Twitter has proven a powerful tool to shape peoples’ opinions and thoughts. One efficient way to spread information is with the use of links. In this paper, we characterize the link sharing usage on Twitter, placing particular focus on third-party link shortener services that hide the full URL from the user. First, we present a measurement framework that combines two Twitter APIs and the Bitly API, and allows us to collect detailed statistics about tweets, their posters, their link usage, and the retweets and clicks 24 hours after the original tweet. Second, using two one-week-long datasets, collected one year apart (April 2019 and2020), we then characterize and analyze important difference in link usage among users, the domains that different users and shorteners (re)direct users too, and compare the click rates of such links with the corresponding retweet rates. The analysis provides insights into link sharing biases on Twitter, skews, and behavioral differences in usage, as well as reveal interesting observations capturing differences in how a tweet containing a link may be retweeted versus how the embedded link is clicked. Finally, we use click-based results for covid-19 tweets to discuss the importance of controlling the spread of (mis)information.