activity
20152019
most citedUsing millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

431 citations · 462 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2019★ 6 cited

Evaluating Style Transfer for Text

Remi Mir, Bjarke Felbo, Nick Obradovich +1

Research in the area of style transfer for text is currently bottlenecked by a lack of standard evaluation practices. This paper aims to alleviate this issue by experimentally iden…

cs.CL2018

Comparing Models of Associative Meaning: An Empirical Investigation of Reference in Simple Language Games

Judy Hanwen Shen, Matthias Hofer, Bjarke Felbo +1

Simple reference games are of central theoretical and empirical importance in the study of situated language use. Although language provides rich, compositional truth-conditional s…

cs.CY2018★ 22 cited

Closing the AI Knowledge Gap

Ziv Epstein, Blakeley H. Payne, Judy Hanwen Shen +6

AI researchers employ not only the scientific method, but also methodology from mathematics and engineering. However, the use of the scientific method - specifically hypothesis tes…

cs.CL2017★ 3 cited

A First Step in Combining Cognitive Event Features and Natural Language Representations to Predict Emotions

Andres Campero, Bjarke Felbo, Joshua B. Tenenbaum +1

We explore the representational space of emotions by combining methods from different academic fields. Cognitive science has proposed appraisal theory as a view on human emotion wi…

stat.ML2017★ 431 cited

Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

Bjarke Felbo, Alan Mislove, Anders Søgaard +2

NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment analysis and related tasks, researchers have therefore used binarized emoticons and sp…

cs.LG2015

Modeling the Temporal Nature of Human Behavior for Demographics Prediction

Bjarke Felbo, Pål Sundsøy, Alex 'Sandy' Pentland +2

Mobile phone metadata is increasingly used for humanitarian purposes in developing countries as traditional data is scarce. Basic demographic information is however often absent fr…