Characterizing Interdisciplinarity of Researchers and Research Topics Using Web Search Engines

Researchers' networks have been subject to active modeling and analysis. Earlier literature mostly focused on citation or co-authorship networks reconstructed from annotated scientific publication databases, which have several limitations. Recently, general-purpose web search engines have also been utilized to collect information about social networks. Here we reconstructed, using web search engines, a network representing the relatedness of researchers to their peers as well as to various research topics. Relatedness between researchers and research topics was characterized by visibility boost-increase of a researcher's visibility by focusing on a particular topic. It was observed that researchers who had high visibility boosts by the same research topic tended to be close to each other in their network. We calculated correlations between visibility boosts by research topics and researchers' interdisciplinarity at individual level (diversity of topics related to the researcher) and at social level (his/her centrality in the researchers' network). We found that visibility boosts by certain research topics were positively correlated with researchers' individual-level interdisciplinarity despite their negative correlations with the general popularity of researchers. It was also found that visibility boosts by network-related topics had positive correlations with researchers' social-level interdisciplinarity. Research topics' correlations with researchers' individual- and social-level interdisciplinarities were found to be nearly independent from each other. These findings suggest that the notion of "interdisciplinarity" of a researcher should be understood as a multi-dimensional concept that should be evaluated using multiple assessment means.Comment: 20 pages, 7 figures. Accepted for publication in PLoS On

The quark-meson coupling model for Lambda, Sigma and Xi hypernuclei

The quark-meson coupling (QMC) model, which has been successfully used to describe the properties of both infinite nuclear matter and finite nuclei, is applied to a systematic study of $\Lambda, \Sigma$ and $\Xi$ hypernuclei. Assumptions made in the present study are, (i) the (self-consistent) exchanged scalar, and vector, mesons couple only to the u and d quarks, and (ii) an SU(6) valence quark model for the bound nucleons and hyperon. The model automatically leads to a very weak spin-orbit interaction for the $\Lambda$ in a hypernucleus. Effects of the Pauli blocking at the quark level, particularly in the open, coupled, $\Sigma N - \Lambda N$ channel (strong conversion), is also taken into account in a phenomenological way.Comment: 27 pages, 14 postscript figures, uses epsfig.sty. Version to appear in Nucl. Phys.

Agent-Based Modeling for Investigating Adaptivity of

Misperception is a term which is generally used in a negative sense. However, when information promoting a certain kind of behavior is obtained, it can happen that the diversity of the behavior is enhanced by the misperceptions of the individual in the population, resulting in a situation in which misperception works advantageously for the population. This paper presents this view in terms of four hypotheses, dealing with (1) the basic adaptivity of misperception, (2) basic properties of communication, (3) the adaptivity of misperception in communication, and (4) the behavioral specificity of information in the adaptivity of misperception. A simple agent model for the resourcesearching problem is constructed. Direct misperception, which is misperception in the direct acquisition of information from the surrounding environment, and indirect misperception, which occurs when information is obtained through communication, are considered. Their effects are investigated by simulation experiments. It is shown that misperception enhances the diversity of agent behavior and can contribute to adaptivity. It is also shown that exact communication may decrease the diversity of agent behavior, and that adaptivity is decreased when false information is shared. A tendency for the adaptivity of misperception to decrease when the behavioral specificity in information terms is low is demonstrated. We believe that study of the adaptivity of misperception as a factor generating diversity will lead to new findings in cognitive science, memetics

An example of “visibility boost" calculation.

<p>This figure shows how to calculate the visibility boost by research topic “network" for the researcher A in the middle (blue).</p

Two dimensional maps summarizing each research topic's correlations with a researcher's individual-level interdisciplinarity (vertical, topic hit entropy) and social-level interdisciplinarity (horizontal, three centrality measurements).

<p>Two dimensional maps summarizing each research topic's correlations with a researcher's individual-level interdisciplinarity (vertical, topic hit entropy) and social-level interdisciplinarity (horizontal, three centrality measurements).</p

Reconstructed network of 1,000 researchers.

<p>(A) Visualized network. Each node represents a researcher. (B) Distribution of total link weights of nodes, plotted as a complementary cumulative distribution function (CCDF).</p