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172 results for “Media Use”
Incentivizing news consumption on social media platforms using large language models and realistic bot accounts
Open the record for dataset details and reuse information.
Juxtaposition of climate change contrarians and scientists in the media using Media Cloud data
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Use of social media in the marketing of agricultural products and farmers' turnover in South-South Nigeria
<p class="CxSpFirst"><span>The study investigated the use of social media in the marketing of agricultural products and farmers turnover in South-South Nigeria. The purpose of the study was to determine the extent to which the usage of social media in the marketing of agricultural products in Nigeria can enhance efficiency and farmers' sales turnover. It employed the survey research design and data were collected with the help of a structured questionnaire. Research data were analysed using t-test and least square method. The results showed that the use of social media (Facebook, WhatsApp and Instagram) in the marketing of agricultural products enhances efficiency and turnover of farmers through a significant reduction in the cost of marketing agricultural products as well as increased awareness and the attendant increase in demand for agricultural produce.</span></p>
dhaaana/paper-ep: Dataset Jawaban Survei Penggunaan Media Sosial Di Kalangan Mahasiswa ITS Menggunakan Teori Uses and Gratifications
<p>dataset hasil kuisioner paper Etika Profesi TI kelas C</p>
Raw data and code for: Shaping entangled photons through thick scattering media using an advanced wave beacon
<p>The paper is here: </p> <p>https://arxiv.org/abs/2403.18324</p> <p>And available as a reposity also on bitbucket: </p> <p>https://bitbucket.org/rshekel/klyshko-optimization-data/src/master/</p>
Understanding the Rare Inflammatory Disease Using Large Language Models and Social Media Data
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Social Media use on 1st-year Students' Experiences and Well-being: Dataset and Questionnaire
<p>This is the SPSS dataset and the questionnaire which supported a project on Social Media use on 1st-year Students’ Experiences and Well-being. The questionnaire has been guided by the four key elements of collecting information about the students' diverse backgrounds, social media use, support experience and mental well-being. Respective validated scales are included in the survey to assess students' support experience and well-being. </p> <p> </p>
Data for manuscript: "Using Word Embeddings to Probe Sentiment Associations of Politically Loaded Terms in News and Opinion Articles from News Media Outlets"
<p>This data set contains material for the purpose of scientific reproducibility of the accompanying manuscript "Using Word Embeddings to Probe Sentiment Associations of Politically Loaded Terms in News and Opinion Articles from News Media Outlets".</p> <p>Note that this data set is distributed with an Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License. NonCommercial means you may not use the material for commercial purposes. NoDerivatives means if you remix, transform, or build upon the material, you may not distribute the modified material. Attribution means you must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. See attached license terms for details.</p> <p>The work "Using Word Embeddings to Probe Sentiment Associations of Politically Loaded Terms in News and Opinion Articles from News Media Outlets" describes an analysis of political associations in 27 million diachronic (1975-2019) news and opinion articles from 47 news media outlets popular in the United States. We use embedding models trained on individual outlets content to quantify outlet-specific latent associations between positive/negative sentiment words and terms loaded with political connotations such as those describing political orientation, party affiliation, names of influential politicians and ideologically aligned public figures. </p> <p>News and opinion articles from the outlets listed in Figure 3 are available in the outlet's online domains and/or public cache repositories such as Google cache, The Internet Wayback Machine [31] and Common Crawl [32]. This work has not analyzed video or audio content of news media organizations, except when the outlet explicitly provides a transcript of such content in article form.<br> The temporal coverage of articles from different news outlets is not uniform. For most media organizations, news articles availability in their online domains or Internet cache backups becomes sparse as a function of articles’ age. This is not the case for some news outlets, where availability of news articles goes back to the 1970s. The Supplementary Material (SM) illustrates the time ranges of article data analyzed based on news outlets articles online availability.</p> <p>Textual content included in our analysis is circumscribed to the articles’ headlines and main text and does not include other article elements such as figure captions. Targeted textual content was located in HTML raw data using outlet specific XPath expressions. Tokens were lowercased prior to estimating embedding models. Markup language tags, URLs, nonalphanumeric characters, punctuation, digits, 330 common stop words and multiple spaces were removed prior to estimating word embeddings models.<br> All the analysis scripts and the diachronic word embedding models built from each of the 47 news media outlets analyzed in this work are available in this repository.</p> <p>For the purpose of reproducibility, we also provide in the above repository the articles’ text used to train the news outlets embedding models with the caveat that outlets articles not accessible without a subscription have been excluded. Also, for the included articles, stop words have been removed and the remaining words have been randomly scrambled within a sliding window of size 10 to render the articles incomprehensible to a human reader. These steps have been taken to not infringe articles copyright. These preprocessing steps have only minor impact on Continuous Bag of Words (CBOW) word2vec and the results reported in this work are similar when using the scrambled articles text to train outlet-specific embedding models.</p> <p>We derived outlet-specific word embedding models at every five-year time intervals within the 1975-2019 time range. The gensim [33] implementation of word2vec was used to train the embedding models. The continuous bag of words (CBOW) architecture performed slightly better than the Skip-Gram architecture in commonly used validation metrics so it was used for all subsequent analysis. </p> <p>For training the word embedding models, the following parameters were used: vector dimensions=300, window size=10, negative sampling=10, down sampling frequent words = 0.0001, minimum frequency count of 5 (only terms that appear more than 5 times in the corpus were included into the word embedding model vocabulary), number of training iterations (epochs) through the corpus=5. The exponent used to shape the negative sampling distribution was the default 0.75. </p> <p>Outlet-specific embedding models performance across a range of commonly used semantic, syntactic and analogy tasks was similar to popular pre-trained embedding models trained on corpora such as Twitter or Google books on similarity, association and word analogy tasks, see Supplemeentary Material of the manuscript for detailed validation tests results.</p> <p> </p>
Traveltime calculations for qP, qSV and qSH waves in 3D tilted transversely isotropic media using fast sweeping method with a Newton method local solver
<p>Data for the 3D BP model, which is used in the numerical example test for fast sweeping method </p>
Data: Towards understanding specific ion effects in aqueous media using thermodiffusion
<p>Data, which are presented in the following publication: Mohanakumar, Shilpa; Wiegand, Simone (2022): Towards understanding specific ion effects in aqueous media using thermodiffusion. In: The Eur. Phys. J. E 45 (2), S. 10. DOI: 10.1140/epje/s10189-022-00164-8.</p>
Dataset to support "Explore the potential of using social media crowdsourcing for earthquake damage assessment"
<p>This dataset is used to support findings in the paper "<strong>Explore the potential of using social media crowdsourcing for earthquake damage assessment.</strong>"</p> <p>In this paper, we investigated six earthquake events to explore the potential of using social media crowdsourcing for earthquake damage assessment. These cases include the 2014 Iquique earthquake, the 2015 Napa earthquake, the 2015 Nepal earthquake, the 2019 Ridgecrest earthquake, the 2021 Fukushima earthquake, and the 2021 Haiti earthquake. For the first three cases, tweet ID information was collected from the publicly available website CrisisNLP (https://crisisnlp.qcri.org/). For the last three cases, we collected “near-real-time” tweets with the key search term “earthquake.” For the 2019 Ridgecrest earthquake, the search date range was from July 4 to 10, 2019. For the 2021 Fukushima earthquake, the search date range was February 13 to 17, 2021. For the 2021 Haiti earthquake, the search date range was August 14 to 19, 2021. It should be noted that restrictions apply to the availability of tweet data due to the policy from <em>Twitter</em> Inc. Tweet data showing user profiles or text content is not allowed to be shared publicly, but tweet IDs are available to download from this dataset. </p> <p>In addition, we attached our processed results to this dataset, including,</p> <ol> <li>Damage estimation. The damage estimation for each event is based on the average estimated level of all damage-related tweets identified by text classification models, as documented in our paper.</li> <li>Temporal dynamics of damage estimation. We conducted the temporal analysis to explore the convergence of damage estimates over time, in which data were first binned based on the number of damage-related tweets in each 2-hour interval.</li> </ol> <p>If you need the training and testing datasets or have any further questions regarding the dataset or paper, please do not hesitate to reach us. </p>
Pounds Off Digitally (POD): The Use of Podcasting and Mobile Media to Promote Weight Loss
ClinicalTrials.gov study NCT01139255. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Reduction of Screen-Based Media Use in Families With Children
ClinicalTrials.gov study NCT03788525. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Short-term Efficacy of Reducing Screen-based Media Use
ClinicalTrials.gov study NCT04098913. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Theory-based Social Media Intervention for Non-medical Use of Prescription Opioids in Young Adults
ClinicalTrials.gov study NCT06469749. IPD Sharing: NO. Countries: 1. Publications: 1.
Social Media Anti-Vaping Messages to Reduce ENDS Use Among Sexual and Gender Minority Teens
ClinicalTrials.gov study NCT06308081. IPD Sharing: NO. Countries: 1. Publications: 30.
Comparison of Human Embryo Development Using Sequential and Single Media With Time-lapse Imaging
ClinicalTrials.gov study NCT01939626. IPD Sharing: Not stated. Countries: 2. Publications: 1.
The Effect of Social Media Use on Eating Behaviours
ClinicalTrials.gov study NCT03346785. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effect of a Social Media-based Health Education Program on Postnatal Care (PNC) Knowledge Among Pregnant Women Using Smartphones in Dhulikhel Hospital
ClinicalTrials.gov study NCT05132608. IPD Sharing: NO. Countries: 1. Publications: 2.
Safer Online Lives: Use of the Internet & Social Media by People With Intellectual Disabilities
ClinicalTrials.gov study NCT04919213. IPD Sharing: NO. Countries: 1. Publications: 6.
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.