Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
240
datasets available to search
ShareScore release 0.9.0
Dataset results
240 results for “social interaction”
Data from: Selective social interactions and speed-induced leadership in schooling fish
<p>Experimental datasets for the manuscript:</p> <div>Puy, A., Gimeno, E., Torrents, J., Bartashevich, P., Miguel, M. C., Pastor-Satorras, R., & Romanczuk, P. (2024). Selective social interactions and speed-induced leadership in schooling fish. <em>Proceedings of the National Academy of Sciences</em>, <em>121</em>(18), e2309733121.</div> <div> </div> <p>The datasets provide trajectories of fish. There are 2 recordings with N=39 fish (60 minutes duration) and 6 recordings with N=8 fish (30 minutes duration). The columns are as follows:</p> <ul> <li>Time [frame]: Time of the trajectory in frames.</li> <li>X_0 [px]: Position in the x-coordinate in pixels of the trajectory of individual 0.</li> <li>Y_0 [px]: Position in the y-coordinate in pixels of the trajectory of individual 0.</li> <li>X_1 [px]: Position in the x-coordinate in pixels of the trajectory of individual 1.</li> <li>Y_1 [px]: Position in the y-coordinate in pixels of the trajectory of individual 1.</li> <li>...</li> </ul> <p>Conversion to international units:</p> <ul> <li>50 frames = 1 s.</li> <li>2745 px= 100 cm.</li> </ul>
Learning to embed lifetime social behavior from interaction dynamics - Data
<p><strong>Interaction matrices and metadata used in "Learning to embed lifetime social behavior from interaction dynamics"</strong></p> <p>The following files are included:</p> <ul> <li>interactions_bn16_sparse.npz and interactions_bn19_sparse.npz: These are the interaction affinity matrices for the BN16 and BN19 datasets as described in the publication. The data is stored as compressed sparse tensors with time on the first, and the individuals on the second and third dimensions. The data was stored using the <a href="http://sparse.pydata.org">pydata/sparse</a> library 0.9.1</li> <li> <p>alive_bn16.csv and alive_bn19.csv: These files contain the dates of emergence (also corresponding to the dates they were introduced into the colonies) and heuristically determined number days alive for all individuals in the interaction matrices. Death dates were determined using a bayesian changepoint model and the number of daily detections of each individual</p> </li> <li> <p>rhythmicity_bn16.csv and rhythmicity_bn19.csv: These files contain the circadian rhythmicity values used in the evaluation of the method. The circadian rhythmicity is the <span class="math-tex">\(R^2\)</span> value of a sine with a 24 hour period fitted to the individuals' movement velocities over a three day window</p> </li> <li> <p>indices_bn16.csv and indices_bn19.csv: These files contain the mapping between the original marker IDs used during the recording of the data (which has gaps, because not all markers were used) and the sequential indices used in the interaction matrices. These files can therefore be used to look up the original ID of an individual based on it's index in the interaction matrix and vice versa</p> </li> <li> <p>time_spent_on_substrates.csv: This data was used for the mapping from factors to the proportion of time spent on various cell substrates (Figure 5). The positions of the individuals were accumulated by minute, and the column "location_descriptor_count" contains the total number of minutes on the respective day that the individual was detected</p> </li> </ul> <p>See <a href="https://doi.org/10.1101/2020.05.06.076943">10.1101/2020.05.06.076943</a> for more details about the bayesian changepoint model, circadian rhythmicity calculation, and location mapping.</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>
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>
User Study Data for Paper "A case study in designing trustworthy interactions: implications for socially assistive robotics"
<p>Experimental data collected for the user study described in Frontiers paper "A case study in designing trustworthy interactions: implications for socially assistive robotics" by Mengyu Zhong et al. Citation: <i>Zhong, Mengyu, et al. "A case study in designing trustworthy interactions: implications for socially assistive robotics." Frontiers in Computer Science 5.1152532 (2023). </i></p>
Brain activity during reciprocal social interaction investigated using conversational robots as control condition
Open the record for dataset details and reuse information.
Evolution of conditional cooperation in collective-risk social dilemma with repeated group interactions
<p>The question of how cooperation evolves and is sustained over time has been a long-standing and unresolved issue in the fields of evolutionary biology and social sciences. Previous theoretical and experimental research based on the collective-risk social dilemma game has revealed the risk that the failure of collective goals will affect the evolution of cooperation. Considering that in the real world individuals usually adjust their decisions based on environmental factors such as risk intensity and cooperation level, it is still not well understood how such conditional behaviors affect the evolution of cooperation in repeated group interactions scenario from a theoretical perspective. Here, we construct an evolutionary game model with repeated interactions, in which defectors decide whether to cooperate in subsequent rounds of the game based on whether the risk exceeds their tolerance threshold and whether the number of cooperators exceeds the collective goal in the early rounds of the game. We find that the introduction of conditional cooperation strategy can effectively promote the emergence of cooperation, especially when the risk is low. In addition, the risk threshold significantly affects the evolutionary outcomes. Furthermore, our results confirm that a high risk can promote the emergence of cooperation. Importantly, when the risk exceeds the tolerance threshold, timely adjustment of strategies by conditional cooperators is beneficial for maintaining high-level cooperation.</p>
When does antimicrobial resistance increase bacterial fitness? Effects of dosing, social interactions and frequency dependence on the benefits of AmpC β-lactamases in broth, biofilms and a gut infection model.
<p><span>One of the longstanding puzzles of antimicrobial resistance is why the frequency of resistance persists at intermediate levels.<span> </span>Theoretical explanations for the lack of fixation of resistance include cryptic costs of resistance or negative frequency-dependence but are seldom explored experimentally. <span> </span><em>β</em>-lactamases, which detoxify penicillin-related antibiotics, have well-characterized frequency-dependent dynamics driven by cheating and cooperation.<span> </span>However, bacterial physiology determines whether <em>β</em>-lactamases are cooperative and we know little about the sociality or fitness of <em>β</em>-lactamase producers in infections.<span> </span>Moreover, media-based experiments constrain how we measure fitness, and ignore important parameters such as infectivity and transmission among hosts.<span> </span>Here, we investigated the fitness effects of broad-spectrum AmpC <em>β</em>-lactamases in <em>Enterobacter cloacae</em> in broth, biofilms and gut infections in a model insect. <span> </span>We quantified frequency- and dose-dependent fitness using cefotaxime, a third-generation cephalosporin.<span> </span>We predicted that infection dynamics would be similar to those observed in biofilms, with social protection extending over a wide dose range.<span> </span>We found evidence for the sociality of <em>β</em>-lactamases in all contexts with negative frequency-dependent selection ensuring the persistence of wild-type bacteria although cooperation was less prevalent in biofilms, contrary to predictions.<span> </span>While competitive fitness in gut infections and broth had similar dynamics, incorporating infectivity into measurements of fitness in infections<em> </em>significantly affected conclusions. <span> </span>Resistant bacteria had reduced infectivity which limited the fitness benefits of resistance to infections challenged with low antibiotic doses and having low initial frequencies of resistance. <span> </span>The fitness of resistant bacteria in more physiologically tolerant states (in biofilms, in infections) could be constrained by the presence of wild-type bacteria, high antibiotic doses and limited availability of <em>β</em>-lactamases.<span> </span>One conclusion is that increased tolerance of <em>β</em> -lactams does not necessarily increase selection pressure for resistance.<span> </span>Overall, both cryptic fitness costs and frequency-dependence curtailed the fitness benefits of resistance in this study.<span> </span></span></p> <p><span> </span></p>
Replication Archive for "Teen Social Interactions and Well-being during the COVID-19 Pandemic"
<p><span>This archive includes the Stata code to replicate all results in the referenced paper.</span></p>
Data from: Status-dependent metabolic effects of social interactions in a group-living fish
<p>Social interactions can sometimes be a source of stress, but social companions can also ameliorate and buffer against stress. Stress and metabolism are closely linked, but the degree to which social companions modulate metabolic responses during stressful situations—and whether such effects differ depending on social rank—is poorly understood. To investigate this question, we studied Neolamprologus pulcher, a group-living cichlid fish endemic to Lake Tanganyika, and measured the metabolic responses of dominant and subordinate individuals when they were either visible or concealed from one another. When individuals could see each other, subordinates had lower maximum metabolic rates and tended to take longer to recover following an exhaustive chase compared to dominants. In contrast, metabolic responses of dominants and subordinates did not differ when individuals could not see one another. These findings suggest that the presence of a dominant individual has negative metabolic consequences for subordinates, even in stable social groups with strong prosocial relationships.</p>
Figure 11. Cognitive architecture of the process of social signals perception-Gestalt Processing in Human-Robot Interaction: A Novel Account for Autism Research
<p>A possible cognitive architecture and formalization of the process of learning via<br> multisensory integration is presented in figure 11. The formal description of the proposed cognitive<br> architecture, capable of interpreting social-communication signals, signs and symbols, is based on<br> multisensory integration at the level of perception, parallel processing at the level of interpretation<br> and decision making followed by verbalization, as well as performing an action (eye contact,<br> gesture, mimicking) at the level of behaviour.</p>
Interspecific social interactions shape public goods production in natural microbial communities
<p>The R code (Hesse_etal.R) descibes step by step how metal polution affects the ecology and evolution of a community-wide public good – the production of metal-detoxifying siderophores. This code accompanies the manuscript "Interspecific interactions shape public goods production in natural microbial communities" (https://www.biorxiv.org/content/10.1101/710715v1).</p> <p>The R code is divided into different sections per figure (1-5 and supplementary Figure S1). Each section first starts with reading in the appropriate data files (cvs files) and continues with statistics and plotting of figures.</p>
FIGURE 4 in Amateur paleontological societies and fossil clubs, interactions with professional paleontologists, and social paleontology in the United States
FIGURE 4. (Top) Percentage of total responses (N=40) about content and information preferences for future activities that might be mediated by FOSSIL. (Bottom) Examples of real-world (practical) skills for future activities.
FIGURE 3 in Amateur paleontological societies and fossil clubs, interactions with professional paleontologists, and social paleontology in the United States
FIGURE 3. Perceived comfort (%) of amateur respondents contacting other amateurs versus professionals. Along the x-axis, 1 represents "Not comfortable," whereas 6 is "Comfortable," and 7 is "Very Comfortable."
FIGURE 9 in Amateur paleontological societies and fossil clubs, interactions with professional paleontologists, and social paleontology in the United States
FIGURE 9. Theoretical model of the end-members and spectrum of motivations for participating in paleontology.
FIGURE 7 in Amateur paleontological societies and fossil clubs, interactions with professional paleontologists, and social paleontology in the United States
FIGURE 7. Comparison of the growth in the following modes of communication for the FOSSIL project: Facebook likes, Twitter followers, e-newsletter subscribers, Listserv subscribers, and FOSSIL project website, www.myfossil.org.
FIGURE 6. A in Amateur paleontological societies and fossil clubs, interactions with professional paleontologists, and social paleontology in the United States
FIGURE 6. A paleontological news story as a FOSSIL project Facebook post. Note the number of people reached (1,191), as well as the levels of engagement (23 likes, 4 share).
FIGURE 1 in Amateur paleontological societies and fossil clubs, interactions with professional paleontologists, and social paleontology in the United States
FIGURE 1. Theoretical learning model for social paleontology in which amateur and professional paleontologists come together via the FOSSIL project within the framework of a Community of Practice.
FIGURE 2 in Amateur paleontological societies and fossil clubs, interactions with professional paleontologists, and social paleontology in the United States
FIGURE 2. Word cloud illustrating the relative use of different words in the names of the 30 fossil societies and clubs that participated in the front-end evaluation. The size of the word relates to its frequency of occurrence.
FIGURE 5 in Amateur paleontological societies and fossil clubs, interactions with professional paleontologists, and social paleontology in the United States
FIGURE 5. Likelihood of future participation in the FOS- SIL project for amateurs and professionals who participated in our formative evaluation.
ScienceDex guides
Understand access before you commit
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.