Science of Innovation and Success Workshop

Inspired by the social and economic benefits of diversity, we analyze over 9 million papers and 6 million scientists to study the relationship between research impact and five classes of diversity: ethnicity, discipline, gender, affiliation, and academic age. Using randomized baseline models, we establish the presence of homophily in ethnicity, gender and affiliation. We then study the effect of diversity on scientific impact, as reflected in citations. Remarkably, of the classes considered, ethnic diversity had the strongest correlation with scientific impact. To further isolate the effects of ethnic diversity, we used randomized baseline models and again found a clear link between diversity and impact. To further support these findings, we use coarsened exact matching to compare the scientific impact of ethnically diverse papers and scientists with closely-matched control groups. Here, we find that ethnic diversity resulted in an impact gain of 10.63% for papers, and 47.67% for scientists.

The ever-increasing competitiveness in the academic publishing market incentivizes journal editors to pursue higher impact factors. This translates into journals becoming more selective, and, ultimately, into higher publication standards. However, the fixation on higher impact factors leads some journals to artificially boost impact factors through the coordinated effort of a "citation cartels'' of journals. "Citation cartel'' behavior has become increasingly common in recent years, with several instances being reported. Here, we propose an algorithm----named CIDRE---to detect anomalous groups of journals that exchange citations at excessively high rates when compared against a null model that accounts for scientific communities and journal size. CIDRE detects more than half of the journals suspended by Thomson Reuters due to anomalous citation behavior in the year of suspension or in advance. Furthermore, CIDRE detects many new anomalous groups, where the impact factors of the member journals are lifted substantially higher by the citations from other member journals. We describe a number of such examples in detail and discuss the implications of our findings with regard to the current academic climate.

In scientific articles, acknowledgments suggest not only gratitude but also the interaction among entities. In this study, we examine the academic world from the acknowledgment interactions. Employing the data from open-access journals (PLOS series & Scientific Reports), we established acknowledgment networks where the nodes are identified as authors and acknowledged people, while the edges correspond to mentions in acknowledgment statements. Employing motif analysis, we showed how the acknowledgment networks have developed and the reciprocal relationships tend to emerge. To understand the mechanisms by which reciprocal relationships tend to emerge, we analyzed the reciprocal sub-graphs of acknowledgement networks from two perspectives: citation networks and gender diversity. In the viewpoint of citation networks, we counted the number of citations of reciprocal and non-reciprocal authors. We found that reciprocal authors highly tend to cite other reciprocal authors than non-reciprocal authors. With regard to gender diversity, since it is known to have a strong impact on innovation, we computed the gender patterns of reciprocity in the acknowledgment network. As a result, we found that the reciprocal pairs including females tend to emerge more than male-male pairs of reciprocity in various fields despite the comparatively fewer females.

Patents are intellectual properties that often reflect innovative activities of companies and organizations. Many studies have investigated the citations among the patents, but only a few addressed the relations between the patent owners. These include the adversarial relations formed by patent opposition, a legal activity in which a company challenges the validity of a patent, and the collaborative relations implied by the co-ownership of patents by multiple companies. Characterizing the patent oppositions, collaborations, and the interplay between them is important for understanding how innovation happens. In this study, we construct a two-layer temporal network to model the patent oppositions and collaborations among the companies. We utilize temporal motifs to analyze the oppositions and collaborations from structural and temporal perspectives. Our analysis reveals the common patterns in patent oppositions, and shows that companies in different sizes have different capabilities and strategies on attacking other companies. It also suggests that two collaborating companies are more likely to oppose or be opposed by the same company in the future. We believe that our study discovers the business relations lying in the patent data, which will advance the research in business strategy and management.

Modern data archival, retrieval, and statistical analysis techniques are providing novel opportunities for understanding how complex social systems, past and present, function and evolve. This is a promising development particularly for studying ancient social systems where formidable challenge loom due to the scarcity of data and the impossibility of real-time social experimentation and observation. High-quality social data from the past are therefore indispensable, being the only gateway to understanding them. Here we present as a preeminent example the set of official government records produced by the Kingdom of Chosun during its reign between 1392 and 1905 CE of the Korean peninsula and its people. It consist of The Annals of Chosun Dynasty that details the kingdom's various affairs in a narrative format, and the Pangmok, personnel records of Chosun’s bureaucrats. Inspired by the nature and content of these data and the universal recognition of the importance of the people working in an organization for its proper functioning, in this paper we take a deep look at Chosun's vaunted bureaucracy and its role in the kingdom's operation and fate. Specifically, we find large-scale stable pattern of the career trajectories of the members of the bureaucracy that typically start with the highly-selective and open recruitment process. We shows that the knowledge of stable patterns in the workings of the highly complex social system allows us to detect true and unusual anomalies such as a corruption of the system sufficiently serious and irreversible that would ultimately lead to the demise of the kingdom itself.