Posted by iPullRank
"Michael Jackson" Tweets
"Michael Jackson" Search Volume

If this is still unclear check out the Google Books Ngram viewer ; it’s a pretty cool way to get a good idea of what Ngrams are. Also you should check out John Doherty’s Google Analytics Advanced Segments post where talks about how to segment N-grams using RegEx.
Real-Time Keyword Research Methodology
Now that we’ve got the small vocabulary update out of the way let’s talk about how you can do keyword research in real-time. The following methodology was developed by my friend Ron Sansone with some small revisions from me in order to port it into code.
1. Pull all the tweets containing your keyword from Twitter Search within the last hour. This part is pretty straightforward; you want to pull down the most recent portion of the conversation right now in order to extract patterns. Use Topsy for this. If you’re not using Topsy, pulling the last 200 tweets via Twitter is also a good sized data set to use.
2. Identify the top 10 most repeated N-grams ignoring stop words. Here you identify the keywords with the highest (ugh) density. In other words the keywords that are tweeted the most are the ones you are considering for optimization. Be sure to keep this between 2 and 5 N-grams beyond that you most likely not dealing with a large enough search volume to make your efforts worthwhile. Also be sure to exclude stop words so you don’t end up with n-grams like “jackson the” or “has Michael.” Here’s a list of English stop words and Textalyser has an adequate tool for breaking a block of text into N-grams.
3. Check to see if there is already search volume in the Adwords Keyword tool or Google Insights. This process is not just about identifying breakout keywords that aren’t being shown yet in Google Insights but it’s also about identifying keywords with existing search volume that are about to get boost. Therefore you’ll want to check the Search Engine tools to see if any search volume exists in order to prioritize opportunities.
4. Pull the Klout scores of all the users tweeting them. Yeah, yeah I know Klout is a completely arbitrary calculation but you want to know that the people tweeting the keywords have some sort of influence. If you find that a given N-gram has been used many times by a bunch of spammy Twitter profiles then that N-gram is absolutely not useful. Also if you create content around the given term, you’ll know exactly who to send it to.
Methodology Expanded

"Michael Jackson" Social Mention

