Computing Feelings: Danish Approaches to Sentiment Analysis - Daniel Hardt
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This document discusses Danish approaches to sentiment analysis, which is the computational study of opinions, sentiments and emotions expressed in text. It covers machine learning methods like bag-of-words modeling and algorithms like naive Bayes, maximum entropy, and support vector machines. It also discusses deep learning approaches using the Stanford Sentiment Treebank to model semantic compositionality. The document is a presentation by Daniel Hardt from Copenhagen Business School on sentiment analysis research.
Computing Feelings: Danish Approaches to Sentiment Analysis - Daniel Hardt
- 1. Computing Feelings: Danish Approaches to Sentiment Analysis Daniel Hardt Copenhagen Business School 21 February 2014 Daniel Hardt Computing Feelings: Danish Approaches to Sentiment Analy
- 2. Business Daniel Hardt Computing Feelings: Danish Approaches to Sentiment Analy
- 3. Business Daniel Hardt Computing Feelings: Danish Approaches to Sentiment Analy
- 4. Business Daniel Hardt Computing Feelings: Danish Approaches to Sentiment Analy
- 5. Business Daniel Hardt Computing Feelings: Danish Approaches to Sentiment Analy
- 6. Liu, Bing. Sentiment analysis and subjectivity Handbook of natural language processing 2 (2010): 568. Sentiment analysis or opinion mining is the computational study of opinions, sentiments and emotions expressed in text Daniel Hardt Computing Feelings: Danish Approaches to Sentiment Analy
- 7. Machine Learning Methods Pang, Bo, Lillian Lee, and Shivakumar Vaithyanathan. "Thumbs up?: sentiment classification using machine learning techniques." Proceedings of the ACL-02 conference on Empirical methods in natural language processing-Volume 10. Association for Computational Linguistics, 2002. Bag of words: With lexicon of m words, each document d is represented by the document vector (n1 (d), n2 (d), ..., nm (d)) Machine Learning: Naive Bayes, Maximum Entropy, Support Vector Machines Naive Bayes: Daniel Hardt Computing Feelings: Danish Approaches to Sentiment Analy
- 8. Deep Learning: Stanford Sentiment Treebank Socher, Richard, et al. "Recursive deep models for semantic compositionality over a sentiment treebank." Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP). 2013. Daniel Hardt Computing Feelings: Danish Approaches to Sentiment Analy