Sentiment Analysis: Machines Are Like Us
Interesting post but in particular for:
We are very aware of the importance of industry-specific language here at Brandwatch and we do our best to offer language analysis that specialises in industries as much as possible.
We constantly refine our language systems by adding newly trained classifiers (a classifier is the particular system used to detect and analyse the language of a query’s matches – which classifier should be used is determined upon query creation).
We have over 500 classifiers for different industries across the 17 languages we cover.
Did you catch that? Over 500 classifiers for different industries.
In other words, we don’t need a single classifier that does all the heavy lifting on entity recognition for building topic maps. We could, for example, train a classifier for use with all the journals in a field or sub-field. For astronomy, for example, we don’t have to disambiguate all the various uses of “Venus” but can concentrate on the one most likely to be found in a sub-set of astronomy literature.
By using specialized classifiers, perhaps we can reduce the target for more generalized classifiers to a manageable size.