12,250 research outputs found

    Gender Disparities in Science? Dropout, Productivity, Collaborations and Success of Male and Female Computer Scientists

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    Scientific collaborations shape ideas as well as innovations and are both the substrate for, and the outcome of, academic careers. Recent studies show that gender inequality is still present in many scientific practices ranging from hiring to peer-review processes and grant applications. In this work, we investigate gender-specific differences in collaboration patterns of more than one million computer scientists over the course of 47 years. We explore how these patterns change over years and career ages and how they impact scientific success. Our results highlight that successful male and female scientists reveal the same collaboration patterns: compared to scientists in the same career age, they tend to collaborate with more colleagues than other scientists, seek innovations as brokers and establish longer-lasting and more repetitive collaborations. However, women are on average less likely to adapt the collaboration patterns that are related with success, more likely to embed into ego networks devoid of structural holes, and they exhibit stronger gender homophily as well as a consistently higher dropout rate than men in all career ages

    Social Networks of Researchers in Business To Business Marketing: A Case Study of the IMP Group 1984-1999

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    Science is a social process that functions through social networks of researchers that form invisible colleges. Analysis of these social networks provides a means for examining the structure of relations among researchers. The Industrial Marketing and Purchasing (IMP) group, "an informal international group of scholars concerned with developing concepts and knowledge in the field of business-to-business marketing and purchasing," is used as a case study of a network of researchers because it has been responsible for considerable research over the last decades in the area of business-to-business marketing, yet its structure remains hidden because of its informal network characteristics. The results of a social network analysis of the IMP group is described based on the pattern of co-authorship at annual IMP conferences. The results reveal a power law distribution of paper co-authorship and a small world network that conforms to the results of studies of other types of social networks. A core network of 57 researchers is identified and its network properties are described, including how it has evolved over time. The study provides the basis for further studies of the social networks of marketing and business researchers.informal networks, business-to-business marketing

    Name Disambiguation from link data in a collaboration graph using temporal and topological features

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    In a social community, multiple persons may share the same name, phone number or some other identifying attributes. This, along with other phenomena, such as name abbreviation, name misspelling, and human error leads to erroneous aggregation of records of multiple persons under a single reference. Such mistakes affect the performance of document retrieval, web search, database integration, and more importantly, improper attribution of credit (or blame). The task of entity disambiguation partitions the records belonging to multiple persons with the objective that each decomposed partition is composed of records of a unique person. Existing solutions to this task use either biographical attributes, or auxiliary features that are collected from external sources, such as Wikipedia. However, for many scenarios, such auxiliary features are not available, or they are costly to obtain. Besides, the attempt of collecting biographical or external data sustains the risk of privacy violation. In this work, we propose a method for solving entity disambiguation task from link information obtained from a collaboration network. Our method is non-intrusive of privacy as it uses only the time-stamped graph topology of an anonymized network. Experimental results on two real-life academic collaboration networks show that the proposed method has satisfactory performance.Comment: The short version of this paper has been accepted to ASONAM 201
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