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Found 14 papers, 5 papers with code
Evaluating Fairness in Self-supervised and Supervised Models for Sequential Data
Self-supervised learning (SSL) has become the de facto training paradigm of large models where pre-training is followed by supervised fine-tuning using domain-specific data and labels.
Uncovering Bias in Personal Informatics
Personal informatics (PI) systems, powered by smartphones and wearables, enable people to lead healthier lifestyles by providing meaningful and actionable insights that break down barriers between users and their health information.
Beyond Accuracy: A Critical Review of Fairness in Machine Learning for Mobile and Wearable Computing
The field of mobile and wearable computing is undergoing a revolutionary integration of machine learning.
UBIWEAR: An end-to-end, data-driven framework for intelligent physical activity prediction to empower mHealth interventions
To this end, we propose UBIWEAR, an end-to-end framework for intelligent physical activity prediction, with the ultimate goal to empower data-driven goal-setting interventions.
Multilingual Name Entity Recognition and Intent Classification Employing Deep Learning Architectures
Named Entity Recognition and Intent Classification are among the most important subfields of the field of Natural Language Processing.
Pointspectrum: Equivariance Meets Laplacian Filtering for Graph Representation Learning
In a different GRL approach, spectral methods based on graph filtering have emerged addressing over smoothing; however, up to now, they employ traditional neural networks that cannot efficiently exploit the structure of graph data.
My tweets bring all the traits to the yard: Predicting personality and relational traits in Online Social Networks
Despite a marked increase on research in personality prediction on based on online behavior the focus has been heavily on individual personality traits largely neglecting relational facets of personality.
Detecting Cyberbullying and Cyberaggression in Social Media
We also explore specific manifestations of abusive behavior, i. e., cyberbullying and cyberaggression, in one of the hate-related communities (Gamergate).
A Unified Deep Learning Architecture for Abuse Detection
Hate speech, offensive language, sexism, racism and other types of abusive behavior have become a common phenomenon in many online social media platforms.
Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior
In recent years, offensive, abusive and hateful language, sexism, racism and other types of aggressive and cyberbullying behavior have been manifesting with increased frequency, and in many online social media platforms.
Social and Information Networks 68T06 K.4.2
Class-based Prediction Errors to Detect Hate Speech with Out-of-vocabulary Words
Common approaches to text categorization essentially rely either on n-gram counts or on word embeddings.
Measuring #GamerGate: A Tale of Hate, Sexism, and Bullying
Over the past few years, online aggression and abusive behaviors have occurred in many different forms and on a variety of platforms.
Mean Birds: Detecting Aggression and Bullying on Twitter
In recent years, bullying and aggression against users on social media have grown significantly, causing serious consequences to victims of all demographics.
Computers and Society Social and Information Networks
Bridge Bounding: A Local Approach for Efficient Community Discovery in Complex Networks
There are numerous techniques adopting a global perspective to the community detection problem, i. e. they operate on the complete network structure, thus being computationally expensive and hard to apply in a streaming manner.
Data Analysis, Statistics and Probability Physics and Society
