This episode of Fresh Machine Learning is all Tone Analysis. Tone analysis consists of not just analyzing sentiment (positive or negative), but also analyzing emotions as well as writing style. There are a lot of dimensions to tone, and in this episode I talk about what I consider to be 3 seminal papers in this field. At the end of the episode, we use IBM’s Watson Tone Analyzer API to build our own tone analysis web app.
The demo code for this video can be found here:
https://github.com/llSourcell/Tone-Analyzer
I created a Slack channel for us, sign up here:
https://wizards.herokuapp.com/
I introduce three papers in this video
Convolutional neural networks for sentence classification:
http://emnlp2014.org/papers/pdf/EMNLP2014181.pdf
Text categorization using LSTM for region embeddings:
http://arxiv.org/pdf/1602.02373v2.pdf
Hierarchical attention networks for document classification:
https://www.cs.cmu.edu/~diyiy/docs/naacl16.pdf
More info about the IBM Watson Tone Analyzer API:
http://www.ibm.com/watson/developercloud/tone-analyzer.html
Some great notes, slides, and practice problems for NLP:
http://cs224d.stanford.edu/syllabus.html
Live demo of the Watson Tone Analyzer:
https://tone-analyzer-demo.mybluemix.net/
Really great long-form page talking about text classification
http://www.nltk.org/book/ch06.html
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