Search Results for author:
Found 7 papers, 2 papers with code
Predicting the Topical Stance and Political Leaning of Media using Tweets
Discovering the stances of media outlets and influential people on current, debatable topics is important for social statisticians and policy makers.
Predicting the Role of Political Trolls in Social Media
In particular, we show how to classify trolls according to their political role ---left, news feed, right--- by using features extracted from social media, i. e., Twitter, in two scenarios: (i) in a traditional supervised learning scenario, where labels for trolls are available, and (ii) in a distant supervision scenario, where labels for trolls are not available, and we rely on more-commonly-available labels for news outlets mentioned by the trolls.
Predicting the Topical Stance of Media and Popular Twitter Users
Discovering the stances of media outlets and influential people on current, debatable topics is important for social statisticians and policy makers.
Recursive Style Breach Detection with Multifaceted Ensemble Learning
We present a supervised approach for style change detection, which aims at predicting whether there are changes in the style in a given text document, as well as at finding the exact positions where such changes occur.
Resolving Gendered Ambiguous Pronouns with BERT
Pronoun resolution is part of coreference resolution, the task of pairing an expression to its referring entity.
Deploying AI Frameworks on Secure HPC Systems with Containers
The increasing interest in the usage of Artificial Intelligence techniques (AI) from the research community and industry to tackle "real world" problems, requires High Performance Computing (HPC) resources to efficiently compute and scale complex algorithms across thousands of nodes.
Tweety at SemEval-2018 Task 2: Predicting Emojis using Hierarchical Attention Neural Networks and Support Vector Machine
We present the system built for SemEval-2018 Task 2 on Emoji Prediction.
