Demographic
Please cite the following paper when using this dataset:
N. Thakur, "Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions", Journal of Analytics, Volume 1, Issue 2, 2022, pp. 72-97, DOI: https://doi.org/10.3390/analytics1020007
Abstract
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Mother’s Significant Feature (MSF) Dataset has been designed to provide data to researchers working towards woman and child health betterment. MSF dataset records are collected from the Mumbai metropolitan region in Maharashtra, India. Women were interviewed just after childbirth between February 2018 to March 2021. MSF comprise of 450 records with a total of 130 attributes consisting of mother’s features, father’s features and health outcomes. A detailed dataset is created to understand the mother’s features spread across three phases of her reproductive age i.e.
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Recent US Census Data the American Community Survey,
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This data set provides a list of the indexed journal by Scopus, Web of Science, and Directory of Open Access Journals (DOAJ) with the data in each row: Journal ID, Journal name, Publisher name, Publisher Address, Print-ISSN, E-ISSN, Scope, Coverage year, Status level (such as a Top-Level, etc), Cited Score, Languages, and many more.
Reference attached on the link.
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The data include:
- Demographic data of the participants including: gender, group of participation and number of years in the company.
- Results of the use of Ethool including: expended time and subjective evaluation of if using a Likert of 5 points. Two different files are available corresponding to each iteration (prototype 1 and prototype 2).
- Results of the SUS questionnaire for both iterations (prototype 1 and prototype 2).
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The Cross-sectional Diabetes Risk survey aims to assess the prevalence of diabetes and its risk factors at the same point in time and also provide a "snapshot" of diseases and risk factors simultaneously for individuals belonging to the western region of the Kingdom of Saudi Arabia (KSA).
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This repository introduces a novel dataset for the classification of Chronic Obstructive Pulmonary Disease (COPD) patients and Healthy Controls. The Exasens dataset includes demographic information on 4 groups of saliva samples (COPD-HC-Asthma-Infected) collected in the frame of a joint research project, Exasens (https://www.leibniz-healthtech.de/en/research/projects/bmbf-project-exasens/), at the Research Center Borstel, BioMaterialBank Nord (Borstel, Germany).
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The dataset consists of reviews for various hotels throughout the world and data columns range from Location, Trip Type to various parameters of reviewing with individual review score. The data can be preprocessed and used for various purposes ranging from review categorization, topic extraction, sentiment analysis, location based quality calculation etc. Trustworthy real world data comes handy now-a-days and is tough to get a grasp on. So this dataset will be a good contribution for the researcher community as well as professionals.
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This data set includes records of the student data, data descriptions, student demographic survey, class size from students to participated in the 10 program Personal Software Process course.
This version of the course was delivered between 1995 and 2006.
The data was collected by the Software Engineering Institute (SEI) from classes taught by SEI staff and class data submitted by authorized instructors.
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Datasets contain survey data of 873 rural poor households in the states of Maharashtra, Odisha, Madhya Pradesh, and Rajasthan.
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