Contexts of diffusion: Adoption of research synthesis in Social Work and Women's Studies

Texts reveal the subjects of interest in research fields, and the values, beliefs, and practices of researchers. In this study, texts are examined through bibliometric mapping and topic modeling to provide a birds eye view of the social dynamics associated with the diffusion of research synthesis methods in the contexts of Social Work and Women's Studies. Research synthesis texts are especially revealing because the methods, which include meta-analysis and systematic review, are reliant on the availability of past research and data, sometimes idealized as objective, egalitarian approaches to research evaluation, fundamentally tied to past research practices, and performed with the goal informing future research and practice. This study highlights the co-influence of past and subsequent research within research fields; illustrates dynamics of the diffusion process; and provides insight into the cultural contexts of research in Social Work and Women's Studies. This study suggests the potential to further develop bibliometric mapping and topic modeling techniques to inform research problem selection and resource allocation.Comment: To appear in proceedings of the 2014 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP2014

A quantitative and qualitative open citation analysis of retracted articles in the humanities

In this article, we show and discuss the results of a quantitative and qualitative analysis of open citations to retracted publications in the humanities domain. Our study was conducted by selecting retracted papers in the humanities domain and marking their main characteristics (e.g., retraction reason). Then, we gathered the citing entities and annotated their basic metadata (e.g., title, venue, subject, etc.) and the characteristics of their in-text citations (e.g., intent, sentiment, etc.). Using these data, we performed a quantitative and qualitative study of retractions in the humanities, presenting descriptive statistics and a topic modeling analysis of the citing entities' abstracts and the in-text citation contexts. As part of our main findings, we noticed that there was no drop in the overall number of citations after the year of retraction, with few entities which have either mentioned the retraction or expressed a negative sentiment toward the cited publication. In addition, on several occasions, we noticed a higher concern/awareness when it was about citing a retracted publication, by the citing entities belonging to the health sciences domain, if compared to the humanities and the social science domains. Philosophy, arts, and history are the humanities areas that showed the higher concern toward the retraction

A qualitative and quantitative analysis of open citations to retracted articles: the Wakefield 1998 et al.'s case

In this article, we show the results of a quantitative and qualitative analysis of open citations on a popular and highly cited retracted paper: “Ileal-lymphoid-nodular hyperplasia, non-specific colitis and pervasive developmental disorder in children” by Wakefield et al., published in 1998. The main purpose of our study is to understand the behavior of the publications citing one retracted article and the characteristics of the citations the retracted article accumulated over time. Our analysis is based on a methodology which illustrates how we gathered the data, extracted the topics of the citing articles and visualized the results. The data and services used are all open and free to foster the reproducibility of the analysis. The outcomes concerned the analysis of the entities citing Wakefield et al.’s article and their related in-text citations. We observed a constant increasing number of citations in the last 20 years, accompanied with a constant increment in the percentage of those acknowledging its retraction. Citing articles have started either discussing or dealing with the retraction of Wakefield et al.’s article even before its full retraction happened in 2010. Articles in the social sciences domain citing the Wakefield et al.’s one were among those that have mostly discussed its retraction. In addition, when observing the in-text citations, we noticed that a large number of the citations received by Wakefield et al.’s article has focused on general discussions without recalling strictly medical details, especially after the full retraction. Medical studies did not hesitate in acknowledging the retraction of the Wakefield et al.’s article and often provided strong negative statements on it

How research programs come apart: the example of supersymmetry and the disunity of physics

According to Peter Galison, the coordination of different ``subcultures'' within a scientific field happens through local exchanges within ``trading zones''. In his view, the workability of such trading zones is not guaranteed, and science is not necessarily driven towards further integration. In this paper, we develop and apply quantitative methods (using semantic, authorship, and citation data from scientific literature), inspired by Galison's framework, to the case of the disunity of high-energy physics. We give prominence to supersymmetry, a concept that has given rise to several major but distinct research programs in the field, such as the formulation of a consistent theory of quantum gravity or the search for new particles. We show that ``theory'' and `phenomenology'' in high-energy physics should be regarded as distinct theoretical subcultures, between which supersymmetry has helped sustain scientific ``trades''. However, as we demonstrate using a topic model, the phenomenological component of supersymmetry research has lost traction and the ability of supersymmetry to tie these subcultures together is now compromised. Our work supports that even fields with an initially strong sentiment of unity may eventually generate diverging research programs and demonstrates the fruitfulness of the notion of trading zones for informing quantitative approaches to scientific pluralism

Identification of Emerging Scientific Topics in Bibliometric Databases

Bibliometrie, Maschinelles Lernen, LDA, Clustering, Neue Themen Abstract = Frühzeitiges Erkennen von aufkommenden Themengebieten in der Wissenschaft unterstützt sowohl Entscheidungen auf individueller als auch öffentlicher Ebene. Viele bestehende Verfahren beschränken sich auf eine retrospektive (Zitations-)Analyse der Publikationsdaten. Das Ziel der vorliegenden Arbeit war deshalb die Entwicklung eines Verfahrens, das zeitnah und neutral sogenannte "emerging topic candidates" aus einem Set von wissenschaftlichen Publikationen auswählt

Identification of Emerging Scientific Topics in Bibliometric Databases

Bibliometrie, Maschinelles Lernen, LDA, Clustering, Neue Themen Abstract = Frühzeitiges Erkennen von aufkommenden Themengebieten in der Wissenschaft unterstützt sowohl Entscheidungen auf individueller als auch öffentlicher Ebene. Viele bestehende Verfahren beschränken sich auf eine retrospektive (Zitations-)Analyse der Publikationsdaten. Das Ziel der vorliegenden Arbeit war deshalb die Entwicklung eines Verfahrens, das zeitnah und neutral sogenannte "emerging topic candidates" aus einem Set von wissenschaftlichen Publikationen auswählt

Hidden Citations Obscure True Impact in Science

References, the mechanism scientists rely on to signal previous knowledge, lately have turned into widely used and misused measures of scientific impact. Yet, when a discovery becomes common knowledge, citations suffer from obliteration by incorporation. This leads to the concept of hidden citation, representing a clear textual credit to a discovery without a reference to the publication embodying it. Here, we rely on unsupervised interpretable machine learning applied to the full text of each paper to systematically identify hidden citations. We find that for influential discoveries hidden citations outnumber citation counts, emerging regardless of publishing venue and discipline. We show that the prevalence of hidden citations is not driven by citation counts, but rather by the degree of the discourse on the topic within the text of the manuscripts, indicating that the more discussed is a discovery, the less visible it is to standard bibliometric analysis. Hidden citations indicate that bibliometric measures offer a limited perspective on quantifying the true impact of a discovery, raising the need to extract knowledge from the full text of the scientific corpus