at version v1.0. It uses the following ontology: <a href="https://w3id.org/mira/ontology/">https://w3id.org/mira/ontology/</a>. </p>
Changes in the users of the social-ecological system around a reciprocal human-dolphin relationship
<p>This package contains the deidentified data and R code to replicate the quantitative analyses and figures of the scientific article accepted for publication at People & Nature:</p> <p><span>Cantor M</span><strong><span>,</span></strong><span> Santos-Silva B, Daura-Jorge FG, Machado AMS, Peterson D, da Rosa DX, Simões-Lopes PC, Valle-Pereira JVS, Zank S, Hanazaki N. Accepted. Changes in the users of the social-ecological system around a reciprocal human-dolphin relationship. People & Nature.</span> </p> <p> </p> <p><span>Abstract</span></p> <p>1. In contrast to many contemporary negative human-nature relationships, Indigenous Peoples and Local Communities have stewarded nature through cultural practices that include reciprocal contributions for both humans and nature. A rare example is the century-old artisanal fishery in which net-casting fishers and wild dolphins benefit by working together, but little is known about the persistence of the social-ecological system formed around this cultural practice.</p> <p>2. Here, we frame the human-dolphin cooperative fishery in southern Brazil as a social-ecological system based on secondary data from the scientific and grey literature. To investigate the dynamics of this system, we survey the local and traditional ecological knowledge and examine potential changes in its main component—the artisanal fishers—over time and space.</p> <p>3. Over 16 years, we conducted four interview campaigns with 188 fishers in fishing sites that are more open (accessible) or closed (restricted) to external influence. We investigated their experience, engagement, and economic dependence on dolphin-assisted fishing, as well as the learning processes and transmission of the traditional knowledge required to cooperate with dolphins.</p> <p>4. Our qualitative data suggest that fishers using accessible and restricted fishing sites have equivalent fishing experience, but those in more restrictive sites tend to be more economically dependent on dolphins, relying on them for fishing year-round. The traditional knowledge on how to cooperate with dolphins is mostly acquired via social learning, with a tendency for vertical learning to be frequent among fishers using sites more restrictive for outsiders. Experience, economic dependence, and reliance on vertical learning seem to decrease recently, especially in the accessible site. Our quantitative analyses, however, suggest that some of these fluctuations were not significant.</p> <p>5. Our study outlines the key components of this social-ecological system and identifies changes in the attributes of a main component, the users. These changes, when coupled with changes on other components such as governance and resource units (fish and dolphins), can have implications for the persistence of this cultural practice and the livelihoods of Local Communities. We suggest that continuous monitoring of this system can help to safeguard the reciprocal contributions of this human-nature relationship in years to come.</p>
Annotated Data in Spanish for Toxicity and Insults in Digital Social Networks
<p>This repository contains data sets and materials for a gold standard elaboration on toxicity and incivility in the digital sphere based on human coding to benchmark algorithmic classification tasks with transformers and LLMs. <strong>The labelling progress is 62%</strong>.</p> <p>We are labelling two samples of novel datasets of political digital interactions on Twitter (rebranded as X). The first set comprises almost 5 million data points from three Latin American protest events: (a) protests against the coronavirus and judicial reform measures in Argentina during August 2020; (b) protests against education budget cuts in Brazil in May 2019; and (c) the social outburst in Chile stemming from protests against the underground fare hike in October 2019. We are focusing on interactions in Spanish to elaborate a gold standard for digital interactions in this language, therefore, we prioritise Argentinian and Chilean data. The second set contains more than 31 million messages and more than 9 million interactions between 2010 and 2022, covering the election of members of the first Constitutional Convention in Chile, the drafting process and the referendum in which the proposal was rejected.</p> <p>This project is generously funded by the <strong>OpenAI Academic Programme</strong>, <strong>2024 FAE-UDP Research Grant</strong>, and partially by the <strong>St Hilda's College Muriel Wise Fund at the University of Oxford</strong>. The <a href="https://training-datalab.com/"><strong>Training Data Lab</strong></a> research group also logistically supports this project.</p>
How Can Subjective Well-being be Increased? The Role of Social Comparison and Subjective Financial Well-Being
<p><strong>Data Dictionary :</strong></p> <p>CFA = Confirmatory factor analysis</p> <p>Finwell = SFW = Financial well being</p> <p>CS = PK =social comparison</p> <p>IFLS = Indonesian Family Life Survey</p> <p> </p> <p> </p>
Data from: Multifaceted density dependence: Social structure and seasonality effects on Serengeti lion demography
<p>This dataset contains the data and R scripts to estimate the survival, transition, and detection probabilities (Lions_Survival_Transition_MultistateCMRModel.zip) as well as the probability of reproduction and recruitment to 1 year old (Lions_Reproduction_Recruitment_GLMM.zip) in a population of African lions (<em>Panthera leo</em>) monitored between 1984 and 2014 in the Serengeti National Park, Tanzania.</p> <p>We assessed the season-specific effects of density measures at the intra- (number of females in a pride and male coalition size) and extra-group levels (number of nomadic coalitions in the home range of a group) using a Bayesian multistate capture-mark-recapture model for the survival and transition rates and Bayesian generalized linear mixed models for reproduction probability and recruitment. <br><br>The README file further describes each uploaded file.</p>
From social categorization to implicit citizenship theories: Advancing the socio-cognitive foundations of state–citizen interactions
<p>Data for the following article: Vogel, R., Vogel, D., Liegat, M. C., & Hensel, D. (2024). From social categorization to implicit citizenship theories: Advancing the socio‐cognitive foundations of state–citizen interactions. Public Administration Review, Article puar.13844. Advance online publication. https://doi.org/10.1111/puar.13844</p>
Data for: Crall et al., Spatial fidelity of workers predicts collective response to disturbance in a social insect
<p>Dataset for: Crall et al., Spatial fidelity of workers predicts collective response to disturbance in a social insect, in final revision for Nature Communications.</p> <p>Includes two files - one behavioral data from uniquely identified worker bumblebees, and the second containing metadata for the colonies from which these data were generated (including experimental treatments, locations, sizes, etc.).</p>
Quantitative account of social interactions in a mental health care ecosystem: cooperation, trust and collective action
<p>Mental disorders have an enormous impact in our society, both in personal terms and in the economic costs associated with their treatment. In order to scale up services and bring down costs, administrations are starting to promote social interactions as key to care provision. We analyze quantitatively the importance of communities for effective mental health care, considering all community members involved. By means of citizen science practices, we have designed a suite of games that allow to probe into different behavioral traits of the role groups of the ecosystem. The evidence reinforces the idea of community social capital, with caregivers and professionals playing a leading role. Yet, the cost of collective action is mainly supported by individuals with a mental condition - which unveils their vulnerability. The results are in general agreement with previous findings but, since we broaden the perspective of previous studies, we are also able to find marked differences in the social behavior of certain groups of mental disorders. We finally point to the conditions under which cooperation among members of the ecosystem is better sustained, suggesting how virtuous cycles of inclusion and participation can be promoted in a ’care in the community’ framework.</p>
Star Wars social network
<p><strong>Star Wars social network</strong></p> <p>This dataset contains the social network of Star Wars characters extracted from movie scripts. In short, two characters are connected if they speak together within the same scene. The data contain characters and links from episodes I to VII.</p> <p>How the data were created is described in my blog posts:</p> <ul> <li><a href="http://evelinag.com/blog/2015/12-15-star-wars-social-network/index.html">The Star Wars social network</a></li> <li><a href="http://evelinag.com/blog/2016/01-25-social-network-force-awakens/index.html">Star Wars social network: Force Awakens</a></li> </ul> <p>The associated code is available in the main Github repository <a href="https://github.com/evelinag/StarWars-social-network">evelinag/StarWars-social-network</a>.</p> <p>Contents of the files are the following:</p> <ul> <li> <p><code>starwars-episode-N-interactions.json</code> contains the social network extracted from Episode N, where the links between characters are defined by the times the characters speak within the same scene.</p> </li> <li> <p><code>starwars-episode-N-mentions.json</code> contains the social network extracted from Episode N, where the links between characters are defined by the times the characters are mentioned within the same scene.</p> </li> <li> <p><code>starwars-episode-N-interactions-allCharacters.json</code> is the <code>interactions</code> network with R2-D2 and Chewbacca added in using data from <code>mentions</code> network.</p> </li> <li> <p><code>starwars-full-...</code> contain the corresponding social networks for the whole set of 6 episodes.</p> </li> </ul> <p><strong>Description of networks</strong></p> <p>The json files representing the networks contain the following information:</p> <p><strong>Nodes</strong></p> <p>The nodes contain the following fields:</p> <ul> <li>name: Name of the character</li> <li>value: Number of scenes the character appeared in</li> <li>colour: Colour in the visualization</li> </ul> <p><strong>Links</strong></p> <p>Links represent connections between characters. The link information corresponds to:</p> <ul> <li>source: zero-based index of the character that is one end of the link, the order of nodes is the order in which they are listed in the “nodes” element</li> <li>target: zero-based index of the character that is the the other end of the link.</li> <li>value: Number of scenes where the “source character” and “target character” of the link appeared together. Please not that the network is <em>undirected</em>. Which character represents the source and the target is arbitrary, they correspond only to two ends of the link.</li> </ul>
RedMed: Extending drug lexicons for social media applications
<p>Data associated with the RedMed project.</p> <p>Details for the process behind the data creation can be found in the associated paper:</p> <p><strong>Lavertu, A. & Altman, R. B. </strong>"RedMed: Extending drug lexicons for social media applications"<br> Journal of Biomedical Informatics, (2019)</p> <p><a href="https://doi.org/10.1016/j.jbi.2019.103307">https://doi.org/10.1016/j.jbi.2019.103307</a></p> <p><strong>RedMed embedding model:</strong></p> <p>Word vectors trained on comments from health related subreddits and optimized for drug synonym retrieval.</p> <p>The Redmed model was train using only social media data from Reddit and achieves comparable performance on the UMNSRS and MayoSRS similarity tasks. Vectors are 64 dimensional.</p> <p><strong><strong>redmed_model_vectors.tsv.gz - </strong></strong>Tab-separated word vectors (token\tdim1\tdim2\t...dim64)</p> <p><strong><strong>redmed_model.bin - </strong></strong>Binary word2vec file saved using gensim, can be loaded into python gensim</p> <p>Other Files:</p> <p>supp_file_1_sidebar_subreddits.txt - List of health-related subreddits based on "r/Health" and "r/Drugs" sidebars<br> supp_file_2_enrichment_based_subreddits.txt - List of health-related subreddits based on amount of health-related content<br> supp_file_3_custom_stopword_list.txt - List of stopwords based on counts derived from Reddit comments</p>
TwitCID: a Collection of Data Sets for Studies on Information Diffusion on Social Networks
<p>The TwitCID collection consists of five Twitter datasets which were extracted from the 1 percent of tweets from Twitter API. </p> <p>The Firstweek and Secondweek data set were collected during the first week and second week of January 2017 while the Iphone, Gucci and Galaxy data sets were collected from 21 September 2015 to 31 May 2017 using the keywords “iphone”, “gucci” and “galaxys” respectively. </p> <p>We publish these datasets on behalf of our academic institution – IRIT, France and for the sole purpose of non-commercial research under the license CC BY-NC-SA (Attribution-NonCommercial-ShareAlike). In accordance with Twitter's Terms of Service, we only provide identifiers of tweets. In order to collect the actual tweets in JSON, you could use the script Collect_JSONtweets.py attached.</p> <p>If you would like to use this collection, please cite our paper: </p> <p>Hoang, T. B. N., Mothe, J., & Baillon, M. (2019, September). TwitCID: a collection of data sets for studies on information diffusion on social networks. In <em>International Conference of the Cross-Language Evaluation Forum for European Languages</em> (pp. 88-100). Springer, Cham.</p>
AI validated plant observations from social media: Flickr images from central London 2011-2019
<p>This dataset is the result of using an AI image classifer to classify images of plants on social media. We believe this is the first AI validated dataset of biological records taken from social media. This represents the dawn of AI naturalists whose domain of exploration is not the outdoor world but the digital realm. These AI naturalists will trawl streams of data from all over the globe, identifying genuine images of species, and in so doing create valuable data sets that will further our understanding of the distribution of wildlife on our planet. </p> <p>This dataset contains 31,973 classifications of images taken in central London between May 2011 and September 2019 retrieved using the search term 'flower' on Flickr.com. Some images have very low classification confidence (7910 below 0.1), while others have very high confidence (3185 over 0.9). As expected given the spatial extent of the dataset many of the observations are of planted species in gardens and parks.</p> <p>August_et_al_2019.csv provides the data while metadata.txt contains a description of the data and its generation.</p> <p>An interactive visualisation of this data can be viewed at <a href="https://tomaugust.shinyapps.io/ai_flickr_data/">https://tomaugust.shinyapps.io/ai_flickr_data/</a></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
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.