  In previous work we reported that resources linked in tweets disappeared at
the rate of 11% in the first year followed by 7.3% each year afterwards. We
also found that in the first year 6.7%, and 14.6% in each subsequent year, of
the resources were archived in public web archives. In this paper we revisit
the same dataset of tweets and find that our prior model still holds and the
calculated error for estimating percentages missing was about 4%, but we found
the rate of archiving produced a higher error of about 11.5%. We also
discovered that resources have disappeared from the archives themselves (7.89%)
as well as reappeared on the live web after being declared missing (6.54%). We
have also tested the availability of the tweets themselves and found that
10.34% have disappeared from the live web. To mitigate the loss of resources on
the live web, we propose the use of a "tweet signature". Using the Topsy API,
we extract the top five most frequent terms from the union of all tweets about
a resource, and use these five terms as a query to Google. We found that using
tweet signatures results in discovering replacement resources with 70+% textual
similarity to the missing resource 41% of the time.
