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444
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ShareScore release 0.9.0
Dataset results
444 results for “social networks”
Data from: Impact of repeated exposures on information spreading in social networks
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Data from: Mortality risk and social network position in resident killer whales: sex differences and the importance of resource abundance
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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 from: The evolution of generalized reciprocity on social interaction networks
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Wild mice with different social network sizes vary in brain gene expression
GEO Series GSE148075. Mus musculus. 86 samples. Type: Expression profiling by high throughput sequencing.
SOCIAL NETWORK TEXT CLASSIFICATION ALGORITHM AND SOFTWARE TOOL
<p><em><span>In this article, today's information in social networks, global information flows and algorithms for their analysis, research in this regard and their effects are studied. Recent effective algorithms are presented and the procedure for their use is shown.</span></em></p>
Enhancing Family Based Treatment of Childhood Obesity Through Social Networks
ClinicalTrials.gov study NCT02206529. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Walking in Pregnancy (WiP) - a Social Networking Physical Activity Intervention for Pregnant Obese Women
ClinicalTrials.gov study NCT03307733. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Do Network Centrality Predict Overall Depression Symptom Reduction With Lifting of Social Distancing Protocols?
ClinicalTrials.gov study NCT04444713. IPD Sharing: Not stated. Countries: 0. Publications: 0.
A Survey on the Role and Benefits of Online Social Networks on Filipino Patients With Psoriasis
ClinicalTrials.gov study NCT01465061. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Social network position is a major predictor of ant behaviour, microbiota composition, and brain gene expression
GEO Series GSE232770. Camponotus fellah. 299 samples. Type: Expression profiling by high throughput sequencing.
YOUTH ENGAGEMENT: PERSONAL MOTIVATIONS AND POSITION IN SOCIAL NETWORKS
<p>Data to analyze the social networks and motivations like predictors of social participation. University students (N = 263) estimated in an on-line survey the likelihood of their future engagement in several types of social participation. The students also estimated their possible motivations, and indicated an approximate number of their social contacts already involved in each type of participation. Based on this latter measure we were able to estimate the participants’ centrality degree in their social networks</p>
Gut microbiome strain-sharing within isolated village social networks (Social Network)
<h2><strong>Abstract</strong></h2> <p>When humans assemble into face-to-face social networks, they create an extended environment that permits exposure to the microbiome of other people, thereby shaping the composition and diversity of the microbiome at individual and population levels. Here, we use comprehensive social network mapping and detailed microbiome sequencing data in 1,787 adults within 18 isolated villages in Honduras to investigate the relationship between social network structure and gut microbiome composition. Using both species-level and strain-level data, we show that microbial sharing occurs between many relationship types, notably including non-familial and non-household connections. Using strain-sharing data alone, we can confidently predict a wide variety of relationship types (AUC ~0.72). This strain-level sharing extends to second-degree social connections in a network, suggesting the relevance of the extended network with respect to microbiome composition. We also observe that socially central individuals are more microbially similar to the overall village than socially peripheral individuals. Using a subset of 301 people in 4 villages whose microbiome was also measured 2 years later, we observed greater convergence in strain-sharing in connected versus otherwise similar unconnected co-villagers. Finally, we observe that clusters of both species and strains occur within clusters of people in the village social networks, providing the social niches within which microbiome biology and phenotypic impact are manifested.</p> <h2><strong>Data Description</strong></h2> <p>Social-network data for the 1,787 participants in the study. Each line identifies a tie between two individuals ('ego' and 'alter') and the type of the relationship between the individuals.</p>
Large-scale analysis of grooming in modern social networks
<p>We provide a large-scale dataset of the messages exchanged publicly by the streamers and viewers during the live broadcasts of users identified as adult content producers from the <a href="https://www.liveme.com/">LiveMe</a> platform, a major Social Live Streaming Service (SLSS). The dataset comprises 39,382,838 chat messages exchanged by 1,428,284 users, in the context of 293,271 live broadcasts during a period of approximately two years, from July 2016 to June 2018. The analysis of this dataset can be found in our paper <strong><em>"Large-scale analysis of grooming in modern social networks" </em></strong>(<a href="https://arxiv.org/abs/2004.08205">arXiv:2004.08205</a> [cs.SI]).</p>
dataset related to article " Social Network and Environment as determinants of diability and quality of life in aging: results from an italian study"
<p>The “TAPAS in Aging” database includes data related to socio-demographic information, health condition, quality of life, social network and environment of people aged more than 50 years in Lombardy region.</p>
Decision Analysis in e-Cognocracy using Dynamic Social Networks
<p>Poser presented to the ICDSST 2020 Conference, International Conference on Decision Support System Technologies, Zaragoza (Spain), May 21-23 2020.</p>
Social Networks, Cooperative Breeding, and the Human Milk Microbiome: data release
<p>Social Networks, Cooperative Breeding, and the Human Milk Microbiome</p>
Data and Script for Network nestedness in primates: a structural constraint or a biological advantage of social complexity?
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Social Networks that Matter: explaining the civic engagement of university students
<p>Young people's social participation has numerous benefits and universities can play an important role in promoting it. The aim of this study is to broaden our understanding of the impact of social relationships on the development of social participation among university students. We also aimed to determine to what extent previous social participation experiences may modulate said impact. A total of 827 undergraduate students completed a questionnaire assessing their previous experience with social participation, the likelihood of their engaging in social participation in the future and the composition of their social networks, distinguishing between contacts on the basis of the type of relationship (relatives, friends or acquaintance) and its context (on or off campus).</p>
Dataset for Analyzing Social Network Posts and Responses Written in Hebrew from the Political Field
<p>To collect the dataset from Israel’s most popular social network, we employed the services of an information retrieval company. The data was collected from January 2020 to December 2021; every two weeks we obtained the most popular post (based on the number of comments) for each politician. We focused on the most influential party leaders on the right, left, and center of Israel’s political spectrum. We have published the dataset for the benefit of the academic research community.</p> <p>We describe the columns based on their names:</p> <ul> <li>Index – A unique identifier assigned to each row in the dataset by a sequential number.</li> <li>Sub Index – A secondary index assigned to ’Index’ representing a sub comment (a comment made to another comment).</li> <li>Name – The name of the person who wrote the comment, also known as the commenter.</li> <li>Profile ID – A unique identifier assigned to the commenter’s Facebook profile.</li> <li>Date – The date that has been recorded when the comment was published on Facebook.</li> <li>Likes – The number of likes received for a comment.</li> <li>Comment – The content of the comment.</li> <li>URL – The web address or link associated with the comment.</li> <li>Post ID – A unique identifier assigned to a specific post.</li> <li>Politician Name – The name of the politician who wrote the post.</li> <li>Comment ID – A unique identifier assigned to a specific comment.</li> <li>Is Media – A binary feature that indicates where some media (e.g., picture or video) has been part of the user’s comment.</li> </ul>
ScienceDex guides
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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.