Web Archiving: “Using Micro-collections in Social Media to Generate Seeds for Web Archive Collections”

The item linked below is an extended version of a paper that will be presented at the ACM/IEEE Joint Conference on Digital Libraries (JCDL 2019) taking place next week in Champaign, IL.

Title

Using Micro-collections in Social Media to Generate Seeds for Web Archive Collections

Authors

Alexander C. Nwala
Old Dominion University

Michele C. Weigle
Old Dominion University

Michael L. Nelson
Old Dominion University

Source 

via arXiv

Abstract

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. We showed that seeds generated by scraping SERPs had a higher median probability (0.63) of producing relevant URIs than micro-collections (0.5). However, micro-collections were more likely to produce seeds with a higher precision than conventional SERP collections for Twitter collections generated with hashtags. Also, micro-collections were more likely to produce older webpages and more non-HTML documents.

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