Annotating and Training for Population Subjective Views
Maria Alexeeva, Caroline Hyland, Keith Alcock, Allegra A. Beal Cohen, Hubert Kanyamahanga, Isaac Kobby Anni, Mihai Surdeanu
The 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis Long Paper
TLDR:
In this paper, we present a dataset of subjective views (beliefs and attitudes) held by individuals or groups. We analyze the usefulness of the dataset by training a neural classifier that identifies belief-containing sentences that are relevant for our broader project of interest---scientific model
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Abstract:
In this paper, we present a dataset of subjective views (beliefs and attitudes) held by individuals or groups. We analyze the usefulness of the dataset by training a neural classifier that identifies belief-containing sentences that are relevant for our broader project of interest---scientific modeling of complex systems. We also explore and discuss difficulties related to annotation of subjective views and propose ways of addressing them.