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Altmetrics: Present and Future
Panel discussion at ASIST 2013
Stefanie Haustein

stefanie.haustein@umontreal.ca
@stefhaustein
Altmetrics: Present
•  Altmetrics are “representing very different things”
(Lin & Fenner, 2013)

•  unclear what exactly they measure:
scientific impact, social impact, buzz, or all of the above?
•  ad-hoc classifications need to be confirmed by
qualitative and more quantitative research
Altmetrics: Present
•  first studies show low to moderate positive
correlations with citations and disciplinary
differences in uptake of various social media tools
•  researchers and funders show interest in using
social media counts to reflect broader impact
•  tools aggregate and provide altmetrics
Altmetrics: Future
•  similar to development of SCI in the 1960s, social
media metrics have to be analyzed both from
quantitative and qualitative perspective
•  qualitative studies to analyze who, how and why
people use various social media platforms
•  large-scale quantitative studies to determine
differences and biases in terms of disciplines, topics,
document types, publications years, publication types
and sources, author age and affiliation, etc.
Ø  to find out what various social media metrics actually
mean and what they can be used for
Altmetrics: Challenges
•  complex to define and classify tools and motivations
•  scientific and non-scientific audiences cannot be
determined merely on the platform used
•  level of engagement differs not only between
platforms but also within, e.g.:
saving paper to Mendeley library vs. tweeting about it
saving vs. reading and retweeting link vs. discussing content

Ø  differentiation between audiences and
engagements needs to be subject of future research
Altmetrics: Challenges
scientist on
Twitter tweeting
scientific paper
in non-scholarly
manner:
•  Scientific impact?
•  Social impact?
•  Buzz?
Altmetrics: Challenges
Mistakes are meant for learning, not repeating!
•  e.g.: Impact Factor
•  short citation window and document type asymmetry
go back to convenience and cost-efficiency and adhoc decisions made in the 1960s and 1970s
•  50 years later, DORA tries to reverse the dominance
of impact factor use and misuse
Altmetrics: Challenges
Mistakes are meant for learning, not repeating!
•  counting mentions of DOIs without knowing what is
missed
•  comparing social media counts subject to biases that are
not (yet) fully understood:
•  publication year
•  certain topics
•  social media presence of publishing authors
and journals
•  …
Altmetrics: Future
•  before applying social media counts in information
retrieval and research evaluation, we need:
•  qualitative and more quantitative studies to
understand and define the meaning of various
social media counts
•  more transparency and reliability in data aggregation
Thank you for your attention!
Stefanie Haustein

stefanie.haustein@umontreal.ca
@stefhaustein

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SIGMET Panel at ASIST: Altmetrics - Present and Future

  • 1. Altmetrics: Present and Future Panel discussion at ASIST 2013 Stefanie Haustein stefanie.haustein@umontreal.ca @stefhaustein
  • 2. Altmetrics: Present •  Altmetrics are “representing very different things” (Lin & Fenner, 2013) •  unclear what exactly they measure: scientific impact, social impact, buzz, or all of the above? •  ad-hoc classifications need to be confirmed by qualitative and more quantitative research
  • 3. Altmetrics: Present •  first studies show low to moderate positive correlations with citations and disciplinary differences in uptake of various social media tools •  researchers and funders show interest in using social media counts to reflect broader impact •  tools aggregate and provide altmetrics
  • 4. Altmetrics: Future •  similar to development of SCI in the 1960s, social media metrics have to be analyzed both from quantitative and qualitative perspective •  qualitative studies to analyze who, how and why people use various social media platforms •  large-scale quantitative studies to determine differences and biases in terms of disciplines, topics, document types, publications years, publication types and sources, author age and affiliation, etc. Ø  to find out what various social media metrics actually mean and what they can be used for
  • 5. Altmetrics: Challenges •  complex to define and classify tools and motivations •  scientific and non-scientific audiences cannot be determined merely on the platform used •  level of engagement differs not only between platforms but also within, e.g.: saving paper to Mendeley library vs. tweeting about it saving vs. reading and retweeting link vs. discussing content Ø  differentiation between audiences and engagements needs to be subject of future research
  • 6. Altmetrics: Challenges scientist on Twitter tweeting scientific paper in non-scholarly manner: •  Scientific impact? •  Social impact? •  Buzz?
  • 7. Altmetrics: Challenges Mistakes are meant for learning, not repeating! •  e.g.: Impact Factor •  short citation window and document type asymmetry go back to convenience and cost-efficiency and adhoc decisions made in the 1960s and 1970s •  50 years later, DORA tries to reverse the dominance of impact factor use and misuse
  • 8. Altmetrics: Challenges Mistakes are meant for learning, not repeating! •  counting mentions of DOIs without knowing what is missed •  comparing social media counts subject to biases that are not (yet) fully understood: •  publication year •  certain topics •  social media presence of publishing authors and journals •  …
  • 9. Altmetrics: Future •  before applying social media counts in information retrieval and research evaluation, we need: •  qualitative and more quantitative studies to understand and define the meaning of various social media counts •  more transparency and reliability in data aggregation
  • 10. Thank you for your attention! Stefanie Haustein stefanie.haustein@umontreal.ca @stefhaustein