On the Science of Science

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The amount of published scientific research has been doubling almost every 15 years (Fortunato et al.). This is paired with an increasing amount of data and tools of analysis that can be used to understand the dynamics of scientific research. Contandriopoulos et al., Qi et al., Fortunato et al., and Li et al.’s findings are used to better understand these dynamics, how they lead to impactful research output, and how the roles individual researchers play in the network of science affects that impactful output.

Scientific research can be described as “a complex, self-organizing, and constantly evolving multi-scale network” (Fortunato et al., 2018). This “multi-scale network” of scientific research has many elements of connectivity– fields, institutions, and works cited by a given publication are all a part of the network and can be analyzed to understand the patterns they affect. All of the researchers above used this network structure as a tool for analysis, focusing especially on the importance of collaborators within this network on a researcher’s career productivity and impact.

Contandriopoulos et al. examined how the diversity of a researcher’s collaboration network may predict the researcher’s career impact. Researchers who play more of a bridging role between different groups and communities within the research network are likely to produce more influential work (Contandriopoulos et al., 2016). Researchers who prioritize their research productivity should diversify their collaborators and communities to improve their structural position and make novel connections. While a researcher’s choice of collaborators will not be made solely based on the potential for that collaborator to be a novel connection, the impact of that collaboration on the researcher’s structural position should be considered if the researcher hopes to maximize their productive output over their careers. At the same time, we have seen that there are incentives in place that keep researchers choosing more conservative research topics and collaborations (Fortunato et al., 2018). A researcher’s awareness of the importance of their structural position may help them break free of their community silo that could be limiting their research impact.

In addition to considering a researcher’s position within the network of science, it is important to understand how key collaborators can play a role in boosting a researcher’s career. When this network effect is examined, it is clear to see that the impact of collaborating with top scientists is very effective at increasing the future impact of an early researcher’s career, and that effect increases for researchers the earlier they are in their career (Qi et al., 2017; Li et al., 2019). While there are multiple ways to define top scientists, the general trend holds that having top collaborators on a researcher’s early publications significantly increases the likelihood of that researcher becoming a top scientist. Li et al. found that the positive effect of this top collaborator is most significant when the early-career researcher has one or fewer of the following: is associated with a top 10% institution, is in the top 10% of publications for their career phase, is in the top 10% of citations received for their career phase. If a researcher is otherwise productive or has access to a prestigious institution, the impacts of that top collaborator are less significant. Inversely, this shows that it is especially important for researchers who have fewer institutional advantages or are less familiar with how the scientific research community operates to find top collaborators to help boost their careers.

The fact that the impact of these top collaborators is greater the earlier they occur in a researcher’s career (Qi et al., 2017; Li et al., 2019) means that when students are least knowledgeable about the world of scientific research is when their decisions may be of highest impact for their future careers as scientists. It should be noted that while the impact of collaborating with top scientists is significant, Qi et al. found that this relationship is not linear. There are diminishing returns to collaborating with an increasingly exceptional scientists, and this is an indication that an early researcher does not need to be extraordinarily selective and that likely any scientist in the top 10% of their field would be a valuable boost to an early researcher’s career.

These findings suggest that there is likely significant untapped potential in the scientific research community (Li et al., 2019), and a more thorough understanding of these dynamics may lead to institutional policies that improve the output of impactful scientific research over coming years. It is especially important for young and early researchers to understand the dynamics of the scientific research network and take the time to consider how the decisions they make regarding their collaborators and the communities they engage with may affect their structural position in the scientific research community and impact their future career impact.

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science of science {{renderer :wordcount_}}

The amount of published scientific research has been doubling almost every 15 years (Fortunato et al). This is paired with an increasing amount of data and tools of analysis that can be used to understand how scientific research evolves. Contandriopoulos et al, Qi et al, Fortunato et al, and Li et al’s findings were used to better understand the dynamics of how scientific research creates impactful output, and how the roles individual researchers play in the network of science effects that impactful output.

Scientific research can be described as “a complex, self-organizing, and constantly evolving multi-scale network” (Fortunato et al, 2018). All of the researchers above used this network structure as a tool for analysis, focusing especially on the network of collaborators and citations.

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All of the mentioned researchers studied the importance of collaborators on scientific impact and success

The importance of collaborators on a researcher’s success was a key focus of all of the researchers in this review. The “multiscale network” (Fortunato et al, 2018) of scientific research has many elements of connectivity– fields, institutions, and works cited by a given publication are all a part of the network and can be analyzed to understand the patterns they affect.

Contandriopoulos et al examined how the diversity of a researcher’s collaboration network may predict the researcher’s success. Researchers who play more of a bridging role between different groups and communities within the research network are likely to produce more influential work (Contandriopoulos et al, 2016). It appears to be important for researchers who prioritize their research productivity to diversify their collaborators and communities to improve their structural position and make novel connections. The decision of who a researcher decides to collaborate with will not be made solely based on the potential for that collaborator to be a novel connection, but the impact on the researcher’s structural position should be considered if the researcher hopes to maximize their productive output over their careers. At the same time, we have seen that there are incentives in place that keep researchers choosing more conservative research topics and collaborations (Fortunato et al, 2018). A researcher’s awareness of the impact of their structural position may help them break free of their community silo that could be limiting their research impact.

stronger early in career

In addition to the importance of a researcher’s position within the network of research, it is important to understand how key collaborators can play a role in boosting a researcher’s career. When this is network effect is examined, it is clear to see that the impact of collaborating with top scientists is very significant and greater for researchers the earlier they are in their career (Qi et al, 2017; Li et al, 2019). While there are multiple ways to define top scientists, the general trend holds that having top collaborators on a researcher’s early publications significantly increases the likelihood of that researcher becoming a top scientist. Li et al found that the positive effect of this top collaborator is most significant when the early-career researcher has one or fewer of the following: is associated with a top 10% prestigious institution, is in the top 10% of publications for their phase of career, is in the top 10% of citations received for their phase of career. If a researcher is otherwise productive or has access to a prestigious institution, the impacts of that top collaborator are less significant. Inversely, this shows that it is especially important for researchers who have fewer institutional advantages or have less of an understanding of how the scientific research community operates to find top collaborators to help boost their career outlooks.

The fact that the impact of these top collaborators is more significant the earlier they occur in a researcher’s career (Qi et al, 2017; Li et al, 2019) means that when students are least knowledgeable about the world of scientific research is when their decisions may be of highest impact for their future careers as scientists. It should be noted that while the impact of collaborating with top scientists is significant, Qi et al found that this relationship is not linear. There is a diminishing return to collaborating with an increasingly superlative scientist, and this is an indication that an early researcher does not need to be extraordinarily selective, and that almost any scientist in the top 10% of their field would be a valuable boost to an early researcher’s career.

The there is likely a significant amount of untapped potential in the scientific research community (Li et al, 2019), and a more thorough understanding of these dynamics may be able to lead to institutional policies that improve the output of impactful of scientific research over coming years. At the very least, it is especially important for young and early researchers to understand the value of the Science of Science and take the time to understand how the structural decisions they make align with their career goals.

improvements for future

findings have limitations

citations as data

better ways to measure

science is risk averse (Fortunato)

ideas

papers

(Contandriopoulos, 2016)

(Qi et al, 2017)

(Fortunato et al, 2018)

(Li et al, 2019)

what is science of science (100) {{renderer :wordcount_}}

we’ve seen from research

science as network

Because the rigor of scientific research is based on building off of prior work and connecting to other relevant work, Science can be seen as a complex network (Fortunato et al, 2018).

As we better understand the dynamics of this network, and

growth in data allows us to better understand how the scientific research process works

growth in papers

The amount of published scientific research has been doubling almost every 15 years (Fortunato et al). This is paired with an increasing amount of data and tools of analysis that can be used to understand how scientific research evolves and what similarities exist between varieties of

We see multiple trends as

goal is to improve these processes

Fortunato et al

how we analyze researcher success (200) {{renderer :wordcount_}}

each of these researchers uses certain metrics to determine successful research, or “top” or “high impact” researchers

examples of these metrics, citations

flaw with using citations Li et al

how these metrics

how to predict researcher success (300) {{renderer :wordcount_}}

the goal of all of these researchers is to better understand how impactful research

can we predict researcher success

it seems that we can, it seems that the network effects are strong

Very relevant to the idea of scientific research as a network put forward by Fortunato et al, Li et al use a network of coauthorship to try to understand how strongly who researchers partner with early in their careers plays a role in the strength of their future careers.

Important parts of this complex network are the human dynamics. Li et al analyze the network relationships of coauthorship with top researchers on the outcomes for a researcher. Contrandriopoulos et al choose to expand the analyzed network effects beyond just coauthorship more fully to analyzing the communities researchers belong to and the structural positions they hold within these networks.

Qi et al find that collaborators have a significant impact on the outcomes of early career researchers’ future citations. This aligns with the findings of Li et al. Qi et al also show that this relationship is not linear, and that “more outstanding scientists” produces diminishing benefit to the early researcher as a collaborator.

impact of positive collaborators is larger early in career

Li et al

Qi et al also see a similar outcome where the importance of finding high impact collaborators is greater earlier in a researcher’s career.

institutional strength and productivity also are strong

Li et al

this is a problem because it means there is untapped potential

Li et al

better ways we can measure impact (200) {{renderer :wordcount_}}

there are a lot of shortcomings to our existing data

generally, we don’t want to only use citations to measure success

The quality of collaboration is not well identified in existing research, and it might be useful to differentiate between direct supervisors and standard scientific research collaborations (Qi et al, 2017).

The difference from field to field, and from research areas within fields.

Qi et al’s findings are derived from data from the field of physics, while Li et al mention that they are confidence in their findings, but that deeper research could be done.

other shortcomings

impacts on research

scientists are risk averse (Fortunato et al)

LATER bring in citations