Titlebook: Computational Linguistics and Intelligent Text Processing; 15th International C Alexander Gelbukh Conference proceedings 2014 Springer-Verl

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Reader Emotion Prediction Using Concept and Concept Sequence Features in News Headlinesf Sina Social News with user emotion votes show that the proposed approach which do not use any news content, achieves a comparable performance to Bag-Of-Word model using both the headlines and the news contents, making our method more efficient in reader emotion prediction.

玉米

Investigating the Role of Emotion-Based Features in Author Gender Classification of Texte (SVM) algorithm can be reached. Over 75% cross-validation accuracy is reached when classifying the author gender of blog texts. Our findings show positive implications of emotion-based features on assisting author’s gender classification.

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https://doi.org/10.1007/978-3-663-04930-2 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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,Modelluntersuchungen zur Strahllüftung, sentiment classification. In addition we demonstrate that through use of the Multinomial Na?ve Bayes classifier we can minimise the detrimental effects of discourse function during sentiment analysis.

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