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5,666 results for “Social”
Adapting Phrase-based Machine Translation to Normalise Medical Terms in Social Media Messages
<p>Data and supplementary information for the paper entitled "Adapting Phrase-based Machine Translation to Normalise Medical Terms in Social Media Messages" to be published at EMNLP 2015: Conference on Empirical Methods in Natural Language Processing — September 17–21, 2015 — Lisboa, Portugal.</p> <p>ABSTRACT: Previous studies have shown that health reports in social media, such as DailyStrength and Twitter, have potential for monitoring health conditions (e.g. adverse drug reactions, infectious diseases) in particular communities. However, in order for a machine to understand and make inferences on these health conditions, the ability to recognise when laymen's terms refer to a particular medical concept (i.e. text normalisation) is required. To achieve this, we propose to adapt an existing phrase-based machine translation (MT) technique and a vector representation of words to map between a social media phrase and a medical concept. We evaluate our proposed approach using a collection of phrases from tweets related to adverse drug reactions. Our experimental results show that the combination of a phrase-based MT technique and the similarity between word vector representations outperforms the baselines that apply only either of them by up to 55%.</p>
facebook social network graph
<p>This dataset is also contained in http://snap.stanford.edu/data/egonets-Facebook.html, but it is converted to one by one single graphs in this dataset.</p> <p>Graph Example:</p> <p># graph_id, graph_activity, number_of_vertices, number_of_edges</p> <p>vertex_1， vertex_2, ... , vertex_n</p> <p>vertex_1 vertex_k edge_label vertex_2 vertex_m edge_label, ..., vertex_i, vertex_j, edge_label</p>
Dataset for paper: J. A. Cerón-Guzmán and E. León (2015), Detecting Social Spammers in Colombia 2014 Presidential Election. MICAI 2015. DOI: 10.1007/978-3-319-27101-9_9
<p>Dataset for paper: J. A. Cerón-Guzmán and E. León (2015), Detecting Social Spammers in Colombia 2014 Presidential Election. The 14th Mexican International Conference on Artificial Intelligence. DOI: 10.1007/978-3-319-27101-9_9</p>
East-African Social Sciences and Humanities Journals active in 2008-2009
<p>Research Data of „East-African Social Sciences and Humanities Publishing: A Handmade Bibliometrics Approach“, Proceedings of the 21st International Conference on Science and Technology Indicators, València (Spain), September 14-16, 2016.</p> <p>Corrected second version: due to an error, the journal “Chemchemi” was not included in “1 final list merged” and “7 ceased-established”. However, this does not change the conclusions drawn in the paper.</p> <p>Abstract of the paper to be published in the proceedings: For Eastern Africa, very little information about the SSH knowledge production can be found from a European perspective. Adequate indicators like information-rich bibliographic databases that cover East-Africa-based journals and book publishers are lacking. This research in progress explores their indexing situation in detail, their development, which is closely connected to political history, their (non-)usage, and affiliations as well as career-stages of their authors. Furthermore, it also pays attention to East-Africa-based SSH researchers who use other publication venues. Any bibliometric analysis in this field needs to rely on manual data collection, otherwise it would be heavily biased. This study lays out the foundation for citation analyses, qualitative research on the publications' content and the self-description of East-African scholars against the background of an academic environment that is often described as “international”.</p>
Topical alignment in online social systems
<p>Data used in the work https://arxiv.org/abs/1707.06525.</p> <p>Published Files:</p> <p># Hashtag coocurrence graph <br> cooccurrence.txt —- each line: hashtag1 hashtag2 #cooccurrences</p> <p># Communities<br> communities.txt -- 1 line for each community</p> <p># Hashtags used by users<br> users_hashtags.json -- json file wherein, for each user, there is a list of hashtags and the number of times that he/she used it</p> <p># Edges <br> follow_friend.txt - edges from 2013</p>
Scenario delay times regarding the expansion of the transmission system in Germany based on social acceptance
<p>The data is closely related to Mester et al. 2017. Integrating Social Acceptance of Electricity Grid Expansion into Energy System Modeling: A Methodological Approach for Germany. In Wohlgemuth, V., Fuchs-Kittowski, F. and Wittmann, J. (eds.) <em>Advances and New Trends in Environmental Informatics: Stability, Continuity, Innovation</em>. Cham: Springer International Publishing, pp. 115 - 129. doi: 10.1007/978-3-319-44711-7_10.</p> <p>Each dataset contains the assumed delays in commissioning of German transmission grid projects given in years influenced by social acceptance based on three different scenarios - low, mid and high. In the attached file <em>VerNetzen-Verzoegerungszeiten-Kreise.csv </em>these<em> </em>delay times are given per district, which can be identified by their key, "Regionalschlüssel", and corresponding geo data (EPSG: 25832) of the administrative area provided by the Federal Agency for Cartography and Geodesy. © GeoBasis-DE / BKG 2014 (data was changed) Additionally other files contain scenario data for each transmission grid project. Geo data in these files is provided by the Bundesnetzagentur (data was changed).</p> <p>The dataset was created in the context of the interdisciplinary research project VerNetzen and is described in detail in the final project report: VerNetzen Degel, M., Christ, M., Grünert, J., Becker, L., Wingenbach, C., Soethe, M., Bunke, W.-D., Mester, K., und Wiese, F. (2016). <em>VerNetzen: Sozial-ökologische und technisch-ökonomische Modellierung von Entwicklungspfaden der Energiewende</em>. IZT Berlin, Europa-Universität Flensburg, Deutsche Umwelthilfe e.V., pp. 72-92, 102-105, 135-142.</p> <p><em><strong>Deutsch:</strong></em></p> <p>Die Daten stehen in engem Zusammenhang mit Mester et al. 2017. Integrating Social Acceptance of Electricity Grid Expansion into Energy System Modeling: A Methodological Approach for Germany. In Wohlgemuth, V., Fuchs-Kittowski, F. and Wittmann, J. (eds.) <em>Advances and New Trends in Environmental Informatics: Stability, Continuity, Innovation</em>. Cham: Springer International Publishing, pp. 115 - 129. doi: 10.1007/978-3-319-44711-7_10.</p> <p>Je Datensatz ist angegeben, welche akzeptanz-bedingten Verzögerungen in Jahren für die Inbetriebnahme von Übertragungsnetzausbauvorhaben in den drei Szenarien - low, mid und high - zu erwarten sind. In der Datei <em>VerNetzen-Verzoegerungszeiten-Kreise.csv </em>werden Verzögerungen je Landkreis aufgeführt. Diese können durch den Regionalschlüssel oder durch Geodaten (EPSG: 25832) des Bundesamtes für Kartographie und Geodäsie zugeordnet werden. © GeoBasis-DE / BKG 2014 (Daten geändert) Darüber hinaus enthalten die anderen Dateien Daten je Vorhaben. Die entsprechenden Geodaten in diesen Dateien wurden von der Bundesnetzagentur bereitgestellt (Daten geändert).</p> <p>Der Datensatz ist im Kontext des interdisziplinären Forschungsprojekts VerNetzen entstanden und ist ausführlich im Projektabschlussbericht beschrieben: VerNetzen Degel, M., Christ, M., Grünert, J., Becker, L., Wingenbach, C., Soethe, M., Bunke, W.-D., Mester, K., und Wiese, F. (2016). <em>VerNetzen: Sozial-ökologische und technisch-ökonomische Modellierung von Entwicklungspfaden der Energiewende</em>. IZT Berlin, Europa-Universität Flensburg, Deutsche Umwelthilfe e.V., S.72-92, S.102-105, S.135-142.</p>
Supplementary material for "Playback experiments highlight the importance of nearest-neighbor distance and social information for nest site selection in the House Martin (Delichon urbicum)"
<p><strong>Abstract</strong></p> <p>Understanding nest site selection is crucial for species conservation. Bird conservation often involves installing nesting aids to increase nest site availability and induce colonization of unoccupied sites. However, prospecting individuals must find nesting aids, which may be facilitated by social information. Here, we investigated the effectiveness of artificial nests and playback in the declining, migratory House Martin <em>Delichon urbicum</em>. We selected unoccupied sites with artificial nests along a distance gradient to occupied sites and broadcasted conspecific vocalizations during prospection times of House Martins in both the post- and the following pre-breeding periods. Visitation and colonization rates increased considerably in proximity to occupied sites. Playback during the post-breeding and pre-breeding periods enhanced visitation rates, while pre-breeding-only and post-breeding-only playback had smaller positive effects. Colonization rate increased exclusively with pre-breeding-only playback. Colonized playback and non-playback sites had similar breeding success, indicating that playback did not create ecological traps by attracting House Martins to suboptimal sites. Hence, broadcasting conspecific vocalizations informs prospecting birds of nest site availability, thereby increasing visitation, and to some degree, colonization of unoccupied House Martin sites. To boost colonization, we recommend installing artificial House Martin nests within approximately 500 meters of occupied sites and using playback of conspecific vocalizations.</p>
An empirical social vulnerability map for flood risk assessment at global scale ('GlobE-SoVI')
<p>These data were produced as part of the study "An empirical social vulnerability map for flood risk assessment at global scale ('GlobE-SoVI')" (in press in Earth's Future, https://doi.org/10.1029/2023EF003895). We provide raster data at 30 arc seconds spatial resolution (folder 'raster') and vector and table data per administrative unit (folder 'admin') of five social vulnerability variables and the final Global Empirical Social Vulnerability Index (GlobE-SoVI) calculated from the five variables. Please see 'overview_table.pdf' for names and units.</p> <p>The code for data processing and analysis is available at https://github.com/lena-reimann/GlobE-SoVI (https://doi.org/10.5281/zenodo.10671539).</p>
A distinct neurogenomic response to a tradeoff between social challenge and opportunity in male sticklebacks (Gasterosteus aculeatus)
<p>Animals frequently make adaptive decisions about what to prioritize when they are faced with multiple, conflicting demands at the same time. However, the proximate mechanisms of decision-making in the face of competing demands are not well understood. We explored this question using brain transcriptomics in a classic model system: threespined sticklebacks, where males face conflict between courtship and territorial defense. The outcome of decisions made by breeding males over whether to court mates or defend against territory intrusion are profoundly important to fitness. We characterized the behavior and brain gene expression profiles of males confronted by a tradeoff between courtship and territorial defense by comparing them to males not confronted by this tradeoff. When faced with the tradeoff, males behaviorally prioritized defense over courtship, and this decision was reflected in their brain gene expression profiles. A distinct set of genes and biological processes was recruited in the brain when males faced a tradeoff and these responses were largely non-overlapping across two brain regions. Combined, these results raise new questions about the interplay between the neural and molecular mechanisms involved in decision-making.</p>
Zebra finches increase social behavior in traffic noise: implications for urban songbirds
<p>Statistical code & datasets for "Zebra finches increase social behavior in traffic noise: implications for urban songbirds" manuscript submitted to <em>Acta ethologica. </em>Also includes audio file for traffic noise playback in described experiment. </p>
Social behavior among nocturnally migrating birds revealed by automated moonwatching
<p>Migrating birds often fly in group formations during the daytime; whereas at night, it is generally presumed that they fly singly. However, it is difficult to quantify group behavior during nocturnal migration as there are few means of directly observing interactions among individuals. We employed an automated form of moonwatching to estimate percentages of birds that appear to migrate in groups during the night within the Central Flyway of North America. We compared percentages of birds in groups across the spring and fall and examined overnight temporal patterns of group behavior. We found groups were rare in both seasons, never exceeding 10% of birds observed, and were almost nonexistent during the fall. We also observed an overnight pattern of group behavior in the spring wherein groups were more commonly detected early in the night and again just before migration activity ceased. This finding may be related to changes in species composition of migrants throughout the night, or alternatively it suggests that group formation may be associated with flocking activity on the ground as groups are most prevalent when birds begin and end a night of migration.</p>
Dataset - Understanding the software and data used in the social sciences
<p>This is a repository for a UKRI Economic and Social Research Council (ESRC) funded project to understand the software used to analyse social sciences data.</p><p>Any software produced has been made available under a BSD 2-Clause license and any data and other non-software derivative is made available under a CC-BY 4.0 International License. Note that the software that analysed the survey is provided for illustrative purposes - it will not work on the decoupled anonymised data set.</p><p>Exceptions to this are:</p><ul><li>Data from the UKRI ESRC is mostly made available under a <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">CC BY-NC-SA 4.0</a> Licence.</li><li>Data from Gateway to Research is made available under an <a href="https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/">Open Government Licence</a> (Version 3.0).</li></ul><h2>Contents</h2><ul><li>Survey data & analysis: esrc_data-survey-analysis-data.zip</li><li>Other data: esrc_data-other-data.zip</li><li>Transcripts: esrc_data-transcripts.zip</li><li>Data Management Plan: esrc_data-dmp.zip</li></ul><h3>Survey data & analysis</h3><p>The survey ran from 3rd February 2022 to 6th March 2023 during which 168 responses were received. Of these responses, three were removed because they were supplied by people from outside the UK without a clear indication of involvement with the UK or associated infrastructure. A fourth response was removed as both came from the same person which leaves us with 164 responses in the data.</p><p>The survey responses, Question (Q) Q1-Q16, have been decoupled from the demographic data, Q17-Q23. Questions Q24-Q28 are for follow-up and have been removed from the data. The institutions (Q17) and funding sources (Q18) have been provided in a separate file as this could be used to identify respondents. Q17, Q18 and Q19-Q23 have all been independently shuffled.</p><p>The data has been made available as Comma Separated Values (CSV) with the question number as the header of each column and the encoded responses in the column below. To see what the question and the responses correspond to you will have to consult the survey-results-key.csv which decodes the question and responses accordingly. </p><p><strong>A pdf copy of the survey questions is </strong><a href="https://github.com/softwaresaved/esrc-software-study/blob/main/Docs/esrc-survey.pdf"><strong>available</strong></a><strong> on GitHub.</strong></p><p>The survey data has been decoupled into:</p><ul><li>survey-results-key.csv - maps a question number and the responses to the actual question values.</li><li>q1-16-survey-results.csv- the non-demographic component of the survey responses (Q1-Q16).</li><li>q19-23-demographics.csv - the demographic part of the survey (Q19-Q21, Q23).</li><li>q17-institutions.csv - the institution/location of the respondent (Q17).</li><li>q18-funding.csv - funding sources within the last 5 years (Q18).</li></ul><p>Please note the code that has been used to do the analysis will not run with the decoupled survey data. </p><h3>Other data files included</h3><ul><li>CleanedLocations.csv - normalised version of the institutions that the survey respondents volunteered.</li><li>DTPs.csv - information on the UKRI Doctoral Training Partnerships (DTPs) scaped from the UKRI <a href="https://esrc.ukri.org/skills-and-careers/doctoral-training/doctoral-training-partnerships/doctoral-training-partnership-dtp-contacts/">DTP contacts</a> web page in October 2021.</li><li>projectsearch-1646403729132.csv.gz - data snapshot from the <a href="https://gtr.ukri.org/">UKRI Gateway to Research</a> released on the 24th February 2022 made available under an <a href="https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/">Open Government Licence</a>.</li><li>locations.csv - latitude and longitude for the institutions in the cleaned locations.</li><li>subjects.csv - research classifications for the ESRC projects for the 24th February data snapshot.</li><li>topics.csv - topic classification for the ESRC projects for the 24th February data snapshot.</li></ul><h3>Interview transcripts</h3><p>The interview transcripts have been anonymised and converted to markdown so that it's easier to process in general. List of interview transcripts:</p><ul><li>1269794877.md</li><li>1578450175.md</li><li>1792505583.md</li><li>2964377624.md</li><li>3270614512.md</li><li>40983347262.md</li><li>4288358080.md</li><li>4561769548.md</li><li>4938919540.md</li><li>5037840428.md</li><li>5766299900.md</li><li>5996360861.md</li><li>6422621713.md</li><li>6776362537.md</li><li>7183719943.md</li><li>7227322280.md</li><li>7336263536.md</li><li>75909371872.md</li><li>7869268779.md</li><li>8031500357.md</li><li>9253010492.md</li></ul><h3>Data Management Plan</h3><p>The study's Data Management Plan is provided in PDF format and shows the different data sets used throughout the duration of the study and where they have been deposited, as well as how long the SSI will keep these records. </p>
Collective synchrony of mating signals modulated by ecological cues and social signals in bioluminescent sea fireflies
<p><span>Individuals often employ simple rules that can emergently synchronise behaviour. Some collective behaviours are intuitively beneficial, but others like mate signalling in leks occur across taxa despite theoretical individual costs. Whether disparate instances of synchronous signalling are similarly organised is unknown, largely due to challenges observing many individuals simultaneously. Recording field collectives and <em>ex situ</em> playback experiments, we describe principles of synchronous bioluminescent signals produced by marine ostracods (Crustacea; Luxorina) that seem behaviorally convergent with terrestrial fireflies, and with whom they last shared a common ancestor over 500 mya. Like synchronous fireflies, groups of signalling males use visual cues (intensity and duration of light) to decide when to signal. Individual ostracods also modulate their signal based on the distance to nearest neighbours. During peak darkness, luminescent "waves" of synchronous displays emerge and ripple across the sea floor every ~60 seconds, but such periodicity decays within and between nights after the full moon. Our data reveal these bioluminescent aggregations are sensitive to both ecological and social light sources. Because the function of collective signals is difficult to dissect, evolutionary convergence, like in the synchronous visual displays of diverse arthropods, provides natural replicates to understand the generalities that produce emergent group behaviour.</span></p>
Transformation of social relationships in COVID-19 America: Remote communication may amplify political echo chambers
<p>The COVID-19 pandemic, with millions of Americans compelled to stay home and work remotely, presented an opportunity to explore the dynamics of social relationships in a predominantly remote world. Using the 1972-2022 General Social Surveys, we found that the pandemic significantly disrupted the patterns of social gatherings with family, friends, and neighbors, but only momentarily. Drawing from the nationwide ego-network surveys of 41,033 Americans from 2020 to 2022, we found that the size and composition of core networks remained stable, though political homophily increased among non-kin relationships compared to previous surveys between 1985 and 2016. Critically, heightened remote communication during the initial phase of the pandemic was associated with increased interaction with the same partisans, though political homophily decreased during the later phase of the pandemic when in-person contacts increased. These results underscore the crucial role of social institutions and social gatherings in promoting spontaneous encounters with diverse political backgrounds.</p>
Data from: Spatiotemporal-social association predicts immunological similarity in rewilded mice
<p>Environmental influences on immune phenotypes are well-documented, but our understanding of which elements of the environment affect immune systems, and how, remains vague. Behaviors, including socializing with others, are central to an individual's interaction with its environment. We therefore tracked behavior of rewilded laboratory mice of three inbred strains in outdoor enclosures and examined contributions of behavior, including associations measured from spatiotemporal cooccurrences, to immune phenotypes. We found extensive variation in individual and social behavior among and within mouse strains upon rewilding. And we found that the more associated two individuals were, the more similar their immune phenotypes were. Spatiotemporal association was particularly predictive of similar memory T and B cell profiles and was more influential than sibling relationships or shared infection status. These results highlight the importance of shared spatiotemporal activity patterns and/or social networks for immune phenotype and suggest potential immunological correlates of social life.<span><br></span></p>
EduQuick: A Dataset for Assessing Summarization of Informal Educational Content for Social Media
<p>The presented dataset is a curated collection of model-generated text for educational TikTok content, abbreviated as EduQuick. This dataset is the result of evaluating and selecting high-quality content generated by the GPT-4 model following an empirical study. It aims to provide engaging and informative summaries suitable for TikTok's educational audience.</p>
SAQI: An Ontology based Knowledge GraphPlatform for Social Air Quality Index
<p>This dataset consists of all contributions made by Social AQI (SAQI) project. The description of dataset is as below -</p> <p>Local Sensor Data (hyperlocal-air-quality-sensor-data) - contains all sensors values recorded through local neighbourhood sensors throught the length of the project <br> Locations for all these sensors are as below - In Najafgarh, Delhi, India : Jharoda Kalan, Nangli Dairy and DTC Bus terminal.<br> In Okhla : Sanjay Colony, Tekhand, Shaheen Bagh.</p> <p>Data from <a href="https://cpcb.nic.in/">Central Pollution Control Board</a> (central-air-quality-sensor-data) - Najafgarh_CPCB.csv, Okhla_CPCB.csv : Contains data provided by CPCB from Najafgarh,Delhi and Oklha, Delhi</p> <p><br> PollutionODP.owl : Ontology Design Pattern for pollution - http://ontologydesignpatterns.org/wiki/Submissions:Pollution.<br> <br> Ontology : SAQI ontology as triples (ttl), xml (rdf) and json-ld (json) serialization format<br> Ontology documentation : ontology/diagram contains figures describing ontology, ontology/documentation/saqi.html contains LODE documentation for the ontology</p> <p><br> ethnographic-survey-data - anonymized survey responses for initial pollution perception and literacy survey as well as SAQI app feedback survey.</p> <p>SHACL-shapes - for validating against SAQI ontology.</p> <p> sparql-queries - sample queries to run on our ontology.</p> <p>setup-rdf-store-script - script to setup rdf store with given data using rml mapper.</p> <p> </p> <p><br> </p>
Fig. 2 in Social Behavior and Communication in the Neotropical Cicada Fidicina mannifera (Fabricius) (Homoptera: Cicadidae)
Fig. 2. Waveforms of two signals of Fidicina mannifera. (A) One complete call; (B) Twelve pulses from a calling song. Total X axis length is 280 ms in (A) and 18 ms in (B).
Fig. 1 in Social Behavior and Communication in the Neotropical Cicada Fidicina mannifera (Fabricius) (Homoptera: Cicadidae)
Fig. 1. Audiospectrograms of four acoustic displays in the repertoire of Fidicina mannifera. (A) Song; (B) Calls, given in alternation by two males (numbers below the calls identify the caller); (C) Low-amplitude song; (D) Disturbance sound.
Fig. 3 in Social Behavior and Communication in the Neotropical Cicada Fidicina mannifera (Fabricius) (Homoptera: Cicadidae)
Fig. 3. Proportion of calls vs. songs given by male Fidicina mannifera in relation to nearestneighbor distance. Note that the relationship with distance is not linear (fitted curve is logarithmic).
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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.