Twitter? Yes, we can analyze that…

  2 m, 16 s

If you've got tweets, we've got sentiment. And themes. And most mentioned people. And spam lists. In fact, the only issue we've run into is that Twitter won't give us all the data to analyze. All 100 gazillion tweets would be fascinating to analyze automatically, but they just don't seem to be there yet. Or, perhaps, they are building out their revenue model to sell us the data. Either way, don't fret. Just like in reputation management where analyzing every single document can be both time consuming and incredibly inefficient, the same holds true for tweets. The average of the sentiment is often greater than the individual tweet. As our CEO Jeff Catlin mentioned recently on ZDNet: "Sentiment measurement is at the forefront of much business analysis these days, but in some ways Twitter seems as if it was designed from the ground up to defeat any automated sentiment engine. For instance, there isn't much sentence structure in tweets, and what's there is often wrong. And many of the tweets are just tinyurl or links with absolutely no content contained in the URL itself. Given these challenges, is monitoring and measuring sentiment in Twitter a hopeless chore? Fortunately the answer is No. Even though there are some challenges to automated scoring of Twitter content, there are also some advantages to processing tweets and in particular the tone within Twitter. The beauty of Twitter is that there is very little grey area in tweets. You're either posting some source of information, posting an opinion you have, or replying to another informative or opinion-oriented tweet." With the volumes of online data growing at an unbelievable rate, decreasing processing time and implementing automation become key to getting the job done. And from that automation process comes incredible value such as all the associated concepts and themes with a particular topic. Not just the ones with the most hashtags associated with them. And who is talking about those topics? And who else is mentioned with those topics? The value is not always in the number of mentions, while in some aspects that is helpful, but with the context surrounding the tweets and how businesses can use them. In the coming days we will be attending the Inbound Marketing Summit in Boston where we'll have a demo of our twitter topic tracking system available. We aren't formally releasing a site, or promoting a new product, but we are welcome to conversations about the topic of Twitter Topics and what is useful and what is just fluff. Text analytics doesn't just have to be about processing word documents and research reports - it is just as helpful in processing tweets, customer comments and smaller documents as well.

Categories: Categorization, Sentiment Analysis, Social Media, Text Analytics, Topic Extraction