Ask Slater Is sentiment analysis in Twitter old or active research? May 25, 2018 by adamdev Ā There was a particular surge in Twitter sentiment analysis in the early days of Twitter (pre-2015). It was a somewhat narrow window where this kind of research was extremely exciting because all of the traditional approaches to sentiment analysis relied on more formal corpora and these approaches broke down dramatically when applied to Twitter (as […] Read more Ā»
Ask Slater Is feature selection needed to be performed in lexicon-based sentiment analysis? March 27, 2018 by adamdev Ā The two are typically at odds. Generally speaking your lexicon defines your features. So youāre performing feature selection as you build the lexicon and once you have your lexicon you stop choosing new features. If youāre starting with a lexicon and want to add features you could add them to the lexicon youāre working with, […] Read more Ā»
Ask Slater How can l explain why transfer learning gives better performance than standard training? August 21, 2017 by adamdev Ā If youāre looking for an analogy that will explain the concept to a non technical user (unclear from question) here are my two favorite analogies: Imagine you were trying to learn sentiment analysis in Mandarin. Eventually you would be able to figure it out if we showed you enough examples, but it would take a […] Read more Ā»
Ask Slater When measuring the classification accuracy on the training set, can I take a sample of it or should I use it entirely? July 26, 2017 by adamdev Ā Usually inference is the fast part so you measure on the whole dataset once per epoch. The problem with measuring on a sample is that for most useful things (like measuring test/train divergence) this injects so much noise into the signal that itās much less useful. Itās contingent more on the overall size of your […] Read more Ā»
