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37 results for “Social traits”
Agreeableness personality trait and social information encoding
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Multilevel selection on social network traits differs between sexes in experimental populations of forked fungus beetles
<p>Both individual and group behavior can influence individual fitness, but multilevel selection is rarely quantified on social behaviors. Social networks provide a unique opportunity to study multilevel selection on social behaviors, as they describe complex social traits and patterns of interaction at both the individual and group levels. In this study, we used contextual analysis to measure the consequences of both individual network position and group network structure on individual fitness in experimental populations of forked fungus beetles (<em>Bolitotherus</em> <em>cornutus</em>) with two different resource distributions. We found that males with high individual connectivity (strength) and centrality (betweenness) had higher mating success. However, group network structure did not influence their mating success. Conversely, we found that individual network position had no effect on female reproductive success but that females in populations with many social interactions experienced lower reproductive success. The strength of individual-level selection in males and group-level selection in females intensified when resources were clumped together, showing that habitat structure influences multilevel selection. Individual and emergent group social behavior both influence variation in components of individual fitness but impact male mating success and female reproductive success differently, setting up intersexual conflicts over patterns of social interactions at multiple levels. </p>
Autistic traits relate to reduced reward sensitivity in learning from social point-light displays (PLDs)
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Homophily in social and demographic traits predict association patterns in female western and mountain gorillas
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Multilevel selection on social network traits differs between sexes in experimental populations of forked fungus beetles
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Data from: Genetic and environmental effects on morphological traits of social phenotypes in wasps
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Using social media and personality traits to assess software developers' emotions
<p>Companion DATA of the paper "Using social media and personality traits to assess software developers’ emotions" submitted to the IEEE Access journal, 2022.</p> <p>The folders contain:</p> <p><br> /analysis<br> analyzed_tweets_by_psychologists.csv: file containing the manual analysis done by psychologists<br> analyzed_tweets_by_participants.csv: file containing the manual analysis done by participants<br> analyzed_tweets_by_psychologists_solved_divergencies.csv: file containing the manual analysis done by psychologists over 51 divergent tweets' classifications</p> <p><br> /dataset<br> alldata.json: contains the dataset used in the paper</p> <p><br> /notebooks<br> General - Charts.ipynb: notebook file containing all charts produced in the study, including those in the paper<br> Statistics - Lexicons and Ensembles.ipynb: notebook file with the statistics for the five lexicons and ensembles used in the study<br> Statistics - Linear Regression.ipynb: notebook file with the multiple linear regression results</p> <p> Statistics - Polynomial Regression: notebook file with the polynomial regression results<br> Statistics - Psychologists versus Participants.ipynb: notebook file with the statistics between the psychologists and participants manual analysis<br> Statistics - Working x Non-working.ipynb: notebook file containing the statistical analysis for the tweets posted during work period and those posted outside of working period</p> <p><br> /surveys<br> Demographic_Survey.pdf: survey inviting participants to enroll in the study. We collect demographic data and participants' authorization to access their public Tweet posts<br> Demographic_Survey_answers.xlsx: participants' demographic survey answers<br> ibf_pt_br.doc: the Portuguese version of the Big Five Inventory (BFI) instrument to infer participants' Big Five polarity traits<br> ibf_answers.xlsx: participantes' and psychologists' answers for BFI</p> <p><br> ------------------------------------------------------------</p> <p><br> We have removed from dataset any sensible data to protect participants' privacy and anonymity.<br> We have removed from demographic survey answers any sensible data to protect participants' privacy and anonymity.</p>
Social selection analysis reveals limited effect of neighbors' traits in Tree swallows
<p>Social interactions are ubiquitous in nature and can shape fitness of individuals through social selection. This type of selection arises when phenotypes of neighbors influence the fitness of a focal individual. Quantifying social selection is crucial to better characterise the overall selective landscape. For example, if intraspecific competition is strong, traits that are beneficial for an individual could be detrimental for competitors. In this study, we quantified social selection acting on four key ecological traits (body mass, wing length, laying date and clutch size) in wild Tree swallow (<em>Tachycineta bicolor)</em> females. We used reproductive success measured at three stages throughout the breeding season as fitness proxies to assess selection acting at those decisive moments. We also quantified the effects of environment on selection using measures of conspecifics' density, type of agricultural landscape and presence of interspecific competitors. Overall, we found no strong evidence of social selection on these traits in our study system, although there were marginally non-significant selection gradients suggesting positive effect of larger neighbors. Environmental variables affected reproductive success but did not affect social selection gradients. Our study calls for more social selection estimates to be reported across environments to better understand its importance in wild populations.</p>
Using social media and personality traits to assess software developers' emotions
<p>Companion DATA</p> <p>Title:<br> Using social media and personality traits to assess software developers' emotions</p> <p>Authors: <br> Leo Moreira Silva<br> Marília Gurgel Castro<br> Miriam Bernardino Silva<br> Milena Nestor Santos<br> Uirá Kulesza<br> Margarida Lima<br> Henrique Madeira</p> <p>Journal:<br> PeerJ Computer Science</p> <p>Github:<br> <a href="https://github.com/leosilva/peerj_computer_science_2022">https://github.com/leosilva/peerj_computer_science_2022</a></p> <p>------------------------------------------------------------<br> The folders contain:</p> <p>Experiment_Protocol.pdf: document that present the protocol regarding recruitment protocol, data collection of public posts from Twitter, criteria for manual analysis, and the assessment of Big Five factors from participants and psychologists. English version.</p> <p><br> /analysis<br> analyzed_tweets_by_psychologists.csv: file containing the manual analysis done by psychologists<br> analyzed_tweets_by_participants.csv: file containing the manual analysis done by participants<br> analyzed_tweets_by_psychologists_solved_divergencies.csv: file containing the manual analysis done by psychologists over 51 divergent tweets' classifications</p> <p><br> /dataset<br> alldata.json: contains the dataset used in the paper</p> <p>/ethics_committee<br> committee_response_english_version.pdf: contains the acceptance response of Research Ethics and Deontology Committee of the Faculty of Psychology and Educational Sciences of the University of Coimbra. English version.<br> committee_response_original_portuguese_version: contains the acceptance response of Research Ethics and Deontology Committee of the Faculty of Psychology and Educational Sciences of the University of Coimbra. Portuguese version.<br> committee_submission_form_english_version.pdf: the project submitted to the committee. English version.<br> committee_submission_form_original_portuguese_version.pdf: the project submitted to the committee. Portuguese version.<br> consent_form_english_version.pdf: declaration of free and informed consent fulfilled by participants. English version.<br> consent_form_original_portuguese_version.pdf: declaration of free and informed consent fulfilled by participants. Portuguese version.<br> data_protection_declaration_english_version.pdf: personal data and privacy declaration, according to European Union General Data Protection Regulation. English version.<br> data_protection_declaration_original_portuguese_version.pdf: personal data and privacy declaration, according to European Union General Data Protection Regulation. Portuguese version.</p> <p>/notebooks<br> General - Charts.ipynb: notebook file containing all charts produced in the study, including those in the paper<br> Statistics - Lexicons and Ensembles.ipynb: notebook file with the statistics for the five lexicons and ensembles used in the study<br> Statistics - Linear Regression.ipynb: notebook file with the multiple linear regression results<br> Statistics - Polynomial Regression.ipynb: notebook file with the polynomial regression results<br> Statistics - Psychologists versus Participants.ipynb: notebook file with the statistics between the psychologists and participants manual analysis<br> Statistics - Working x Non-working.ipynb: notebook file containing the statistical analysis for the tweets posted during work period and those posted outside of working period</p> <p><br> /surveys<br> Demographic_Survey_english_version.pdf: survey inviting participants to enroll in the study. We collect demographic data and participants' authorization to access their public Tweet posts. English version.<br> Demographic_Survey_portuguese_version.pdf: survey inviting participants to enroll in the study. We collect demographic data and participants' authorization to access their public Tweet posts. Portuguese version.<br> Demographic_Survey_answers.xlsx: participants' demographic survey answers<br> ibf_pt_br.doc: the Portuguese version of the Big Five Inventory (BFI) instrument to infer participants' Big Five polarity traits.<br> ibf_en.doc: translation in English of the Portuguese version of the Big Five Inventory (BFI) instrument to infer participants' Big Five polarity traits.<br> ibf_answers.xlsx: participantes' and psychologists' answers for BFI</p> <p><br> ------------------------------------------------------------</p> <p>We have removed from dataset any sensible data to protect participants' privacy and anonymity.<br> We have removed from demographic survey answers any sensible data to protect participants' privacy and anonymity.</p>
Data from: Trait-specific indirect effects underlie variation in the response of spiders to cannibalistic social partners
<p><span>Organisms may respond in different ways to the risk posed by conspecifics, but the cause of such variation remains elusive. Here, we use a half-sib/full-sib design to evaluate the contribution of (indirect) genetic or environmental effects to the behavioral response of the cannibalistic wolf spider <em>Lycosa</em> <em>fasciiventris</em> (Dufour, 1835) towards conspecific cues. Spiders showed variation in relative </span><span>occupancy time, activity, and velocity on patches with or without conspecific cues, but direct genetic variance was only found for occupancy time. These three traits were correlated and could be lumped in a principal component: spiders spending more time in patches with conspecific cues moved less and at a lower rate in those areas. Genetic and/or environmental components of carapace width and weight loss in the social partner were significantly correlated with the principal component of focal individuals. Individual </span><span>Variation in these traits may reflect the quality and/or quantity of cues produced by social partners, hence focal individuals were likely behaving along a continuum of strategies in response to the risk posed by social partners. Therefore, environmental and genetic trait variation in the social partners may be key to maintain trait diversity in focal individuals, even in the absence of direct genetic variation.</span></p>
Using social media and personality traits to assess software developers' emotional polarity
<p>Companion DATA</p> <p>Title:<br> Using social media and personality traits to assess software developers' emotional polarity</p> <p>Authors: <br> Leo Moreira Silva<br> Marília Gurgel Castro<br> Miriam Bernardino Silva<br> Milena Santos<br> Uirá Kulesza<br> Margarida Lima<br> Henrique Madeira</p> <p>Journal:<br> PeerJ Computer Science</p> <p>Github:<br> <a href="https://github.com/leosilva/peerj_computer_science_2022">https://github.com/leosilva/peerj_computer_science_2022</a></p> <p>------------------------------------------------------------<br> The folders contain:</p> <p>Experiment_Protocol.pdf: document that present the protocol regarding recruitment protocol, data collection of public posts from Twitter, criteria for manual analysis, and the assessment of Big Five factors from participants and psychologists. English version.</p> <p><br> /analysis<br> analyzed_tweets_by_psychologists.csv: file containing the manual analysis done by psychologists<br> analyzed_tweets_by_participants.csv: file containing the manual analysis done by participants<br> analyzed_tweets_by_psychologists_solved_divergencies.csv: file containing the manual analysis done by psychologists over 51 divergent tweets' classifications</p> <p><br> /dataset<br> alldata.json: contains the dataset used in the paper</p> <p>/ethics_committee<br> committee_response_english_version.pdf: contains the acceptance response of Research Ethics and Deontology Committee of the Faculty of Psychology and Educational Sciences of the University of Coimbra. English version.<br> committee_response_original_portuguese_version: contains the acceptance response of Research Ethics and Deontology Committee of the Faculty of Psychology and Educational Sciences of the University of Coimbra. Portuguese version.<br> committee_submission_form_english_version.pdf: the project submitted to the committee. English version.<br> committee_submission_form_original_portuguese_version.pdf: the project submitted to the committee. Portuguese version.<br> consent_form_english_version.pdf: declaration of free and informed consent fulfilled by participants. English version.<br> consent_form_original_portuguese_version.pdf: declaration of free and informed consent fulfilled by participants. Portuguese version.<br> data_protection_declaration_english_version.pdf: personal data and privacy declaration, according to European Union General Data Protection Regulation. English version.<br> data_protection_declaration_original_portuguese_version.pdf: personal data and privacy declaration, according to European Union General Data Protection Regulation. Portuguese version.</p> <p>/notebooks<br> General - Charts.ipynb: notebook file containing all charts produced in the study, including those in the paper<br> Statistics - Lexicons and Ensembles.ipynb: notebook file with the statistics for the five lexicons and ensembles used in the study<br> Statistics - Linear Regression.ipynb: notebook file with the multiple linear regression results<br> Statistics - Polynomial Regression.ipynb: notebook file with the polynomial regression results<br> Statistics - Psychologists versus Participants.ipynb: notebook file with the statistics between the psychologists and participants manual analysis<br> Statistics - Working x Non-working.ipynb: notebook file containing the statistical analysis for the tweets posted during work period and those posted outside of working period</p> <p><br> /surveys<br> Demographic_Survey_english_version.pdf: survey inviting participants to enroll in the study. We collect demographic data and participants' authorization to access their public Tweet posts. English version.<br> Demographic_Survey_portuguese_version.pdf: survey inviting participants to enroll in the study. We collect demographic data and participants' authorization to access their public Tweet posts. Portuguese version.<br> Demographic_Survey_answers.xlsx: participants' demographic survey answers<br> ibf_pt_br.doc: the Portuguese version of the Big Five Inventory (BFI) instrument to infer participants' Big Five polarity traits.<br> ibf_en.doc: translation in English of the Portuguese version of the Big Five Inventory (BFI) instrument to infer participants' Big Five polarity traits.<br> ibf_answers.xlsx: participantes' and psychologists' answers for BFI</p> <p><br> ------------------------------------------------------------</p> <p>We have removed from dataset any sensible data to protect participants' privacy and anonymity.<br> We have removed from demographic survey answers any sensible data to protect participants' privacy and anonymity.</p>
Data from: Trait-specific indirect effects underlie variation in the response of spiders to cannibalistic social partners
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Data and code from: Climate and parasite pressure jointly shape traits mediating the coevolution between an ant social parasite and its host
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The evolutionary demise of a social interaction: experimentally induced loss of traits involved in the supply and demand of care
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Social selection analysis reveals limited effect of neighbors’ traits in Tree swallows
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Data set for: Behavioral traits that define social dominance are the same that reduce social influence in a consensus task
<p>Dominant individuals are often most influential in their social groups, affecting movement, opinion, and performance across species and contexts. Yet behavioral traits like aggression, intimidation, and coercion, which are associated with and in many cases define dominance, can be socially aversive. The traits that make dominant individuals influential in one context may therefore reduce their influence in other contexts. Here we examine this association between dominance and influence using the cichlid fish <i>Astatotilapia burtoni</i>, comparing the influence of dominant and subordinate males during normal social interactions and in a more complex group-consensus association task. We find that phenotypically dominant males are aggressive, socially central, and that these males have a strong influence over normal group movement, whereas subordinate males are passive, socially peripheral, and have little influence over normal movement. However, subordinate males have the greatest influence in generating group-consensus during the association task. Dominant males are spatially distant and have lower signal-to-noise ratios of informative behavior in the association task, potentially interfering with their ability to generate group-consensus. In contrast, subordinate males are physically close to other group members, have a high signal-to-noise ratio of informative behavior, and equivalent visual connectedness to their group as dominant males. The behavioral traits that define effective social influence are thus highly context-specific and can be dissociated with social dominance. Thus, processes of hierarchical ascension in which the most aggressive, competitive, or coercive individuals rise to positions of dominance may be counter-productive in contexts where group-performance is prioritized.</p>
Male-male behavioral interactions drive social-dominance mediated differences in ejaculate traits
<p>Higher social status is expected to result in fitness benefits as it secures access to potential mates. In promiscuous species, male reproductive success is also determined by an individual's ability to compete for fertilization after mating by producing high quality ejaculates. However, the complex relationship between a male's investment in social status and ejaculates remains unclear. Here we examine how male social status influences ejaculate quality under a range of social contexts in the pygmy halfbeak <i>Dermogenys </i>cf.<i> collettei</i>, a small, group-living, internally fertilizing freshwater fish. We show that male social status influences ejaculate traits, both in the presence and absence of females. Dominant males produced faster swimming and more viable sperm, two key determinants of ejaculate quality, but only under conditions with frequent male-male behavioral interactions. When male-male interactions were experimentally reduced through the addition of a refuge, differences in ejaculate traits of dominant and subordinate males disappeared. Furthermore, dominant males were in better condition, growing faster and possessing larger livers, highlighting a possible condition-dependence of competitive traits. Contrary to expectations, female presence or absence did not affect sperm swimming speed or testes mass. Together, these results suggest a positive relationship between social status and ejaculate quality in halfbeaks,<i> </i>and highlight that the strength of behavioral interactions between males is a key driver of social-status dependent differences in ejaculate traits.</p>
Training dataset for marmo3Dpose, related to the paper entitled "Deciphering social traits and pathophysiological conditions from natural behaviors in common marmosets"
<p>The training dataset for marmosets' 3D pose estimation developed for Kaneko and Matsumoto et al. 2024: Deciphering social traits and pathophysiological conditions from natural behaviors in common marmosets.</p> <p>Please visit</p> <p>Github: <a href="https://github.com/PrimatoModelling/marmo3Dpose">https://github.com/PrimatoModelling/marmo3Dpose</a></p> <p>Journal article: <a href="https://www.cell.com/current-biology/fulltext/S0960-9822(24)00676-6">https://www.cell.com/current-biology/fulltext/S0960-9822(24)00676-6</a></p>
Intrinsic traits, social context, local environment, and home range size and fidelity data from a field study of sleepy lizards, 2009 - 2017
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Data from: Ecological divergence, adaptive diversification, and the evolution of social signaling traits: an empirical study in arid Australian lizards
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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.
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DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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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.
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