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Interleaved snowballing: Reducing the workload of literature curators

Ralf Stephan

TL;DR

It is shown that the improved algorithm can substantially reduce curator work, even before application of text classification, by reducing the number of candidates to classify.

Abstract

We formally define the literature (reference) snowballing method and present a refined version of it. We show that the improved algorithm can substantially reduce curator work, even before application of text classification, by reducing the number of candidates to classify. We also present a desktop application named LitBall that implements this and other literature collection methods, through access to the Semantic Scholar academic graph (S2AG).

Interleaved snowballing: Reducing the workload of literature curators

TL;DR

It is shown that the improved algorithm can substantially reduce curator work, even before application of text classification, by reducing the number of candidates to classify.

Abstract

We formally define the literature (reference) snowballing method and present a refined version of it. We show that the improved algorithm can substantially reduce curator work, even before application of text classification, by reducing the number of candidates to classify. We also present a desktop application named LitBall that implements this and other literature collection methods, through access to the Semantic Scholar academic graph (S2AG).
Paper Structure (7 sections, 4 equations, 1 table, 2 algorithms)

This paper contains 7 sections, 4 equations, 1 table, 2 algorithms.

Table of Contents

  1. Introduction
  2. Definitions
  3. Snowballing and Interleaved Snowballing
  4. LitBall: the application
  5. Discussion