Changes between Version 4 and Version 5 of private/NlpInPracticeCourse/OpinionSentiment
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- Jul 23, 2015, 4:53:18 PM (8 years ago)
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private/NlpInPracticeCourse/OpinionSentiment
v4 v5 5 5 Prepared by: Zuzana Nevěřilová 6 6 7 == TODO til 31.5.2015==7 == State of the Art == 8 8 9 1. choose particular papers for [[#References|References]] below (that will serve as input for the lecture later on) 10 1. prepare the [[#PracticalSession|Practical Session]] 11 12 == State of the Art == 9 Sentiment analysis can be seen as a text categorization task (i.e. is the writer's opinion on a discussed topic X or Y?). It consists of detection of the topic (which can be easy in focused reviews) and detection of the sentiment (which is generally difficult). Opinions are sometimes expressed in a very subtle manner (e.g. the sentence ''How could anyone sit through this movie?'' contains no negative word) [3]. The sentiments are usually simply classified by their polarity (positive, negative) but they can be recognized more in depth (e.g. strongly negative). Recognized opinions are also subject to summarization (e.g. how many people like this new iPhone design?). 13 10 14 11 === References === 15 12 16 LIU, Bing. Sentiment Analysis and Opinion Mining. Synthesis Lectures on Human Language Technologies. 2012, 5(1): 1-167. DOI: 10.2200/s00416ed1v01y201204hlt016. Draft version available at http://www.cs.uic.edu/~liub/FBS/SentimentAnalysis-and-OpinionMining.pdf 13 1. Bing Liu. Sentiment Analysis and Opinion Mining. Synthesis Lectures on Human Language Technologies. 2012, 5(1): 1-167. DOI: 10.2200/s00416ed1v01y201204hlt016. Draft version available at [[http://www.cs.uic.edu/~liub/FBS/SentimentAnalysis-and-OpinionMining.pdf]] 14 1. Bing Liu. Sentiment Analysis Tutorial. AAAI-2011, August 8, 2011. Slides available at [[http://www.cs.uic.edu/~liub/FBS/Sentiment-Analysis-tutorial-AAAI-2011.pdf]] 15 1. Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan, Thumbs up? Sentiment Classification using Machine Learning Techniques, Proceedings of EMNLP 2002. [[http://www.cs.cornell.edu/home/llee/papers/sentiment.pdf]] 17 16 18 LIU, Bing. Sentiment Analysis Tutorial. AAAI-2011, August 8, 2011. Slides available at http://www.cs.uic.edu/~liub/FBS/Sentiment-Analysis-tutorial-AAAI-2011.pdf 19 20 References: http://www.cs.uic.edu/~liub/FBS/AAAI-2011-tutorial-references.pdf 17 Bing Liu's References: http://www.cs.uic.edu/~liub/FBS/AAAI-2011-tutorial-references.pdf 21 18 22 19 == Practical Session == 23 20 24 Concrete description of work assignment for students for the second one-hour part of the lecture. The work will consist of tasks connected with practical implementations of algorithms connected with the current topic (probably not the state-of-the-art algorithms mentioned in the first part) and with real data. Students can test the algorithms, evaluate them and possibly try some short adaptations for various subtasks. 21 Train classifier on the Movie Review Data [[http://www.cs.cornell.edu/people/pabo/movie-review-data/]]. Measure precision, recall, and F1-score. 25 22 26 Students can also be required to generate some results of their work and hand them in to prove completing the tasks. 23 Train classifier on e-shop evaluation provided by customers and users of www.zbozi.cz. Measure precision, recall, and F1-score. 27 24 28 Test opinion mining on e-shop evaluation provided by customers and users of www.zbozi.cz. 29 30 Rule-based approach, basic machine learning approach. 25 Discuss the differences between training classifiers on Czech and English data.
