A presentation on 'Publishing in Academic Journals – Tips to help you succeed' presented at the 2015 University of South Africa (Unisa) Authors Workshop organised by Unisa’s College of Graduate Studies and the Unisa Library
9. •What is the readership and usage? The top cited or downloaded papers may be on the
journal website
• What is the journal’s policy on repositories?
• Is it in the Thomson Reuters Citation Index or SCOPUS? Does the journal have an Impact
Factor? Is that an important consideration for your subject area?
• If your work is publicly funded, is your paper required to be ‘Open Access’?
• Should you send an abstract of your paper to the Editor to assess its quality or ‘fit’?
• Look at previous papers to get a feel for what is accepted
• Take note of maximum extent of the submission
(see the Instructions for Authors/Notes for Contributors)
• Follow any submission guidelines; how should you submit your paper?
-Check if submission should be made via an online editorial office, many journals use
ScholarOne Manuscripts or Editorial Manager
• Quote from and reference previous papers published in the journal if relevant. It
demonstrates you have read the journal and contextualises your paper within their
historic contributions to the field.
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14. •Take care when choosing your title; most readers will access your paper online by
way of a search engine or see it via a content alerting service
• Remember, the title and abstract are the most visible parts of your article and
therefore require care and attention
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20. • Article level metrics also created a drive towards author metrics such as
the H-Index.
• The h-index is easy to compute
• E.g. one paper has at least one citation, two papers that each
have at least two citations
• The h-index can be applied to any set of papers, for example Google
Scholar has used as it the basis for their journal level metrics.
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22. Taylor & Francis are pleased to be continuing our partnership with Kudos - a
new service that helps researchers and their institutions/funders to measure,
monitor and maximize the visibility and impact of their published articles.
The Kudos initiative fits very well with T&F’s wider support for authors and
their institutions and so we are excited to have been involved from the early
stages of development.
Kudos builds on three core principles:
1. that readers are increasingly struggling to filter the growing quantity
of published research;
2. that information which supports filtering – such as lay summaries
and impact statements – often exists but is not made public;
3. and that authors are best placed to increase awareness and impact
of their work, but don’t always know how to do this. Kudos provides
a platform for assembling or creating information to help filtering, for
sharing information to drive discovery, and for measuring and
monitoring the effect of both activities.
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23. As part of the pre-pilot phase (September -December 2013), Kudos surveyed
almost 4,000 authors and the results were compelling:
• 84% thought that more could be done to raise the visibility, impact
and usage of their work
• 80% felt that it was their personal responsibility to increase the levels
of impact, usage and visibility of their work
• 75% of respondents said they would be quite likely, likely or very
likely to use Kudos themselves
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24. T&F Online provides article level metrics such as Article Views and Citation
Counts
• Article views (the combined .pdf downloads and HTML full-text views of
an article on Taylor & Francis Online; this figure updates every 24-hours)
• Citation counts
•The citation count and list of citations is currently only pulled from
CrossRef and the participating CrossRef members, but we’re
working on expanding the sources from which we pull citation data
to include Scopus and the Web of Science, so that the citation
counts and list of citations are more comprehensive;
•we should see the results of that work on Taylor & Francis Online
early next year
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25. Altmetrics – new metrics proposed as an alternative to Journal Impact Factor and personal citation indices like the
H-index.
Term “altmetrics” is a generalization of ‘article level metrics’
Altmetrics are often perceived as just a social media measurement tool.
BUT we do need a tool to effectively answer the question: “what I do I need to read?”
Altmetrics act as a post-publication Filter of research
• More than 1.7 Million articles that were published in 2012 are listed on Scopus
• No one can read everything, even within small fields
• Speed
• Altmetrics are very fast
• Social media attention for articles is normally concentrated around the 1st few weeks after
publication.
•There are many types of research and research outputs that serve different roles.
•The metrics we use need to reflect the differing types of output.
•With Altmetrics we also see many different trends emerging per subject area
•Altmetrics Manifesto:
“Altmetrics expand our view of what impact looks like, but also of what’s making the impact”
“This matters because expressions of scholarship are becoming more diverse”
• Different altmetric tools:
• Altmetric
• Impact Story
• Plum Analytic
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26. Example of article level information on Altmetric.com
The scores are calculated using a proprietary algorithm which is based on a
combination of both the amount and type of mentions, and news articles are
counted differently to tweets.
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27. Example of detail at article level on altmetric.com
…amusingly about the many kinds of mental illness displayed by characters in
AA Milne’s Winnie the Pooh
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28. This is an Impact Story report for one authors articles.
Different articles have been picked up in different ways, the highly cited and
highly discussed articles are different.
• Question: Do altmetrics only highlight fashionable articles not the
best in terms of scholarly work?
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29. • Article level metrics also created a drive towards author metrics such as
the H-Index.
• The h-index is easy to compute
• E.g. one paper has at least one citation, two papers that each
have at least two citations
• The h-index can be applied to any set of papers, for example Google
Scholar has used as it the basis for their journal level metrics.
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32. • Article level metrics also created a drive towards author metrics such as
the H-Index.
• The h-index is easy to compute
• E.g. one paper has at least one citation, two papers that each
have at least two citations
• The h-index can be applied to any set of papers, for example Google
Scholar has used as it the basis for their journal level metrics.
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