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.
61
datasets available to search
ShareScore release 0.9.0
Dataset results
61 results for “Twitter data”
Data from: Quantifying crowd size with mobile phone and Twitter data
Open the record for dataset details and reuse information.
Data from: Estimating mobile traffic demand using Twitter
Open the record for dataset details and reuse information.
Mining the first 100 days: Human and data ethics in Twitter research
Open the record for dataset details and reuse information.
Data from: Circadian mood variations in Twitter content
Open the record for dataset details and reuse information.
Data from: In the mood: the dynamics of collective sentiments on Twitter
We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source SentiStrength program. Specifically we make three contributions. Firstly, we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example, they use positive sentiment more often and negative sentiment less often. Secondly, we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable with those obtained from our empirical dataset.
Twitter Data Selfies
<p>Information for Twitter Data Selfies </p>
My twitter data set
<p>My twitter dataset</p>
Data from Political Actors' Twitter Accounts Related to Transitional Justice
Open the record for dataset details and reuse information.
Figure 2 from: Miyazaki Y, Teramura A, Senou H (2016) Biodiversity data mining from Argus-eyed citizens: the first illegal introduction record of Lepomis macrochirus macrochirus Rafinesque, 1819 in Japan based on Twitter information. ZooKeys 569: 123-133. https://doi.org/10.3897/zookeys.569.7577
Figure 2 - Photographs of Lepomis macrochirus macrochirus collected from the outdoor pool of Chigasaki Park, Yokohama City, Kanagawa Prefecture, Japan on 14 June 2015. A voucher specimen, juvenile, KPM-NI 38654 (photo: KPM-NR 164120 by AT), 22.6 mm SL B voucher specimen, juvenile (right side), KPM-NR 108928 by YM (the same individual as KPM-NI 38654) C adult specimens, photograph, KPM-NR 164118 by AT.
Figure 3 from: Miyazaki Y, Teramura A, Senou H (2016) Biodiversity data mining from Argus-eyed citizens: the first illegal introduction record of Lepomis macrochirus macrochirus Rafinesque, 1819 in Japan based on Twitter information. ZooKeys 569: 123-133. https://doi.org/10.3897/zookeys.569.7577
Figure 3 - Photograph of the outdoor pool of Chigasaki Park, Yokohama City, Kanagawa Prefecture, Japan.
Figure 1 from: Miyazaki Y, Teramura A, Senou H (2016) Biodiversity data mining from Argus-eyed citizens: the first illegal introduction record of Lepomis macrochirus macrochirus Rafinesque, 1819 in Japan based on Twitter information. ZooKeys 569: 123-133. https://doi.org/10.3897/zookeys.569.7577
Figure 1 - A tweet including two fish images posted by AT on 14 June 2015. The image on the left shows two adults of Lepomis macrochirus macrochirus, while the one on the right shows juveniles of Lepomis macrochirus macrochirus and two young of Carassius auratus (however, the specimens in the latter image are not able to be identified even to family level from the image alone). The comments are translated into English as follows: "The results of a pool cleaning. I cannot believe the foolishness of the person who introduced these fish into the pool." https://twitter.com/orca_lf/status/610088107476516864 [Accessed on 25 November 2015]
Figure 5 from: Miyazaki Y, Teramura A, Senou H (2016) Biodiversity data mining from Argus-eyed citizens: the first illegal introduction record of Lepomis macrochirus macrochirus Rafinesque, 1819 in Japan based on Twitter information. ZooKeys 569: 123-133. https://doi.org/10.3897/zookeys.569.7577
Figure 5 - The voucher specimens and photographs of Carassius auratus collected from the outdoor pool of Chigasaki Park, Yokohama City, Kanagawa Prefecture, Japan, on 14 June 2015. A voucher specimen, KPM-NI 38655 (photo: KPM-NR 108929 by YM), 64.9 mm SL B voucher specimen (live), KPM-NI 38656 (photo: KPM-NR 164119 by AT), 61.3 mm SL C voucher specimen (fresh), KPM-NR 108930 by YM (the same individual as KPM-NI 38656).
Figure 4 from: Miyazaki Y, Teramura A, Senou H (2016) Biodiversity data mining from Argus-eyed citizens: the first illegal introduction record of Lepomis macrochirus macrochirus Rafinesque, 1819 in Japan based on Twitter information. ZooKeys 569: 123-133. https://doi.org/10.3897/zookeys.569.7577
Figure 4 - A portion of gut components of Lepomis macrochirus macrochirus collected from the outdoor pool of Chigasaki Park, Yokohama City, Kanagawa Prefecture, Japan, on 14 June 2015. Dragonfly nymphs, Sympetrum sp., were included.
Data from: In the mood: the dynamics of collective sentiments on Twitter
Open the record for dataset details and reuse information.
Data from: Scaling in words on Twitter
Open the record for dataset details and reuse information.
Twitter Data on some Rumors during 2014 Flood Tragedy in Malaysia
<p>Data was collected from Twitter Advanced Search webpage using keyword based on some rumors during period of December 2014 until January 2015</p>
Corpus analysis of the polysemy of the verb taper 'hit' in non-standard French using Twitter data
<p>This data package contains (i) an annotated corpus sample of 10 000 tweets with the verb taper 'hit' in non-standard French (e.g. taper un coma, taper (dans) un kebab, taper une équipe 3-0) (NON-FINAL VERSION) and (ii) the Python script used to retrieve the tweets.</p>
Data from: Tracking time evolution of collective attention clusters in twitter: time evolving nonnegative matrix factorisation
Open the record for dataset details and reuse information.
German Twitter Data on Occupations
<h1>Background</h1> <p>There are many valuable insights on jobs and professions in different sectors of society based on their imminent and ascribed characteristics. Studying such characteristics traditionally was done by action research, surveys, questionnaires, etc. which typically take much time and resources to be concluded. This dataset accompanies our studies where we examine vocational education and training data on Twitter. We presented a generic framework to retrieve, process and analyze tweets, and discussed research questions from computational social science: For example, how can we make Twitter data interoperable to other<br>available resources, e.g. classifications of occupations, tools and skills? Second, do we have enough data to process job collocational prestige analysis on a geographical basis? This presents a novel approach towards labor market research, making novel data interoperable which has not been considered in previous literature. Our approach and pipeline is generic and could be easily extended to other languages. It also contributes to prestige research by widening the question of ascribed prestige to the question of how information on occupations is collocated and what these contextualization tell us about how occupations are seen.</p> <h1>Data</h1> <p>This dataset contains the metadata related to 3,407,481 tweets (2007-2023). However, according to Twitter/X rules of data protection, we do not publish any data retrieved by their API. This dataset contains a unique id (not the tweet id), a job_id related to KldB (Klassifikation der Berufe), a job_title linked to that tweet, a timestamp and a sentiment. </p> <h1>Contact</h1> <p>Please contact us if you have questions or want to use this dataset.</p>
Restricted access data for the paper Fake News on Twitter During the 2016 U.S. Presidential Election
<p>Restricted access data for replicating results in the paper Fake News on Twitter During the 2016 U.S. Presidential Election.</p>
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.