Lexalytics and Datasift and the Twitter Firehose

  1 m, 2 s

Nick Halstead has launched a new service called Datasift. Datasift exists to help you filter the twitter firehose, chopping things up along any vector you can think of (and more). For example, you can do simple keyword filtering, but across a polygon that defines a geographical locale around the tweet-er, and only includes positive tweets. And that’s where we come in. They integrated Lexalytics’ Salience Engine to provide our entity extraction and sentiment analysis functionality. In a matter (literally) of a few days of integration work, they had the power of Salience available for filtering the entire Twitter firehose.


So, 20 different vectors are available from Salience… These include the ability to automatically extract company/people/product names (without having a list of them ahead of time), the ability to calculate tweet, entity, and “linked-content” sentiment, output lists of positive/negative entities, output quoted content and more. Example Tweet streams: * Movies getting positive reviews. * Coffee shops that are getting negative reviews within 10 miles of me (so that I can go sell them something to help them do better). * People mentioned in positive tweets about the US Government This is a really exciting new service that provides a super-sophisticated way to slice and dice the whole of the Twitter firehose…

Categories: Announcements, Sentiment Analysis, Social Media