Social Sciences

Several fields of study can benefit from a large, structured, and accurate dataset of historical figures. Due to a lack of such a dataset, in this paper, we aim to use machine learning and text mining models to collect, predict, and cleanse online data with a focus on age and gender. We developed a five-step method and inferred birth and death years, binary gender, and occupation from community-submitted data to all language versions of the Wikipedia project.

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・The first question (Q1) is to choose between the pedestrian-first setting and the driver-first setting of an autonomous car they are to drive.

・The second question (Q2) is to probe the aspect of the accident the participants focus on in the case of an unavoidable accident involving an autonomous car with a victim.

・The third question (Q3) was about the ideal car production for all groups, asking whether car companies should produce pedestrian- or driver-first-setting cars.

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The dataset includes the responses of the healthcare professionals towards the role of information technology in the healthcare centers. In addiition, the dataset provides the participants' perception on the recent technologies and its impact on the disease detection. 

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This article was results based on the interview phase in the English language 

course of even semester [the academic year 2021-2022] Institut Agama Kristen 

Negeri Ambon. The majority concern is how the students of English courses respond 

during even semester conducted. Moreover, only a few students are encouraged to 

finish their course with moderate achievement, and half of the students are stated on 

lower achievement following unconscious narration to be absent during English 

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Lists of male and female names have been drawn up to determine the gender affiliation of the authors of scientific publications. Feminine Given Names  and Masculine Given Names were taken from Wikipedia's free encyclopedia for the listing of the lists. These lists are supplemented by names specific to the research of countries. As a result, the list of male names contains 2515 records and a list of female names - 1461 records. The following was to check the lists for the coincidence of names. 218 names coincided withdrawn from both lists.

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Please cite the following paper when using this dataset:

N. Thakur and C.Y. Han, “An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection,” Journal of COVID, 2022, Volume 5, Issue 3, pp. 1026-1049

Abstract

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Please cite the following paper when using this dataset:

N. Thakur, “MonkeyPox2022Tweets: The first public Twitter dataset on the 2022 MonkeyPox outbreak,” Preprints, 2022, DOI: 10.20944/preprints202206.0172.v2

Abstract

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Social media data mining is a popular way to find out different preferences, biases, and overall sentiments of a group of people on a specific topic. On 24th February 2022, Russia invaded Ukraine. A social media war also starts with the ground war. People from multiple countries have participated in that social media war. Twitter is one of the most popular micro-blogging sites. There are multiple hashtags with Ukraine-Russia tweets emerging having millions of tweets. #ukrainerussiawar, #ukraine #russia #ukrainewar are some of the popular hashtags on this topic.

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991 Views

This dataset contains 220,085 tweets containing the word vaccine between December 9th and December 18th 2021 at different times during each day, extracted using the Twitter API v2. Each tweet was extracted at least 3 days after its initial posting time in order to register 3 days of engagements, and it doesn't include retweets.

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