How to keep text private? A systematic review of deep learning methods for privacy-preserving natural language processing
Deep learning (DL) models for natural language processing (NLP) tasks often handle
private data, demanding protection against breaches and disclosures. Data protection laws …
private data, demanding protection against breaches and disclosures. Data protection laws …
Temporal graph networks for deep learning on dynamic graphs
Graph Neural Networks (GNNs) have recently become increasingly popular due to their
ability to learn complex systems of relations or interactions arising in a broad spectrum of …
ability to learn complex systems of relations or interactions arising in a broad spectrum of …
Understanding social engagements: A comparative analysis of user and text features in Twitter
Abstract Information is spread as individuals engage with other users in the underlying
social network. Analysis of social engagements can therefore provide insights to understand …
social network. Analysis of social engagements can therefore provide insights to understand …
RecSys 2020 challenge workshop: engagement prediction on Twitter's home timeline
The workshop features presentations of accepted contributions to the RecSys Challenge
2020, organized by Politecnico di Bari, Free University of Bozen-Bolzano, TU Wien …
2020, organized by Politecnico di Bari, Free University of Bozen-Bolzano, TU Wien …
Context-Based Tweet Engagement Prediction
J Jeromela - arXiv preprint arXiv:2310.03147, 2023 - arxiv.org
Twitter is currently one of the biggest social media platforms. Its users may share, read, and
engage with short posts called tweets. For the ACM Recommender Systems Conference …
engage with short posts called tweets. For the ACM Recommender Systems Conference …
Predicting twitter engagement with deep language models
Twitter has become one of the main information sharing platforms for millions of users world-
wide. Numerous tweets are created daily, many with highly time sensitive content such as …
wide. Numerous tweets are created daily, many with highly time sensitive content such as …
A stacking ensemble model for prediction of multi-type tweet engagements
S Goda, N Agata, Y Matsumura - Proceedings of the Recommender …, 2020 - dl.acm.org
The RecSys Challenge 2020 is a competition with a task of predicting four types of user
engagements on Twitter: Like, Reply, Retweet and Retweet with comment. In this paper, we …
engagements on Twitter: Like, Reply, Retweet and Retweet with comment. In this paper, we …
Knowledge-enhanced collaborative meta learner for long-tail recommendation
Long-tail effect is common in recommender systems, meaning that a tiny number of users
have lots of interaction with items, while the majority of users have extremely little interaction …
have lots of interaction with items, while the majority of users have extremely little interaction …
Engaging with tweets: The missing dataset on social media
SA Alhosseini, R Bin Tareaf, C Meinel - Proceedings of the …, 2020 - dl.acm.org
Most social media websites make use of recommender systems to show the content of
interest for their users and to keep them engaged with the platform. On Twitter users can …
interest for their users and to keep them engaged with the platform. On Twitter users can …
Large-scale User Preference Tracking via Asynchronous and Asymmetric Updating at Twitter
For content recommendation systems on social media platforms, timely, efficient, and
accurate estimation of user preferences can effectively improve their performance and …
accurate estimation of user preferences can effectively improve their performance and …