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A dataset of gamers on Twitter
This gaming-related dataset consists of 8932 users (labeled as gamers) engaging in game-related conversations. We have collected (June 2018) their timeline (the most recent 3200... -
Learning to quantify: LeQua 2022 datasets
The aim of LeQua 2022 (the 1st edition of the CLEF “Learning to Quantify” lab) is to allow the comparative evaluation of methods for “learning to quantify” in textual... -
Product Reviews for Ordinal Quantification
This data set comprises a labeled training set, validation samples, and testing samples for ordinal quantification. It appears in our research paper "Ordinal Quantification... -
Cherenkov Telescope Data for Ordinal Quantification
This labeled data set is targeted at ordinal quantification. It appears in our research paper "Ordinal Quantification Through Regularization", which we have published at... -
VaxxHesitancy: A Dataset for Studying Hesitancy Towards COVID-19 Vaccination ...
We create a publicly available dataset of over 3,100 COVID-19 vaccine-related tweets labeled as one of four stance categories: pro-vaxx, anti-vaxx, vaxx-hesitant, or... -
Ukraine-related Disinformation Dataset
Ukraine-related disinformation dataset from "Comparative Analysis of Engagement, Themes, and Causality of Ukraine-Related Debunks and Disinformation" (accepted at SocInfo... -
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CSV
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CSV
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Ego Networks of Words in Twitter
This set of dataframes were used in our last paper : Ollivier K, Boldrini C, Passarella A, Conti M (2022) Structural invariants and semantic fingerprints in the “ego network”... -
Cross-Lingual Dataset of Crisis-Related Social Media
If you use this dataset, please cite the following paper: Fedor Vitiugin, Carlos Castillo: Cross-Lingual Query-Based Summarization of Crisis-Related Social Media: An Abstractive... -
Dataset for Evaluating Abstractive Summaries of Crisis-Related Social Media
The dataset created for evaluation of summaries generated from social media posted during five natural disasters. The dataset contains: ground truth reports created by human... -
Attributed Sream Hypergraphs
ash_model is a Python software package that allows to represent and analyze dynamic hypergraphs enriched with node attributes. -
Private Morningness–eveningness assessment from mobile phone communication analysis
Human behaviour follows a 24-h rhythm and is known to be governed by the individual chronotypes. Due to the widespread use of technology in our daily lives, it is possible to... -
Private Human-agent coordination in a group formation game
Coordination and cooperation between humans and autonomous agents in cooperative games raise interesting questions on human decision making and behaviour changes. Here we report... -
Private Ecology of the digital world of Wikipedia
Wikipedia, a paradigmatic example of online knowledge space is organized in a collaborative, bottom-up way with voluntary contributions, yet it maintains a level of reliability... -
Membership Inference Attacks on ML Models
This collection of Jupyter notebooks implements membership inference attacks found in Salem et al. "ML-Leaks: Model and Data Independent Membership Inference Attacks and... -
Structify-Net
Structify_net is a python library allowing to create networks with a predefined structure, and a chosen number of nodes and links.-
ZIP
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ZIP
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What is a meme, technically speaking?
This contribution seeks to demonstrate how studying memes as a collection depends on the website or platform where they are sourced. To do so, we compare how memes,... -
The Propagation of Misinformation in Social Media
There is growing awareness about how social media circulate extreme viewpoints and turn up the temperature of public debate. Posts that exhibit agitation garner... -
How to Make Meme Collections
How to guide to make meme collections by querying and extracting memes from four key sites: the meme database Know Your Meme, the web search engine Google Images, the meme...-
PDF
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PDF
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PyGM
Python library implementing sorted containers with state-of-the-art query performance and compressed memory usage.