6 citations · 11 across the 3 of their papers we have counts for
6 papers
Mixed Feelings, Single Polarity
Emily Öhman, Saif Mohammad
Emotion datasets are routinely mapped onto positive and negative valence, by assigning each emotion category one polarity. We test where this works and where it fails, using SemEva…
Fear Is Not Always Fear: Variation in Emotion Label Equivalence Across Datasets
Emily Öhman, Anna Koufakou
Emotion classifiers are routinely applied beyond their training data, on the assumption that same-named labels such as fear or surprise mean the same thing across resources. We tes…
Affect as a proxy for literary mood
Emily Öhman, Riikka Rossi
We propose to use affect as a proxy for mood in literary texts. In this study, we explore the differences in computationally detecting tone versus detecting mood. Methodologically…
Hate speech, Censorship, and Freedom of Speech: The Changing Policies of Reddit
Elissa Nakajima Wickham, Emily Öhman
This paper examines the shift in focus on content policies and user attitudes on the social media platform Reddit. We do this by focusing on comments from general Reddit users from…
SELF & FEIL: Emotion and Intensity Lexicons for Finnish
Emily Öhman
This paper introduces a Sentiment and Emotion Lexicon for Finnish (SELF) and a Finnish Emotion Intensity Lexicon (FEIL). We describe the lexicon creation process and evaluate the l…
XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection
Emily Öhman, Marc Pàmies, Kaisla Kajava +1
We introduce XED, a multilingual fine-grained emotion dataset. The dataset consists of human-annotated Finnish (25k) and English sentences (30k), as well as projected annotations f…