63 citations · 345 across the 53 of their papers we have counts for
8 papers · 1 filter
GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception
Laura Bostan, Evgeny Kim, Roman Klinger
Most research on emotion analysis from text focuses on the task of emotion classification or emotion intensity regression. Fewer works address emotions as a phenomenon to be tackle…
Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning
Deniz Cevher, Sebastian Zepf, Roman Klinger
The recognition of emotions by humans is a complex process which considers multiple interacting signals such as facial expressions and both prosody and semantic content of utteranc…
Embedding Projection for Targeted Cross-Lingual Sentiment: Model Comparisons and a Real-World Study
Jeremy Barnes, Roman Klinger
Sentiment analysis benefits from large, hand-annotated resources in order to train and test machine learning models, which are often data hungry. While some languages, e.g., Englis…
An Analysis of Emotion Communication Channels in Fan Fiction: Towards Emotional Storytelling
Evgeny Kim, Roman Klinger
Centrality of emotion for the stories told by humans is underpinned by numerous studies in literature and psychology. The research in automatic storytelling has recently turned tow…
Crowdsourcing and Validating Event-focused Emotion Corpora for German and English
Enrica Troiano, Sebastian Padó, Roman Klinger
Sentiment analysis has a range of corpora available across multiple languages. For emotion analysis, the situation is more limited, which hinders potential research on cross-lingua…
Exploring Fine-Tuned Embeddings that Model Intensifiers for Emotion Analysis
Laura Bostan, Roman Klinger
Adjective phrases like "a little bit surprised", "completely shocked", or "not stunned at all" are not handled properly by currently published state-of-the-art emotion classificati…
Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters
Evgeny Kim, Roman Klinger
The development of a fictional plot is centered around characters who closely interact with each other forming dynamic social networks. In literature analysis, such networks have m…
Adversarial Training for Satire Detection: Controlling for Confounding Variables
Robert McHardy, Heike Adel, Roman Klinger
The automatic detection of satire vs. regular news is relevant for downstream applications (for instance, knowledge base population) and to improve the understanding of linguistic…