298 citations · 686 across the 11 of their papers we have counts for
11 papers
How we do things with words: Analyzing text as social and cultural data
Dong Nguyen, Maria Liakata, Simon DeDeo +4
In this article we describe our experiences with computational text analysis. We hope to achieve three primary goals. First, we aim to shed light on thorny issues not always at the…
Quantifying the visual concreteness of words and topics in multimodal datasets
Jack Hessel, David Mimno, Lillian Lee
Multimodal machine learning algorithms aim to learn visual-textual correspondences. Previous work suggests that concepts with concrete visual manifestations may be easier to learn…
Prior-aware Dual Decomposition: Document-specific Topic Inference for Spectral Topic Models
Moontae Lee, David Bindel, David Mimno
Spectral topic modeling algorithms operate on matrices/tensors of word co-occurrence statistics to learn topic-specific word distributions. This approach removes the dependence on…
Cats and Captions vs. Creators and the Clock: Comparing Multimodal Content to Context in Predicting Relative Popularity
Jack Hessel, Lillian Lee, David Mimno
The content of today's social media is becoming more and more rich, increasingly mixing text, images, videos, and audio. It is an intriguing research question to model the interpla…
Robust Spectral Inference for Joint Stochastic Matrix Factorization
Moontae Lee, David Bindel, David Mimno
Spectral inference provides fast algorithms and provable optimality for latent topic analysis. But for real data these algorithms require additional ad-hoc heuristics, and even the…
Beyond Exchangeability: The Chinese Voting Process
Moontae Lee, Seok Hyun Jin, David Mimno
Many online communities present user-contributed responses such as reviews of products and answers to questions. User-provided helpfulness votes can highlight the most useful respo…