Use the Twitter Search API. Yes, yes I know people say it's not as complete as the hose, but it's actually quite close to complete if you query it constantly wi

Use the Twitter Search API. Yes, yes I know people say it's not as complete as the hose, but it's actually quite close to complete if you query it constantly without sleeping between requests. Just keep track of the MAX Tweet ID, and get tweets > this ID for every request. Especially for queries where there aren't more than XXX results per minute (yes, even for terms like Bitcoin as u can see here: https://twitter.com/search?q=bitcoin&src=typd&f=realtime https://twitter.com/search?q=bitcoin&src=typd&f=realtime) Then map those tweets to the specific hour (in epoch time for something), or even specific minute, or second if you want more granular detail. Index them to a search index like ElasticSearch or SOLR, and then do a faceted search, which will return the # of results for each time period. You can then graph this fairly easily. The flaw I see in your experiment is that there's a TON of noise in Twitter. Maybe filter out tweets by obvious spam bots (ie looking at follower/following ratio, ignoring users who only tweet hashtags, or URLs, etc).