Lexalytics Unveils Sentiment Analysis of Emoticons, Acronyms; First OEM Engine to Examine Short Form Content for Sentiment Analysis

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Lexalytics announces the availability of richer reporting on the conversations occurring around, about, and between different accounts on Twitter based on the sentiment analysis of commonly used emoticons and acronyms.

“We spent a few months enabling our software to better deal with such content,” said Lexalytics CEO Jeff Catlin. “The improvements we made make processing this content significantly more valuable.”

Lexalytics, Inc. (http://www.lexalytics.com), a software and services company specializing in text and sentiment analysis, announced the availability of richer reporting on the conversations occurring around, about, and between different accounts on Twitter based on the sentiment analysis of commonly used emoticons and acronyms.

With the use of emoticons, abbreviations, and confusing “social speak” grammar, micro-blog services such as Twitter present a difficult task for natural language processing systems. These improvements come as part of the yearly software license for Salience, Lexalytics’ core text analytics engine.

“We spent a few months enabling our software to better deal with such content,” said Lexalytics CEO Jeff Catlin. “The improvements we made make processing this content significantly more valuable.”

For acronyms, the Lexalytics team parsed thousands of tweets to get to hundreds of common acronyms and emoticons. The team then made decisions on whether each acronym was sentiment-bearing, needed to be expanded, or should be treated as simply an interjection. 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

With emoticons, some are obviously positive or negative while others are considered more neutral. Examples include:

Positive:
:D
8)
;)

Negative:
:/
:<
:(
:S

For the @ sign, Salience part-of-speech tags the @ tagged string as a “MENTION” which can be used for further reporting. In particular, @ tagged strings will return as people entities, with the associated sentiment, themes, etc.

Additionally, # sign (hashtags) are part-of-speech tagged as @hashtag. These do not report back as any sort of entity type. Hashtags are typically used as a lightweight “tag” for the content of the tweet. This information can be used by Salience for further processing as a tag.

Check out the new capabilities at http://www.lexalytics.com/demo. Select the “Twitter” radio button. Paste a tweet in and test out what Lexalytics returns.

Lexalytics’ out-of-the-box, business critical text analytics and sentiment solutions allows companies to monitor and react in real-time by making sense of the vast repositories of information from sources as diverse as Twitter, blogs, RSS feeds, web sites and in-house content. Lexalytics solutions include entity extraction, theme discovery, and sentiment analysis at the entity-level.

About Lexalytics
Lexalytics, Inc. is a software and services company specializing in text and sentiment analysis for social media monitoring, reputation management and entity-level text and sentiment analysis. By enabling organizations to make sense of the vast content repositories on sources like Twitter, blogs, forums, web sites and in-house documents, Lexalytics provides the context necessary for informed critical business decisions. Serving a range of Fortune 500 companies in the financial, search and media industries, among others, Lexalytics partners with industry leaders such as FAST, Endeca, ThomsonReuters, and BurrellesLuce to deliver the most effective sentiment analysis solutions in the industry. For more information, visit http://www.lexalytics.com. Lexalytics also provides expert commentary on text and sentiment analysis on its blog and Twitter via @Lexalytics.

Media Contacts:
Ann Shannon /Shannon Costello
PAN Communications
978-474-1900

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