=Paper=
{{Paper
|id=Vol-3745/paper22
|storemode=property
|title=Understanding Partnership in Scientific Collaborations: A Preliminary Study from the Paper-level Perspective
|pdfUrl=https://ceur-ws.org/Vol-3745/paper22.pdf
|volume=Vol-3745
|authors=Chao Lu,Mengting Li,Chenyu Zhou
|dblpUrl=https://dblp.org/rec/conf/eeke/LuLZ24
}}
==Understanding Partnership in Scientific Collaborations: A Preliminary Study from the Paper-level Perspective==
https://ceur-ws.org/Vol-3745/paper22.pdf
Understanding Partnership in Scientific Collaborations: A
Preliminary Study from the Paper-level Perspective
Chao Lu1,* , Mengting Li1, and Chenyu Zhou1
1 Hohai University, 8 West Focheng Road, Nanjing, China, 211000
Abstract
Scientific collaboration is more and more common in scientific knowledge production. It has been
widely investigated through quantitative and qualitative ways recently. However, most quantita-
tive methods purely based on co-author information usually fail to dig deeper into the internal
interaction between collaborators as contributors, which fails to observe internal interactions
between collaborators. In this study, we investigated how collaborators in teams work together
to perform their research by understanding how two collaborators work together as partners
which the traditional collaborative network usually overlooked naturally. By collecting author
information from Scopus and author contribution statements from PLoS, we take the biology sub-
ject as an example and have examined more than 120,000 research articles and found that divi-
sion of labor is quite common in scientific collaboration; that partnership as a form of division of
labor is widely observed in our dataset; and that the diversity in contributing tasks between part-
ners is generally mild. This study will shed light on understanding the mechanism in scientific
collaboration via division of labor that co-authorship studies widely overlook. It helps us create
research teams with higher levels of engagement and communication.
Keywords
Scientific Collaboration, Author Contribution Statement, Natural Language Processing.
1 Introduction scientific collaborations, such as division of labor and
team role differentiation[3, 8]. Recently, co-contribu-
Scientific collaboration is more and more common in torship[1] as a type of partnership in scientific collab-
scientific knowledge production. It has been widely in- orations drew our research interest. Given that re-
vestigated through quantitative and qualitative ways search teams consist of not only individual building
[1, 2] recently. However, there is still more to be inves- blocks but living collaborators, we want to investigate
tigated especially when more data are disclosed on in- how this partnership exists in scientific collaboration
teractions between collaborators in each team, i.e., au- and how this close relationship in scientific collabora-
thor contribution statement [1, 3β5] while most quan- tion influences scientific performance in the future.
titative methods based purely on co-author infor- Thus, in this preliminary study, we collected au-
mation usually fail to dig deeper on the internal inter- thor information from Scopus and author contribution
action between collaborators as contributors[6, 7]. statements from PLoS, we took the biology subject as
Contributorship other than authorship especially pay an example and examined more than 120,000 re-
attention to the actual contributions made by each sci- search articles to examine partnership in scientific col-
entific collaborator. Studies suggest that contributor- laboration from three perspectives: ratio, strength,
ship provides us with new perspectives to understand and diversity. This study and the study to come will
Joint Workshop of the 5th Extraction and Evaluation of
Knowledge Entities from Scientific Documents and the 4th AI +
Informetrics (EEKE-AII2024), April 23~24, 2024, Changchun,
China and Online
*Corresponding author.EMAIL: luchao91@hhu..edu.cn
Β©οΈ 2024 Copyright for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
141
help shed light on understanding the mechanism in detailed definition for each role. For each piece of au-
scientific collaboration via division of labor that stud- thor-defined tasks, we might assign more than one
ies via co-authorship widely overlooked. It might help standard contribution role(see Table 1). For those
us create research teams with higher levels of engage- contributions that cannot be standardized using the
ment and communication. taxonomy, we label them as "Other". The rest, around
0.5 percent, of author-defined tasks, we automatically
2 Data and Methods label them as "UNKNOWN" for we did not mannually
label them. Considering the amount of this part of data
2.1 Data is quite small, the potential side effect of them on the
To examine the phenomenon of partnership in scien- whole study could be ignored. With the multi-labeling
tific collaborations, we collected 126,894 articles in tactic, we can expand our data, resulting in 5,154 more
the Biology domain from PLoS (Public Library of Sci- author-task pairs.
ence) from 2006 to 2020 with their author contribu-
tion statements. The yearly distribution of the articles Table 1. Annotation sample for author-defined contri-
we collected is shown in Fig.1. The plot suggests that bution standardization using CrediT
the distribution generally followed an increasing Author-defined Task Contribution Role
trend except in 2015 and 2016, we double-checked the
Participated in critical dis-
data and found that the PLoS journals did not label
cussion of the draft's ini- Writing β review &
subject information for their papers in these two years,
tial findings and revision editing
so we failed to include the biology papers in these
of the manuscript
years from the whole collections.
Statistically analyzed the
Formal analysis
data
Contributed to the design
Conceptualization,
and development of the
Methodology
project
Then we construct paper-level co-authorship net-
works(CAN for short) and co-contributorship net-
works (CCN for short) as proposed in [9] for each pa-
per.
We are to analyze the partnership from three per-
spectives: partnership ratio; partnership strength, and
partnership diversity. The formulas for the three
measurements are as follows:
ππ’ππππ ππ πΆπΆπ πππππ
ππ
= (1)
πππ₯πππ’π ππ’ππππ ππ πππππ
π‘ππ‘ππ π€πππβπ‘ ππ πΆπΆπ πππππ
Fig. 1. Yearly distribution of biology publications ππ = (2)
π‘ππ‘ππ π€πππβπ‘ ππ πΆπ΄π πππππ
from PLoS journals collected in this study
ππ’ππππ ππ π’ππππ’π ππππ‘ππππ’π‘ππ πππππ
ππ· = (3)
ππ’ππππ ππ πππ ππππ‘ππππ’π‘ππ πππππ
2.2 Methods
Following previous studies[1, 9], we process the au- 3 Preliminary Findings
thor contribution statements and link the author
Fig. 2 plots the partnership ratio in our dataset. It sug-
names to their tasks in each paper using Python scripts.
gests that generally in each team exists some level of
Using Scopus API, we can disambiguate author names
partnership, which results in some degree of division
for this study. In total, we have collected 574,979
of labor in scientific collaboration. Specifically, more
pieces of disambiguated author information and
than 60,000 teams all collaborators are engaged in at
2,831,375 author-task pairs.
least one collaborative task.
Given that PLoS did not adopt the CRediT1 taxonomy
Fig.3 shows the partnership strength distribution,
until 2016, we manually labeled around 99.5% of au-
which indicates how closely collaborators in a team
thor-defined tasks according to the taxonomy with
1 http://credi.niso.org/
142
are connected when doing research via the number of usually perform 2.35 different contributor roles, on
tasks two collaborators collaborated in a study. The average. Given that there are 14 different contributor
figure demonstrates that on average the total edge roles theoretically that two partners can work on, the
weights of CCNs are 2.09, which means on average, diversity of the partnership remains quite mild.
two collaborators collaborate two divided tasks in
each study. It also suggests that some collaborators in
teams might be more involved in collaboration than
others, indicating the existance of the partnership in
scientific collaboration. Given that the average weight
of CCNs is as double as those measured in CANs. And
CCNs are naturally sparser than CANs as suggested
by[9], the figure implies that partnership plays a role
in scientific collaboration.
Fig. 4 The distribution of partnership diversity in our
study
4 Conclusion and Future Work
In this preliminary study, we investigated how collab-
orators in teams work together to perform their re-
search by understanding how two collaborators work
together as partners which the traditional collabora-
Fig. 2. The distribution of partnership ratio in our tive network usually overlooked naturally. By collect-
study ing author information from Scopus and author contri-
bution statements from PLoS, we take the biology sub-
ject as an example and have examined more than
120,000 research articles and found that division of la-
bor is quite common in scientific collaboration; that
partnership as a form of division of labor is widely ob-
served in our dataset; and that the diversity in contrib-
uting tasks between partners is generally mild. This
study will shed light on understanding the mechanism
in scientific collaboration via division of labor that co-
authorship studies widely overlook. It helps us create
research teams with higher levels of engagement and
communication.
Acknowledgements
This article is an outcome of the youth project "Study
of Scientific Collaboratorsβ Scientific Effectiveness
Fig. 3. The distribution of partnership strength in our
from The Perspective of Division of Labor" (ID:
study
72004054) supported by the National Natural Science
Foundation of China and the project "The Causal Effect
Fig.4 shows the partnership diversity in scientific
of Team Diversity on Team Performance" supported
collaboration, which generally reflects how diverse it
by the Fundamental Research Funds for the Central
can be when two collaborators work as partners on
Universities (ID: B220201058).
the same tasks. It shows that generally partners
143
References [5] Allen L, Scott J, Brand A, et al (2014) Publishing:
Credit where credit is due. Nature News 508:312.
[1] Lu C, Zhang C, Xiao C, Ding Y (2022) Contributor- [6] Devine EB, Beney J, Bero LA (2005) Equity, ac-
ship in Scientific Collaborations: The Perspective countability, transparency: Implementation of
of Contribution-based Byline Orders. Infor- the contributorship concept in a multi-site study.
mation Processing & Management 59:. Am J Pharm Educ 69:61.
[2] GarcΓa-SΓ‘nchez P, DΓaz-DΓaz NL, De SaΓ‘-PΓ©rez P https://doi.org/10/dqjngb
(2019) Social capital and knowledge sharing in [7] Rennie D, Yank V, Emanuel L (1997) When Au-
academic research teams. International Review thorship Fails: A Proposal to Make Contributors
of Administrative Sciences 85:191β207. Accountable. JAMA 278:579β585.
[3] Haeussler C, Sauermann H (2020) Division of la- [8] Xu F, Wu L, Evans J (2022) Flat teams drive sci-
bor in collaborative knowledge production: The entific innovation. Proc Natl Acad Sci USA
role of team size and interdisciplinarity. Re- 119:e2200927119.
search Policy 49:103987. [9] Lu C, Zhang Y, Ahn Y-Y, et al (2020) Co-contribu-
[4] Larivière V, Desrochers N, Macaluso B, et al torship Network and Division of Labor in Indi-
(2016) Contributorship and division of labor in vidual Scientific Collaborations. Journal of the
knowledge production. Soc Stud Sci 46:417β435. Association for Information Science and Tech-
nology 71:1162β1178.
144