Swimming Through Sentiment Analysis with Lexalytics

By Chelsi Nakano (@chelkano) Oct 21, 2010

Everyone has the right to their own opinion, but add the web in the mix and it's not uncommon for companies to find themselves buried under a hill of negative sentiment. Enter Lexalytics (news, site), a company that helps keep track of what's being said and how it's being said.

Sentiment Analysis 101

The definition of Sentiment Analysis is a broad one, but it essentially refers to technology that aims to determine the mood of written text. This means that anyone looking to gain insight into customer opinions expressed on blogs, social networks and other platforms can do so without having to sit there and actually read through them.

An easy example is Scout Labs (news, site), a company that listens to the voice of the customer over social media outlets like Twitter. Another is Thomson Reuters (news, site), an information company that uses sentiment analysis machine readers to help investor trading.

Behind the curtain, the Reuters machines assign numerical “sentiment scores” to words or phrases which are then processed to give an overall positive, neutral or negative score. These scores can then be added together to calculate the overall sentiment for a company, sector, index, etc. Meanwhile, the ScoutLabs application examines opinions, judgments and emotions about topics across the Web, and can then extract helpful quotes, or create graphs that visually represent brand or product reception.

Lift the curtain behind the curtain, and you’ll find Lexalytics, the provider of the sentiment analysis technology that fuels both of these companies, and several others as well.

Lexalytics 101

Though you might not have heard of them, Lexalytics has been doing what they do best since 2003. In addition to Scout Labs and Thomson Reuters, the company’s core text analysis and sentiment software, Salience, powers big names like Cisco Systems and Lithium Technologies, and has also been deployed as part of search solutions in conjunction with Microsoft and Endeca.

According to the company, Salience can work its way through any sort of English language text, and has been integrated into systems for business intelligence, reputation management, automated trading, survey analysis, market intelligence, search and retrieval, customer satisfaction, etc. Because it primarily focuses on the clients' applications, Salience can integrate with BI, dashboards, analytics and data warehouse systems.

Use cases include:

For analysis and measurement providers: Specifically for measuring sentiment across social media platforms like Twitter.
For manufacturing companies: Salience can expose engineering defects, and highlight competitor weaknesses.
For content and media companies: By picking through content and highlighting what works, Salience can boost advertising rates, content re-use, and site stickiness.

Unsurprisingly, the age of information overload has continued to keep Lexalytics busy this year. Let’s look at a couple of the most recent enhancements:

Sentiment Analysis of Short Form Content

This month Lexalytics enhanced reporting around Twitter by creating sentiment analysis for commonly used emoticons and acronyms. For example,

LOL (Laugh Out Loud) — Does not carry sentiment, nor does expanding it add any value to the resulting lexical processing; treated as an interjection
FTW: (For The Win) — Carries positive sentiment
IDK: (I Don’t Know) — Is useful when expanded out to its individual words

Positive: