Social Sciences
We gathered a total of 1,515 news articles concerning suicide, building jumps, and related incidents from 2019 to 2024. Utilizing sentiment analysis tools, we categorized the data into two groups: positive sentiment words and negative sentiment words. Our primary objective was to examine the relationship between negative sentiment words and other associated terms.
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The UNISTUDIUM dataset contains the logs collected by Unistudium, the University of Perugia elearning platform based on moodle, a open source software for learning management systems (https://moodle.org).
The collected logs record interactions with the platform of students attending 4 courses during the time period of one semester, from 1st September to 31st December.
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This dataset includes the raw data and analyzed data for an IEEE TvCg article:
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To download the dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13738598
Please cite the following paper when using this dataset:
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The Protection of Children from Sexual Offences (POCSO) Act was an important legislation that was enacted in India in 2012. It aims to safeguard children from sexual exploitation through various enforcement and legal redressal mechanisms. This dataset has been scraped from eCourts India Services using Python script which uses Selenium. We have mined apex and high courts’ judgements, which mentioned the POCSO Act and its respective sections. We have chronologically scraped POCSO judgements from 2012 to 2020 in the corpus.
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Decentralized social media platforms like Bluesky Social (Bluesky) have made it possible to publicly disclose some user behaviors with millisecond-level precision. Embracing Bluesky's principles of open-source and open-data, we present the first collection of the temporal dynamics of user-driven social interactions. BlueTempNet integrates multiple types of networks into a single multi-network, including user-to-user interactions (following and blocking users) and user-to-community interactions (creating and joining communities).
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The dataset includes Pakistan most popular YouTube videos for each category from year 2021- 2023. There are two kinds of data files, one includes video statistics and other one related to comments on those videos. They are linked by the unique video_id field. Both datasets are merged in final videos file which contains all videos statistics and sentiment extracted from comments. Here’s a breakdown of each column:
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We sourced our data by crawling comments from the “Zoufan” blog within the Weibo social platform. Subsequently, a team of qualified psychologists were enlisted to annotate the data. In our study, strict data preprocessing measures were adopted to protect users’ privacy.
SocialCD-3K (Cognitive Distortion Classification)
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We sourced our data by crawling comments from the “Zoufan” blog within the Weibo social platform. Subsequently, a team of qualified psychologists were enlisted to annotate the data. In our study, strict data preprocessing measures were adopted to protect users’ privacy.
SOS-HL-1K (Suicide Risk Classification)
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In this paper, we cover the creation of Fantasy Forecast, a gamified forecasting platform used for hosting forecasting competitions, or ‘tournaments’ that was deployed in the run-up to and over the course of the 2023 UK local elections. This research is an interdisciplinary endeavour, gamifying the humanities to create a platform centred on elections and other political phenomena, informed by both quantitative (site use metrics and survey responses) and qualitative (user feedback) data.
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