Leveraging the power of social reading and big data: an analysis of co-read clusters of books on Goodreads

Ridenour, Laura; Jeong, Wooseob

Permalink

https://hdl.handle.net/2142/89314 Copy

Description

Title

Leveraging the power of social reading and big data: an analysis of co-read clusters of books on Goodreads

Author(s)

Ridenour, Laura; Jeong, Wooseob

Issue Date

2016-03-15

Keyword(s)

• readers’ advisory
• bibliometric coupling
• big data
• informetrics

Date of Ingest

2016-03-08T22:51:50Z

Abstract

Readers’ advisory services must keep up with ever-increasing numbers of published titles. We explore a method to identify potentially appealing book recommendations based on the use of bibliographic coupling from data gathered from the social reading site, Goodreads. In this case, books are considered to be similar in appeal to other books read by a user if a co-read pair of books occurs. Co-read book pairs were processed and rendered visually in Gephi, creating two visualizations: one with extremely popular titles, and one without. This method has the potential to augment traditional readers’ advisory services by leveraging readily available big data and open source software.

Publisher

iSchools

Series/Report Name or Number

IConference 2016 Proceedings

Type of Resource

text

Genre of Resource

Conference Paper / Presentation

Language

eng

Permalink

http://hdl.handle.net/2142/89314

DOI

https://doi.org/10.9776/16292

Copyright and License Information

Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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