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.
48
datasets available to search
ShareScore release 0.7.1
Dataset results
48 results for “social media data”
SOCIAL MEDIA DATA 3 SPORTING EVENTS
<p>Comments on social networks (Facebook, Instagram, Twitter and YouTube) about the brand Spain linked to three chosen sporting events (mega, medium and<br>local): a football mega event (Qatar Football World Cup), a semi-massive tennis event (Davis Cup 2022) and a local marathon event (XLI<br>Marathon Valencia Trinidad Alfonso 2022</p>
Propaganda and fake news on the war in Ukraine: data from Russian-speaking social media communities
<p>The data set contains posts from social media networks popular among Russian-speaking communities. Information was searched based on pre-defined keywords ("war", "special military operation", etc.) and is mainly related to the ongoing war in Ukraine with Russia. After a thorough review and analysis of the data, both propaganda and fake news were identified. The collected data is anonymized. Feature engineering and text preprocessing can be applied to obtain new insights and knowledge from this data set. The data set is useful for the study of information wars and propaganda identification.</p>
Data for the paper, "Social media data for environmental sustainability: a critical review of opportunities, threats and ethical use"
<p>These data were collected for the paper, "Social media data for environmental sustainability: a critical review of opportunities, threats and ethical use" published in One Earth. It includes a database of studies applying social media data in environmental sustainability research, which were collected and reviewed in full by the authors. Rather than providing a comprehensive summary of all relevant literature like in a systematic review, our objective was to take stock and evaluate the previous body of work in the field in order to promote conceptual innovation from its critical examination. Building on a set of 169 studies collected in a previous systematic review of social media data applications in environmental research (Ghermandi and Sinclair 2019), the database includes additional relevant studies that were identified by snowballing previous references and adding further gray and scientific academic articles known to the authors. For studies to be included in our analysis, they had to involve the use of data from one or more social media platforms and investigate human interactions with and/or impacts on the environment. We relied on a broad definition of social media including any website or application that enables users to create and share content or to participate in social networking (e.g., blogging sites, recommendation sites, and online forums). We further strengthened the analysis by including insights from additional literature on social media that do not have a direct application to environmental sustainability (e.g., studies on biases in social media data). The final database consists of 415 studies, which were published between 2011 and 2021.</p> <p> </p> <p>Ghermandi, Andrea, and Michael Sinclair. "Passive crowdsourcing of social media in environmental research: A systematic map." <em>Global environmental change</em> 55 (2019): 36-47.</p>
Data From: Analysing social media forums to discover potential causes of phasic shifts in cryptocurrency price series
<p>The recent extreme volatility in cryptocurrency prices occurred in the setting of popular social media forums devoted to the discussion of cryptocurrencies. We develop a framework that discovers potential causes of phasic shifts in the price movement captured by social media discussions. This draws on principles developed in healthcare epidemiology where, similarly, only observational data are available. Such causes may have a major, one-off effect or recurring effects on the trend in the price series. We find a one-off effect of regulatory bans on bitcoin, the repeated effects of rival innovations on ether and the influence of technical traders, captured through discussion of market price, on both cryptocurrencies. The results for Bitcoin differ from Ethereum, which is consistent with the observed differences in the timing of the highest price and the price phases. This framework could be applied to a wide range of cryptocurrency price series where there exists a relevant social media text source. Identified causes with a recurring effect may have value in predictive modelling, whilst one-off causes may provide insight into unpredictable black swan events that can have a major impact on a system.</p>
Social media data from online discourse on Nigeria's budget
<p>The social media data was obtained by extracting online discourse on Nigeria's 2013 budget. This was done as a component of the media analysis on the case study investigating the use of the online national budget of Nigeria which is part of the 'Exploring the Emerging Impacts of Open Data in Developing Countries' (ODDC) research project.</p>
Analyzing Linguistic Patterns in the Social Media Discourse of Juan Guaidó and Nicolás Maduro during the 2019 Political Conflict in Venezuela - research data
<p>In this paper, the political conflict in Venezuela in 2019 is approached from a corpus linguistic point of view. The conflict between Juan Guaidó, the speaker of the parliament, and Nicolás Maduro, who won the internationally unrecognized 2018 presidential election, escalated on January 23, 2019, when Guaidó proclaimed himself the legitimate president of Venezuela. By comparatively analyzing the tweets of the two politicians three months before and after January 23, 2019, a corpus-based discourse analysis will be conducted to investigate whether and to what extent linguistic patterns (especially most frequent words and their co-occurrences, as well as n-grams) change within the respective social media communication of these political opponents. The analysis reveals changes in linguistic patterns, especially with respect to co-occurrences and n-grams, detected in the corpus data, and demonstrates that politicians use Twitter to present themselves, in the case of Guaidó, as the representative of the people wanting to lead Venezuela into a democratic future, and, in the case of Maduro, as the only legitimate president and defender of Venezuela against internal and external threats.</p>
Data from: The viewer doesn't always seem to care - response to fake animal rescues on YouTube and implications for social media self-policing policies
<p>Animal-related content on social media is hugely popular but is not always appropriate in terms of how animals are portrayed or how they are treated. This has potential implications beyond the individual animals involved, for viewers, for wild animal populations, and for societies and their interactions with animals. Whilst social media platforms usually publish guidelines for permitted content, enforcement relies at least in part on viewers reporting inappropriate posts. Currently, there is no external regulation of social media platforms. Based on a set of 241 "fake animal rescue" videos that exhibited clear signs of animal cruelty and strong evidence of being deliberately staged (i.e. fake), we found little evidence that viewers disliked the videos and an overall mixed response in terms of awareness of the fake nature of the videos, and their attitudes towards the welfare of the animals involved. Our findings suggest, firstly, that despite the narrowly defined nature of the videos used in this case study, exposure rates can be extremely high (one of the videos had been viewed over 100 million times), and, secondly, that many YouTube viewers cannot identify (or are not concerned by) animal welfare or conservation issues within a social media context. In terms of the current policy approach of social media platforms, our findings raise questions regarding the value of their current reliance on consumers as watch dogs.</p>
Data from: Social media highlights the overlooked impact of cats on arthropods
Open the record for dataset details and reuse information.
Data From: Analysing social media forums to discover potential causes of phasic shifts in cryptocurrency price series
Open the record for dataset details and reuse information.
Data from: The viewer doesn’t always seem to care - response to fake animal rescues on YouTube and implications for social media self-policing policies
Open the record for dataset details and reuse information.
Data file: a qualitative social media content analysis of the Dutch #breakthesilence campaign on negative and traumatic experiences of labour and birth
<p>Data file with typed out quotes from the Dutch #breakthesilence campaign analysed for the study 'Left powerless: a qualitative social media content analysis of the Dutch #breakthesilence campaign on negative and traumatic experiences of labour and birth'.</p>
Data from: Understanding sentiment of national park visitors from social media data
<p>National parks are key for conserving biodiversity and supporting people´s well-being. However, anthropogenic pressures challenge the existence of national parks and their conservation effectiveness. Therefore, it is crucial to assess how people perceive national parks in order to enhance socio-political support for conservation. User-generated data shared by visitors on social media provide opportunities to understand how people perceive (e.g. preferences, feelings, opinions) national parks during nature-based recreational experiences. In this study, we applied methods from automated natural language processing to assess visitors' sentiment when describing experiences in Instagram posts geolocated inside four national parks in South Africa. We found that visitors' sentiment was positive, and mostly included emotions such as joy, anticipation, trust and surprise, with only a small occurrence of posts with negative feelings. Appreciation of nature, in association with a diverse set of other aspects, such as activities, geographical features and tourist attractions, was used to describe experiences related to nature, wilderness, traveling, holidays and adventures. The type of nature-based experience described by visitors was park specific, revealing different profiles of parks providing wildlife or scenery experiences. Findings support and highlight the societal role of national parks in providing visitors with opportunities to develop positive connections with nature. Social media data may be used to understand visitors' perceptions, and how the image of national parks is constructed by users in the virtual social environment. This may help inform management for promoting a high quality tourism experience, as well as conservation marketing aimed at fostering socio-political support for national parks and their long-term conservation effectiveness.</p>
FIGURE 1 in Ontogeny of an arlequin: morphological and colour pattern changes from juvenile to adult in Gnathophyllum elegans (Risso, 1816) (Decapoda: Palaemonidae), traced through citizen science and social media data mining
FIGURE 1. Morphological and colour pattern changes from juvenile to adult in Gnathophyllum elegans (Risso, 1816). A–C. Specimens from Capo Noli (Italy, Mediterranean Sea) (~44.199232N, 8.420455E), 15–16 m, on anthropogenic debris laying on a detritic bottom, 5–13.IX.2020. A. Photo by Walter Bassi. B–C. Photos by Alessandro Raho. D. Specimen from La Laja beach, Gran Canaria (Spain, Atlantic Ocean) (~28.060335N, -15.418428E), 1 m, amidst algae in a tide pool, 29.VIII.2017. Photo by Alberto Navarro. E. Specimen from Bat Galim reef, Haifa (Israel, Mediterranean Sea) (~32.833317N, 34.97431E), 2 m, under a rock on a rocky bottom, ~2017. Photo by Sarah Ohayon. F. Specimen from Capo Caccia, Sardinia (Italy, Mediterranean Sea) (~40.565506N, 8.165579E), 5 m, detritic bottom with rocks, 28.VIII.2015. Photo by Marco Colombo.
Climate Security on social media: raw and processed data from Twitter
<p>This dataset reflects climate security dialogues on Twitter, from January 2014 to May 2023.</p>
Social Media data and sales for promotional product
<p>Social Media data and sales for promotional product from 2017-2019</p>
Data from: Identifying conservation priorities for gorgonian forests in Italian coastal waters with multiple methods including citizen science and social media content analysis
<div> <div> <div> <div> <p>Gorgonian forests are among the most complex of subtidal habitats in the Mediterranean Sea, supporting high biodiversity and providing diverse ecosystem services. Despite their iconic status, the geographical distribution and condition of gorgonian species is poorly known. Using multiple online data sources, our primary aims were to compile, map and analyse observations of gorgonian forests in Italian coastal waters to assess the biological complexity of gorgonian forests; evaluate impacts and vulnerable species, and identify areas of special interest inside and outside of existing MPAs to help prioritise conservation strategies and actions.</p> </div> </div> </div> </div>
Data for: Exploring Emerging Social Media: Acquiring, Processing, and Visualizing Data with Python and OSoMe Web Tools
<p>Data collected from Bluesky and Mastodon via streaming covering the period between 2024-06-25 and 2024-07-02. Entries contains any the of following terms: biden, trump, or debate. Data also contains embedding precalculated for each dataset. The data also contains embeddings pre calculcated for the datasets.</p>
Data Leveraging Digital Innovation: Enhancing Tourist Intentions through Social Media, Websites, and Mobile App Experiences
Open the record for dataset details and reuse information.
Data for Shouting into the void: A database of the alternative social media platform Gab
<p>As social media platforms have increased their role as content moderators, alternative social media platforms have emerged with fewer rules and policies on moderating content. One such platform is Gab, a social media platform similar to Twitter that champions free speech with minimal standards on content. Early research has linked this platform with alt-right, hate speech, conspiracy theories, and other alternative content that is sometimes marginalized in mainstream social media platforms like Twitter and Facebook. In an effort to provide a means for researchers to study this platform, we introduce a database of 35,851,186 posts (with additional edit histories) and 819,957 user profiles web-scraped from Gab between August 2016 and December 2018. In this paper, we outline our data collection process, provide descriptive statistics, consider the ethics of our data collection process, and provide suggested avenues of inquiry for researchers interested in analyzing our database.</p>
Understanding the Rare Inflammatory Disease Using Large Language Models and Social Media Data
Open the record for dataset details and reuse information.
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.