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A Swiss German Dictionary: Variation in Speech and Writing ...
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Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation
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In: Findings of the Association for Computational Linguistics: EMNLP 2020 (2020)
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Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation ...
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Sentiment Analysis Using a Novel Human Computation Game
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In: http://infoscience.epfl.ch/record/269072 (2019)
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Dataset Construction via Attention for Aspect Term Extraction with Distant Supervision
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In: http://infoscience.epfl.ch/record/269011 (2019)
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Churn Intent Detection in Multilingual Chatbot Conversations and Social Media ...
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Machine Translation of Low-Resource Spoken Dialects: Strategies for Normalizing Swiss German ...
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Semi-Supervised Method for Multi-Category Emotion Recognition in Tweets
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In: http://infoscience.epfl.ch/record/210750 (2015)
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EmotionWatch: Visualizing Fine-Grained Emotions in Event-Related Tweets
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In: Proceedings of the International AAAI Conference on Web and Social Media; Vol. 8 No. 1 (2014): Eighth International AAAI Conference on Weblogs and Social Media ; 2334-0770 ; 2162-3449 (2014)
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Constructing Context-Aware Sentiment Lexicons with an Asynchronous Game with a Purpose
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In: http://infoscience.epfl.ch/record/203147 (2014)
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Abstract:
One of the reasons sentiment lexicons do not reach human-level performance is that they lack the contexts that define the polarities of words. While obtaining this knowledge through machine learning would require huge amounts of data, context is commonsense knowledge for people, so human computation is a better choice. We identify context using a game with a purpose that increases the workers' engagement in this complex task. With the contextual knowledge we obtain from only a small set of answers, we already halve the sentiment lexicons' performance gap relative to human performance.
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URL: https://doi.org/10.1007/978-3-642-54903-8_3 http://infoscience.epfl.ch/record/203147 https://infoscience.epfl.ch/record/203147/files/boia-cicling14.pdf
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A :) Is Worth a Thousand Words: How People Attach Sentiment to Emoticons and Words in Tweets
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In: http://infoscience.epfl.ch/record/197177 (2014)
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Fine-Grained Emotion Recognition in Olympic Tweets Based on Human Computation
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In: http://infoscience.epfl.ch/record/197185 (2014)
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