  In a Web plagued by disappearing resources, Web archive collections provide a
valuable means of preserving Web resources important to the study of past
events ranging from elections to disease outbreaks. These archived collections
start with seed URIs (Uniform Resource Identifiers) hand-selected by curators.
Curators produce high quality seeds by removing non-relevant URIs and adding
URIs from credible and authoritative sources, but it is time consuming to
collect these seeds. Two main strategies adopted by curators for discovering
seeds include scraping Web (e.g., Google) Search Engine Result Pages (SERPs)
and social media (e.g., Twitter) SERPs. In this work, we studied three social
media platforms in order to provide insight on the characteristics of seeds
generated from different sources. First, we developed a simple vocabulary for
describing social media posts across different platforms. Second, we introduced
a novel source for generating seeds from URIs in the threaded conversations of
social media posts created by single or multiple users. Users on social media
sites routinely create and share posts about news events consisting of
hand-selected URIs of news stories, tweets, videos, etc. In this work, we call
these posts micro-collections, and we consider them as an important source for
seeds because the effort taken to create micro-collections is an indication of
editorial activity, and a demonstration of domain expertise. Third, we
generated 23,112 seed collections with text and hashtag queries from 449,347
social media posts from Reddit, Twitter, and Scoop.it. We collected in total
120,444 URIs from the conventional scraped SERP posts and micro-collections. We
characterized the resultant seed collections across multiple dimensions
including the distribution of URIs, precision, ages, diversity of webpages,
etc...
