Suggesting Hashtags on Twitter

As micro-blogging sites, like Twitter, continue to grow in popularity, we are presented with the problem of how to effectively categorize and search for posts. Looking specifically at Twitter, we see that users may categorize their posts using hashtags, and any word or phrase may be used as the category. Attempting to search for tweets about Facebook, a user would need to try many different hashtags, like #Facebook, #FB, #Facebook.com, or #Zuckerberg. To combat this, we propose, implement and evaluate a tool for suggesting relevant hashtags to a user, given a tweet. Initial analyses suggest our dataset is rich enough to extract informative distributions of words for many hashtags that will facilitate a naive Bayes model for hashtag recommendation given a query post.