Large networks contain plentiful information about the organization of a system. The challenge is to extract useful information buried in the structure of myriad nodes and links. Therefore, powerful tools for simplifying and highlighting important structures in networks are essential for comprehending their organization. Such tools are called community-detection methods and they are designed to identify strongly intraconnected modules that often correspond to important functional units. Here we describe one such method, known as the map equation, and its accompanying algorithms for finding, evaluating, and visualizing the modular organization of networks. The map equation framework is very flexible and can identify two-level, multi-level, and overlapping organization in weighted, directed, and multiplex networks with its search algorithm Infomap. Because the map equation framework operates on the flow induced by the links of a network, it naturally captures flow of ideas and citation flow, and is therefore well-suited for analysis of bibliometric networks.

Measuring Scholarly Impact

The relationship between a firm's patent quality and its market value — The case of US pharmaceutical industry

The proportion of zeros in event-count processes may be inflated by an additional mechanism by which zeros are created. This has given rise to statistical models that accommodate zero inflation; these are available in Stata through the zip and zinb commands. The Vuong (1989, Econometrica 57: 307�333) test is regularly used to determine whether estimating a zero-inflation component is appropriate or whether a single-equation count model should be used. The use of the Vuong test in this case is complicated by the fact that zero-inflated models involve the estimation of several more parameters than the single-equation models. Although Vuong (1989, Econometrica 57: 307�333) suggested corrections to the test statistic to address the comparison of models with different numbers of parameters, Stata does not implement any such correction. The result is that the Vuong test used by Stata is biased toward supporting the model with a zero-inflation component, even when no zero inflation exists in the generative process. We provide new Stata commands for computing the Vuong statistic with corrections based on the Akaike and Bayesian (Schwarz) information criteria. In an extensive Monte Carlo study, we illustrate the bias inherent in using the uncorrected Vuong test, and we examine the relative merits of the Akaike and Schwarz corrections. Then, in an empirical example from international relations research, we show that errors in selecting an event-count model can have clear implications for substantive conclusions

https://journals.sagepub.com/doi/pdf/10.1177/1536867X1301300408

Testing for zero inflation in count models: Bias correction for the Vuong test

Recent works in the information science literature have presented cases of using patent databases and patent classification information to construct network maps of technology fields, which aim to aid in competitive intelligence analysis and innovation decision making. Constructing such a patent network requires a proper measure of the distance between different classes of patents in the patent classification systems. Despite the existence of various distance measures in the literature, it is unclear how to consistently assess and compare them, and which ones to select for constructing patent technology network maps. This ambiguity has limited the development and applications of such technology maps. Herein, we propose to compare alternative distance measures and identify the superior ones by analyzing the differences and similarities in the structural properties of resulting patent network maps. Using United States patent data from 1976 to 2006 and the International Patent Classification IPC system, we compare 12 representative distance measures, which quantify interfield knowledge base proximity, field-crossing diversification likelihood or frequency of innovation agents, and co-occurrences of patent classes in the same patents. Our comparative analyses suggest the patent technology network maps based on normalized coreference and inventor diversification likelihood measures are the best representatives.

Measuring technological distance for patent mapping

The paper investigates three aspects of patent value - technological value, direct economic value, and indirect economic value. The paper suggests that we measure the technological value of a patent by looking at its number of citations, direct economic value by looking at its licensing and income from royalties, and indirect economic value by looking at its life (i.e., duration). For the research, the author’s two previous studies are deeply explored. It is found that these three aspects of patent value are positively correlated with one another. In addition, their domains overlap and interrelate. Research collaboration is the one variable found to have a significant effect on all three aspects. The field effect of electronics positively affects technological and indirect economic value, whereas research team size negatively affects technological and indirect economic value.

What affects a patent’s value? An analysis of variables that affect technological, direct economic, and indirect economic value: An exploratory conceptual approach

Patent citation counts represent an aspect of patent quality and knowledge flow. Especially, citation data of US patents contain most valuable pieces of the information among other patents. This paper identifies the factors affecting patent citation counts using US patents belonging to Korea Institute of Science and Technology (KIST). For patent citation count model, zero-inflated models are announced to handle the excess zero data. For explanatory factors, research team characteristics, invention-specific characteristics, and geographical domain related characteristics are suggested. As results, the size of invention and the degree of dependence upon Japanese technological domain significantly affect patent citation counts of KIST.

An in-depth empirical analysis of patent citation counts using zero-inflated count data model: The case of KIST

Purpose - The purpose of this paper is to compare and review behavioral economics models that explain stock price changes after large-scale price shocks in the Korean stock market and to find a suitable model. In this paper, among the theories reviewed, it was confirmed that the anchoring heuristics theory has high explanatory power for stock prices after large-scale stock price fluctuations. 
Design/methodology/approach - This paper conducts an event study on stock price shocks in which the individual stocks that make up the KOSPI200 index show more than 10% fluctuation on a daily basis. In order to materialize the abstract predictions of heuristics theories in a varifiable form, this paper uses the daily stock price index change as a reference point for availability heuristics, and uses the 52-week highest and lowest price as reference point for anchoring heuristics. 
Research implications or Originality - As a result of the empirical analysis, the stock price reversals did not consistently appear for changes in the daily index. On the other hand, the stock price drifts consistently appeared around the 52-week highest and the 52-week lowest price. And in the multiple regression analysis that controlled for company-specific and event-specific variables, the results that supported the anchoring heuristics were more evident. These results suggest that it is possible to establish an investment strategy using large-scale price change in Korean stock market.

Se-Jun Lee

Papers

An in-depth empirical analysis of patent citation counts using zero-inflated count data model: The case of KIST

An Empirical Study on the Validity of the Availability Huristics and Anchoring Huristics in the Korean Stock Market