Papers by Andreas Hanselowski

2 papers
A Retrospective Analysis of the Fake News Challenge Stance-Detection Task (C18-1)

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Challenge: 2017 Fake News Challenge Stage 1 (FNC-1) shared task addressed a stance classification task as a crucial first step towards detecting fake news.
Approach: They propose a new evaluation metric favoring the majority class, which can be easily classified, and propose stacked LSTM models that perform on par with the best systems, but is superior in predicting minority classes.
Outcome: The proposed evaluation metric favors the majority class, which can be easily classified, and overestimates the true discriminative power of the methods.
Beyond Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous Data (L18-1)

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Challenge: Automated summarization has focused on ten to twenty documents, typically news articles, but could in theory analyze hundreds of documents from a wide range of sources and provide an overview to the interested reader.
Approach: They propose a method for creating hierarchical summarization corpora from large, heterogeneous document collections by crowdsourcing relevant content and asking trained annotators to order the relevant information hierarchically.
Outcome: The proposed method can be used to develop and evaluate hierarchical summarization systems.

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