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We rely on filters to make sense of the scholarly literature, but the narrow, traditional filters are being swamped. However, the growth of new, online scholarly tools allows us to make new filters; these altmetrics reflect the broad, rapid impact of scholarship in this burgeoning ecosystem.
We call for more tools and research based on altmetrics. As the volume of academic literature explodes, scholars rely on filters to select the most relevant and significant sources from the rest. Peer-review has served scholarship well, but is beginning to show its age.
It is slow, encourages conventionality, and fails to hold reviewers accountable. Moreover, given that most papers are eventually published somewhere, peer-review fails to limit the volume of research.
Citation counting measures are useful, but not sufficient. Metrics like the h-index are even slower than peer-review: These metrics are narrow; they neglect impact outside the academy, and also ignore the context and reasons for citation.
Online reference managers Zotero and Mendeley each claim to store over 40 million articles making them substantially larger than PubMed ; as many as a third of scholars are on Twitterand a growing number tend scholarly blogs. These new forms reflect and transmit scholarly impact: That hallway conversation about a recent finding has moved to blogs and social networks—now, we can listen in.
The local genomics dataset has moved to an online repository—now, we can track it. This diverse group of activities forms a composite trace of impact far richer than any available before. We call the elements of this trace altmetrics. This matters because expressions of scholarship are becoming more diverse.
Articles are increasingly joined by: Widespread self-publishing via blogging, microblogging, and comments or annotations on existing work. This diversity can also help in measuring the aggregate impact of the research enterprise itself.
Altmetrics are fast, using public APIs to gather data in days or weeks. Altmetrics look beyond counting and emphasize semantic content like usernames, timestamps, and tags. How can altmetrics improve existing filters? With altmetrics, we can crowdsource peer-review.
In the future, greater participation and better systems for identifying expert contributors may allow peer review to be performed entirely from altmetrics. Unlike the JIF, altmetrics reflect the impact of the article itself, not its venue. Some have suggested altmetrics would be too easy to game; we argue the opposite.
The JIF is appallingly open to manipulation ; mature altmetrics systems could be more robust, leveraging the diversity of of altmetrics and statistical power of big data to algorithmically detect and correct for fraudulent activity.
This approach already works for online advertisers, social news sites, Wikipedia, and search engines. The speed of altmetrics presents the opportunity to create real-time recommendation and collaborative filtering systems: Faster, broader impact metrics could also play a role in funding and promotion decisions.
Road map for altmetrics Speculation regarding altmetrics Taraborelli, ; Neylon and Wu, ; Priem and Hemminger, is beginning to yield to empirical investigation and working tools. Priem and Costello and Groth and Gurney find citation on Twitter and blogs respectively.
ReaderMeter computes impact indicators from readership in reference management systems.How to Build a Paper Research Wiki May 11th, · 41 comments. Beyond Databases. Back in the early days of Study Hacks, I introduced the paper research database.
The idea was to build a database of every quote you might need to cite in your paper. These citations could be sorted by date or type, and be linked to their matching source.
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