Nature’s reach: narrow work has broad impact

Gates, Alexander J.; Ke, Qing; Varol, Onur; Barabási, Albert László

doi:10.1038/d41586-019-03308-7

Cited by 73 publications

(53 citation statements)

References 12 publications

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“…However, these factors are found to be relevant for monodisciplinary research fields such as economics, mathematics, physics, biology (Newman, 2004). Increased multidisciplinary research requires the involvement of researchers from different disciplinary backgrounds (Gates et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

International collaboration in higher education research: A gravity model approach

Avdeev

2021

Scientometrics

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Geographical distance has become less relevant in co-authorship for monodisciplinary research fields such as economics, mathematics, physics. Multidisciplinary fields are influenced by the norms and traditions of other fields. Higher education is a multidisciplinary field of research in which multiple communities operate under different norms and paradigms. We study collaboration patterns in higher education research across different world regions using the Scopus database with the application of the gravity model. Our results show that international collaboration has intensified and increased rapidly in the last two decades. We confirm that the intensity of collaboration is dependent on geographical distance and linguistic commonality. The importance of geographical proximity differs significantly between various world regions. EU scholars appear to give preference to linguistic proximate partners over geographical neighbors. Despite the fact that English is the lingua franca in science, language is not a significant factor for the formation of collaboration for North American researchers. This study contributes to the current discussion on the importance of international collaboration in science, paying special attention to the growing public interest in multidisciplinary research.

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Section: Introductionmentioning

confidence: 99%

International collaboration in higher education research: A gravity model approach

Avdeev

2021

Scientometrics

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“…Paralleling with these aggregational efforts, the current study, likewise, adopts multiple analysis methods (GLM contrast, parametric modulation, PPI, and mediation analyses), providing results of different angles into these TPJ-IPL complex, along with its interconnected networks. In a similar spirit, our study, although narrow 80 , helps address this ubiquitous social phenomenon (interacting college couples), with two-people fMRI experiments, and illuminate inner interactions in IPL-TPJ, on top of their alluded functions, including (but not limited to): attention, memory, language, with social behaviors. About the limitation of the current study, we like to list these two aspects: (a) this is a natural study, where couples agreed up to 70% of the together-trials, meaning that only 30% were left for incongruence-resolving.…”

Section: Discussionmentioning

confidence: 86%

A brain network that supports consensus-seeking and conflict-resolving of college couples’ shopping interaction

Chen

et al. 2020

Sci Rep

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One of the typical campus scenes is the social interaction between college couples, and the lesson couples must keep learning is to adapt to each other. This fMRI study investigated the shopping interactions of 30 college couples, one lying inside and the other outside the scanner, beholding the same item from two connected PCs, making preference ratings and subsequent buy/not-buy decisions. The behavioral results showed the clear modulation of significant others’ preferences onto one’s own decisions, and the contrast of the “shop-together vs. shop-alone”, and the “congruent (both liked or disliked the item, 68%) vs. incongruent (one liked but the other disliked, and vice versa)” together trials, both revealed bilateral temporal parietal junction (TPJ) among other reward-related regions, likely reflecting mentalizing during preference harmony. Moreover, when contrasting “own-high/other-low vs. own-low/other-high” incongruent trials, left anterior inferior parietal lobule (l-aIPL) was parametrically mapped, and the “yield (e.g., own-high/not-buy) vs. insist (e.g., own-low/not-buy)” modulation further revealed left lateral-IPL (l-lIPL), together with left TPJ forming a local social decision network that was further constrained by the mediation analysis among left TPJ–lIPL–aIPL. In sum, these results exemplify, via the two-person fMRI, the neural substrate of shopping interactions between couples.

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“…This implies that the flow of knowledge is severely restricted among disciplines or even among different areas within the same discipline. In recent decades, different approaches (Börner et al, 2003;Henry and McInnes 2017;Small et al, 2014) have been proposed to overcome this gap by means of, for example, cooccurrence or semantic models (Cory, 1997;Gabrilovich and Markovitch, 2007;Ibrahim et al, 2017) or bibliometric-based systems (Gates et al, 2019) that use citation information to find related items. However, notwithstanding the significant advances in these methods, mainly through the network of citing articles, interdisciplinary research lacks efficient tools for establishing quantitative connections among different disciplines (such as science, art and literature).…”

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confidence: 99%

Complex networks reveal emergent interdisciplinary knowledge in Wikipedia

Schwartz

2021

Humanit Soc Sci Commun

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In the last 2 decades, a great amount of work has been done on data mining and knowledge discovery using complex networks. These works have provided insightful information about the structure and evolution of scientific activity, as well as important biomedical discoveries. However, interdisciplinary knowledge discovery, including disciplines other than science, is more complicated to implement because most of the available knowledge is not indexed. Here, a new method is presented for mining Wikipedia to unveil implicit interdisciplinary knowledge to map and understand how different disciplines (art, science, literature) are related to and interact with each other. Furthermore, the formalism of complex networks allows us to characterise both individual and collective behaviour of the different elements (people, ideas, works) within each discipline and among them. The results obtained agree with well-established interdisciplinary knowledge and show the ability of this method to boost quantitative studies. Note that relevant elements in different disciplines that rarely directly refer to each other may nonetheless have many implicit connections that impart them and their relationship with new meaning. Owing to the large number of available works and to the absence of cross-references among different disciplines, tracking these connections can be challenging. This approach aims to bridge this gap between the large amount of reported knowledge and the limited human capacity to find subtle connections and make sense of them.

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Nature’s reach: narrow work has broad impact

Cited by 73 publications

References 12 publications

International collaboration in higher education research: A gravity model approach

International collaboration in higher education research: A gravity model approach

A brain network that supports consensus-seeking and conflict-resolving of college couples’ shopping interaction

Complex networks reveal emergent interdisciplinary knowledge in Wikipedia

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