Annika Marie Schoene

According to our database, Annika Marie Schoene authored at least 20 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Language.

Annika Marie Schoene, John E. Ortega, Rodolfo Joel Zevallos Salazar, Laura Haaber Ihle

Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024

Why the Gaming Industry Needs Responsible AI.

Cansu Canca, Laura Haaber Ihle, Annika Marie Schoene

Games Res. Pract., June, 2024

MEANT: Multimodal Encoder for Antecedent Information.

Benjamin J. Irving, Annika Marie Schoene

CoRR, 2024

Is it safe to machine translate suicide-related language from English to Galician?

John E. Ortega, Annika Marie Schoene

Proceedings of the 16th International Conference on Computational Processing of Portuguese, 2024

2023

Emerging trends: Unfair, biased, addictive, dangerous, deadly, and insanely profitable.

Kenneth Church, Annika Marie Schoene, John E. Ortega, Raman Chandrasekar, Valia Kordoni

Nat. Lang. Eng., March, 2023

Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes.

Annika Marie Schoene, Alexander P. Turner, Geeth de Mel, Nina Dethlefs

IEEE Trans. Affect. Comput., 2023

Classifying Suicide-Related Content and Emotions on Twitter Using Graph Convolutional Neural Networks.

Annika Marie Schoene, Lana Bojanic, Minh-Quoc Nghiem, Isabelle M. Hunt, Sophia Ananiadou

IEEE Trans. Affect. Comput., 2023

An Example of (Too Much) Hyper-Parameter Tuning In Suicide Ideation Detection.

Annika Marie Schoene, John E. Ortega, Silvio Amir, Kenneth Church

Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, 2023

2022

Natural language processing applied to mental illness detection: a narrative review.

Tianlin Zhang, Annika Marie Schoene, Shaoxiong Ji, Sophia Ananiadou

npj Digit. Medicine, 2022

RELATE: Generating a linguistically inspired Knowledge Graph for fine-grained emotion classification.

Annika Marie Schoene, Nina Dethlefs, Sophia Ananiadou

Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

2021

Deep learning with knowledge graphs for fine-grained emotion classification in text.

Annika Marie Schoene

PhD thesis, 2021

A divide-and-conquer approach to neural natural language generation from structured data.

Nina Dethlefs, Annika Marie Schoene, Heriberto Cuayáhuitl

Neurocomputing, 2021

2020

Improving the Transparency of Deep Neural Networks using Artificial Epigenetic Molecules.

George Lacey, Annika Marie Schoene, Nina Dethlefs, Alexander P. Turner

Proceedings of the 12th International Joint Conference on Computational Intelligence, 2020

Bidirectional Dilated LSTM with Attention for Fine-grained Emotion Classification in Tweets.

Annika Marie Schoene, Alexander P. Turner, Nina Dethlefs

Proceedings of the 3rd Workshop on Affective Content Analysis (AffCon 2020) co-located with Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020), 2020

Hybrid Approaches to Fine-Grained Emotion Detection in Social Media Data.

Annika Marie Schoene

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Pooling Tweets by Fine-Grained Emotions to Uncover Topic Trends in Social Media.

Annika Marie Schoene, Geeth de Mel

Proceedings of the 22th International Conference on Information Fusion, 2019

Modularity Within Artificial Gene Regulatory Networks.

George Lacey, Annika Marie Schoene, Nina Dethlefs, Alexander P. Turner

Proceedings of the IEEE Congress on Evolutionary Computation, 2019

Dilated LSTM with attention for Classification of Suicide Notes.

Annika Marie Schoene, George Lacey, Alexander P. Turner, Nina Dethlefs

Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis LOUHI@EMNLP 2019, 2019

2018

Evolutionary Constraint in Artificial Gene Regulatory Networks.

Alexander P. Turner, George Lacey, Annika Marie Schoene, Nina Dethlefs

Proceedings of the Advances in Computational Intelligence Systems, 2018

2016

Automatic Identification of Suicide Notes from Linguistic and Sentiment Features.

Annika Marie Schoene, Nina Dethlefs

Proceedings of the 10th SIGHUM Workshop on Language Technology for Cultural Heritage, 2016