Sentiment Extraction: Measuring the Emotional Tone of Text
Sentiment scoring is emotion! Is the text positive or negative? Good or bad? How will you know if you don't look? How can you look by hand if its millions of comments per hour?
The obvious limitations of manual sentiment scoring and sentiment analysis led to the development of machine scoring. Once you have reliable, consistent machine-based sentiment scoring, there are a number of easy applications; reputation management (the problem every marketing person faces), “voice of customer” (listen to how they’re saying what they say, don’t constrain them to closed-ended questions), eDiscovery (was there a wave of negative emails before a certain crisis hit?), etc…
Lexalytics has provided text mining and sentiment analysis for over nine years now. As such, we have a substantial amount of experience and know where it works well. Unfortunately, many vendors haven’t been doing it as long as we have, so you need to be wary of over-reaching claims and confusing descriptions by the vendors rolling out early sentiment analysis engines.
This pages will demystify sentiment scoring and explain how the Lexalytics sentiment analysis engine works. This includes a discussion of how and why we have extended the basic concept of document sentiment to the paragraph and entity level, and how this technology is being further extended to measure other indicators within content, including the assessment of threat, customer satisfaction and many other contextual indicators.