69 citations · 215 across the 16 of their papers we have counts for
6 papers · 1 filter
RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation
Yu Zhang, Wei Wei, Binxuan Huang +2
Real-time location inference of social media users is the fundamental of some spatial applications such as localized search and event detection. While tweet text is the most common…
A Weakly Supervised Approach for Classifying Stance in Twitter Replies
Sumeet Kumar, Ramon Villa Cox, Matthew Babcock +1
Conversations on social media (SM) are increasingly being used to investigate social issues on the web, such as online harassment and rumor spread. For such issues, a common thread…
Stance in Replies and Quotes (SRQ): A New Dataset For Learning Stance in Twitter Conversations
Ramon Villa-Cox, Sumeet Kumar, Matthew Babcock +1
Automated ways to extract stance (denying vs. supporting opinions) from conversations on social media are essential to advance opinion mining research. Recently, there is a renewed…
Parameterized Convolutional Neural Networks for Aspect Level Sentiment Classification
Binxuan Huang, Kathleen M. Carley
We introduce a novel parameterized convolutional neural network for aspect level sentiment classification. Using parameterized filters and parameterized gates, we incorporate aspec…
Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks
Binxuan Huang, Kathleen M. Carley
Aspect level sentiment classification aims to identify the sentiment expressed towards an aspect given a context sentence. Previous neural network based methods largely ignore the…
Aspect Level Sentiment Classification with Attention-over-Attention Neural Networks
Binxuan Huang, Yanglan Ou, Kathleen M. Carley
Aspect-level sentiment classification aims to identify the sentiment expressed towards some aspects given context sentences. In this paper, we introduce an attention-over-attention…