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.
26
datasets available to search
ShareScore release 0.9.0
Dataset results
26 results for “Twitch”
Emotes-2-Vec: A Large Scale Embedding of Twitch Chat Data
<p>These are the data and resources used for a Twitch Emote recommendation system using a Word2Vec model. The nature and exploration of the data is described in Emotes-2-Vec: A Large Scale Embedding of Twitch Chat Data. To protect the privacy of the users whose messages were scraped to build this corpus, names and timestamps have been removed and only the message bodies are included. However, a tutorial for this project is included on the project GitHub: https://github.com/KoroshM/Emote-Recommender.<br> <br> embeddings.tsv and labeled_metadata.tsv may be used in TensorFlow's embedding projector to visualize the embedding space.<br> <br> Note: Model files are the following:<br> embeddings.tsv<br> labeled_metadata.tsv<br> model<br> model.model**<br> model.wv.vectors.npy</p> <p>**Located here: https://drive.google.com/drive/folders/1RZC4JA4CpAcwoo6dOwq_jobTd6dNi_n2?usp=sharing</p>
Expression and function of Twitch-2B in the granulosa cells of mouse ovarian follicles
<p>Briefly, antral follicles were dissected from 23- to 26-d-old <em>RR8; Bact_Cre mice</em>. Follicles were cultured for 24–30 h on organotypic membranes (Millipore; cat. No. PICMORG50) in the presence of follicle-stimulating hormone. The follicle was held in a perfusion slide consisting of a plastic slide (ibidi) and a glass coverslip and assembled using silicon grease. The slide was constructed such that medium containing ovine LH (National Hormone and Peptide Program; 10 μg/mL) could be perfused through a 200-μm-deep channel holding the follicle. Temperature was maintained at 30–34 °C, by use of a warm air blower (Nevtek). Preovulatory Follicles were imaged using a Zeiss Pascal confocal microscope with a 40X/1.2 NA objective. Images were collected every 10 seconds. Measurements were corrected for autofluorescence and for spectral bleed-through of CFP into the YFP channel. Ratios were calculated by dividing the mean CFP intensity in each region of interest by the mean YFP intensity. Data analysis was done using ImageJ and Excel software. Data is representative of 4 follicles.</p>
Replication data for Nematzadeh et al. "Information Overload in Group Communication: From Conversation to Cacophony in the Twitch Chat"
<p>A subset of the chat logs dump from Twitch used in this work is provided, to help replicate the central findings of this work (<a href="https://doi.org/10.5281/zenodo.1182793">https://doi.org/10.5281/zenodo.1182793</a>). Data are aggregated and include the number of messages posted in each channel and the number of users posting them, sampled at intervals of 5 minutes. To protect the identity of the users in this data collection, message contents and user names are not included in this dataset. Stream names have been replaced with numeric IDs. <br> No additional filtering or data cleaning operation has been applied to this data. Replication code is available on Github (<a href="https://github.com/glciampaglia/twitch-overload-replication">https://github.com/glciampaglia/twitch-overload-replication</a>).</p>
Actividad de Chat de Twitch de 6 streamers hispanohablantes (Diciembre de 2022)
<p>Base de datos generada a partir del raspado de mensajes (chat-scrapping) de los canales de Twitch de los streamers Illojuan, Ibai, Auronplay, Iamcristinini, Staryuuki y Rivers_gg durante un periodo de 10 días (entre el 11 de diciembre y 21 de diciembre de 2022).</p>
Efficacy and Safety Study of Botulinum Toxin Type A Against Placebo to Treat Abnormal Contraction or Twitch of the Eyelid
ClinicalTrials.gov study NCT01896895. IPD Sharing: Not stated. Countries: 3. Publications: 3.
Juvenile and adult sea Lamprey behaviour (twitch and movement)
Open the record for dataset details and reuse information.
Twitch Plays Pokemon Dataset
<p>The dataset, titled the Twitch Plays Pokemon Dataset, contains 37.8 million IRC chat messages. It contains IRC chat log data for messages made between February 2, 2014 and April 23, 2014 (68 days). Each line denotes a single IRC chat message.</p> <p>Sample of the dataset:</p> <pre><code><date>2014-02-14</date><time>08:17:32</time><user>medicblue</user><msg>a</msg> <date>2014-02-14</date><time>08:17:32</time><user>murderousburger</user><msg>rare candy, RARE CANDY</msg> <date>2014-02-14</date><time>08:17:32</time><user>milk2978</user><msg>B</msg> <date>2014-02-14</date><time>08:17:32</time><user>mrtiktalik</user><msg>b</msg> <date>2014-02-14</date><time>08:17:32</time><user>dualhammers</user><msg>b</msg> <date>2014-02-14</date><time>08:17:32</time><user>shares5</user><msg>YES</msg> <date>2014-02-14</date><time>08:17:32</time><user>orangerust</user><msg>start</msg> <date>2014-02-14</date><time>08:17:32</time><user>snowiee</user><msg>a</msg> <date>2014-02-14</date><time>08:17:33</time><user>duroate</user><msg>down</msg> <date>2014-02-14</date><time>08:17:33</time><user>crypticcraig</user><msg>up</msg> <date>2014-02-14</date><time>08:17:33</time><user>doug2725</user><msg>LOL HELIX FOSSIL WENT BACK THAT FAR</msg></code></pre> <p><strong>Abstract</strong></p> <p>With the increasing importance of online communities, discussion forums, and customer reviews, Internet “trolls” have proliferated thereby making it difficult for information seekers to find relevant and correct information. In this paper, we consider the problem of detecting and identifying Internet trolls, almost all of which are human agents. Identifying a human agent among a human population presents significant challenges compared to detecting automated spam or computerized robots. To learn a troll’s behavior, we use contextual anomaly detection to profile each chat user. Using clustering and distance-based methods, we use contextual data such as the group’s current goal, the current time, and the username to classify each point as an anomaly. A user whose features significantly differ from the norm will be classified as a troll. We collected 38 million data points from the viral Internet fad, Twitch Plays Pokemon. Using clustering and distance-based methods, we develop heuristics for identifying trolls. Using MapReduce techniques for preprocessing and user profiling, we are able to classify trolls based on 10 features extracted from a user’s lifetime history.</p> <p>You can view the full technical paper here: <a href="https://arxiv.org/abs/1902.06208">https://arxiv.org/abs/1902.06208</a></p> <p><strong>Source Code</strong></p> <p>Code related to this dataset can be found at: <a href="https://github.com/ahaque/twitch-troll-detection">https://github.com/ahaque/twitch-troll-detection</a></p>
Movies of Pseudomonas aeruginosa twitching
<p><strong><span>Movie S1. </span></strong><span>Bacteria twitching in the confined condition. It can be clearly seen that some of the bacteria exhibit obvious twitching movements while others are stationary. The playback speed of the video is 10 times the actual speed.</span></p> <p><strong><span>Movie S2. </span></strong><span>Bacteria twitching in the free condition. The playback speed of the video is 10 times the actual speed.</span></p>
FIGURE 1. Anathallis amazonica A. Flowering habit with oblanceolate leaves. B. Fruiting habit with elliptic leaves. C. Tridenticulate leaf apex. D. Acute distended leaf apex. E. Acute twitched leaf apex. F in A new Anathallis (Orchidaceae: Pleurothallidinae) from the Brazilian Amazon
FIGURE 1. Anathallis amazonica A. Flowering habit with oblanceolate leaves. B. Fruiting habit with elliptic leaves. C. Tridenticulate leaf apex. D. Acute distended leaf apex. E. Acute twitched leaf apex. F. Detail of the inflorescence. G. Dissected perianth. H. Lip ciliate on the base (J. da Cruz 242). I. Lip entirely ciliate (J. da Cruz 240). J. Lip not ciliate (J. da Cruz 243). K. Column. Drawn by Regina Carvalho.
Cervical Paraspinal Muscle Twitching and Cervical Facet Radiofrequency Ablation Outcomes
ClinicalTrials.gov study NCT05450679. IPD Sharing: NO. Countries: 1. Publications: 12.
Postoperative Muscular Pain, ETOIMS (Electrical Twitch Obstructive Intramuscular Stimulation)
ClinicalTrials.gov study NCT03619343. IPD Sharing: NO. Countries: 1. Publications: 1.
Shortening of the Twitch Stabilization Period by Tetanic Stimulation in Acceleromyography in Children and Young Adults
ClinicalTrials.gov study NCT02552875. IPD Sharing: Not stated. Countries: 1. Publications: 9.
Influence of Trigger Threshold on Controlled Twitch Mouth Pressure
ClinicalTrials.gov study NCT01891942. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Multifidus Muscle Twitch on the Prognosis of Lumbar Medial Branch RF
ClinicalTrials.gov study NCT02580383. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Data from: Selection experiments reveal trade-offs between swimming and twitching motilities in Pseudomonas aeruginosa
Bacteria possess a range of mechanisms to move in different environments, and these mechanisms have important direct and correlated impacts on the virulence of opportunistic pathogens. Bacteria use two surface organelles to facilitate motility: a single polar flagellum, and type IV pili, enabling swimming in aqueous habitats and twitching along hard surfaces, respectively. Here, we address whether there are trade-offs between these motility mechanisms, and hence whether different environments could select for altered motility. We experimentally evolved initially isogenic Pseudomonas aeruginosa under conditions which favoured the different types of motility, and found evidence for a trade-off mediated by antagonistic pleiotropy between swimming and twitching. Moreover, changes in motility resulted in correlated changes in other behaviours, including biofilm formation and growth within an insect host. This suggests environmental origins of a particular motile opportunistic pathogen could predictably influence motility and virulence.
Data from: Selection experiments reveal trade-offs between swimming and twitching motilities in Pseudomonas aeruginosa
Open the record for dataset details and reuse information.
Murine fast-twitch muscle: two-week progression of denervation atrophy
GEO Series GSE1893. Mus musculus. 10 samples. Type: Expression profiling by array.
Characterization of two Acinetobacter baumannii rifampin-spontaneous mutants lacking twitching motility
GEO Series GSE73193. Acinetobacter baumannii; Acinetobacter baumannii ATCC 17978. 4 samples. Type: Expression profiling by array.
The Pseudomonas aeruginosa PilSR two-component system regulates both twitching and swimming motilities
GEO Series GSE112597. Pseudomonas aeruginosa PAK. 9 samples. Type: Expression profiling by high throughput sequencing.
The secreted factor TSK maintains slow-twitch myofiber integrity and exercise endurance and contributes to muscle regeneration
GEO Series GSE193089. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
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.