Twitter Data Conundrum: Sentiment Analysis (Part 3 of 5)

It probably goes without saying that complete and accurate data make for better analysis. While good data is relatively easy for a brand to obtain from its owned media, assuring the integrity of data from earned, yet-to-be-earned and just plain “in-the-wild” text documents has a higher degree of difficulty. Twitter data was specifically cited as problematic by several presenters at the Sentiment Analysis Symposium. After the event, I asked some questions of those who are “in the know” about Twitter data to get some clarity on the issue.

It probably goes without saying that complete and accurate data make for better analysis. While good data is relatively easy for a brand to obtain from its owned media, assuring the integrity of data from earned, yet-to-be-earned and just plain “in-the-wild” text documents has a higher degree of difficulty.

Twitter data was specifically cited as problematic by several presenters at the Sentiment Analysis Symposium. After the event, I asked some questions of those who are “in the know” about Twitter data to get some clarity on the issue.

What’s the problem? Or is there a problem?

Along with the global considerations of sentiment analysis discussed in the last post in this series, tweets are written in a “language” that is not English with structure that may confound discovery and analysis techniques.

AW+

WORK SMARTER - LEARN, GROW AND BE INSPIRED.

Spring Special

Save 30% Off an ADWEEK Subscription Today!

View Your Options

Already a member? Sign in