Search (6 results, page 1 of 1)

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Abstract

We surveyed the classes on women's studies in different editions in the LCC (from the 1980 to the 2010 edition) to determine what the main classes consisted of and how they changed over that period. We broke down the main subtopics on women's studies, doing a statistical analysis at the class and subclass level, and then selected several typical examples for in-depth examination. The goal was to show the relationship between the disciplinary development of women's studies and classes on this topic in the LCC. We found that studies about women historically interweaved with family and marriage, but its development should have its own avenue. We found six patterns in the revising of classes associated with women's studies: synthesis, analysis, new creation, expansion, class name change, and removal. Through the comparison and analysis of classes with the additions and revisions to LCCs, supplemented by the bibliographic records from the LC online catalog, we determined that: historic revisions of a certain class show its disciplinary development; synthesis, analysis, comparison, and deduction played important roles in revisions and reflected the discipline's self - understanding on a subject; and a threshold, in terms of number of titles (or "sub-sub topics"), can be established for the creation of a new class . We concluded that a well-systematized classification system facilitates predictions concerning new directions in a discipline. Also, revisions of classification, based on the development of a discipline, will influence that discipline's future development.

Type

a

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Abstract

Purpose - Following the assumption that studies of information inequality need to be based on precise discrimination between society's information rich and poor and against the context that a mechanism for such discrimination is still lacking, the purpose of this paper is to explore the possibility of establishing a holistic informational measurement. Design/methodology/approach - It does so by developing a measurement based on the conceptualization of the individual as an information agent and his/her information world as his/her characterization. The development procedure consists of four steps: operationalization of the theoretical constructs and the initial drafting of the questionnaire instrument; revisions of the questionnaire based on pilot tests with small groups of people; weighing of the questionnaire items for the purpose of calculating index-type variable scores; formal test of validity and reliability. Findings - The resulting measurement consists of eight variables corresponding to eight theoretical constructs of an individual's information world, each being measured by a group of questionnaire-based items which, in turn, generate an index-type score as the variable's value. Validity and reliability tests show that the measurement is, on the whole, able to distinguish the information poor from the information rich and to measure individuals consistently. Originality/value - The study demonstrates that it is possible to distinguish the information rich and poor by informational measurement in the same way as to distinguish economic groups by income, ethnic groups by race and intelligence groups by IQ; and that such a measurement has arguably multifaceted value for information inequality research.

Type

a

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Abstract

We investigated a topic-based navigation guidance system in the World Health Organization portal, compared the link connection network and the semantic connection network derived from the guidance system, analyzed the characteristics of the 2 networks from the perspective of the node centrality (in_closeness, out_closeness, betweenness, in_degree, and out_degree), and provided the suggestions to optimize and enhance the topic-based navigation guidance system. A mixed research method that combines the social network analysis method, clustering analysis method, and inferential analysis methods was used. The clustering analysis results of the link connection network were quite different from those of the semantic connection network. There were significant differences between the link connection network and the semantic network in terms of density and centrality. Inferential analysis results show that there were no strong correlations between the centrality of a node and its topic information characteristics. Suggestions for enhancing the navigation guidance system are discussed in detail. Future research directions, such as application of the same research method presented in this study to other similar public health portals, are also included.

Type

a

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Abstract

Improving health literacy through health information dissemination is one of the most economical and effective mechanisms for improving population health. This process needs to fully accommodate the thematic suitability of health information supply and demand and reduce the impact of information overload and supply-demand mismatch on the enthusiasm of health information acquisition. We propose a health information topic modeling analysis framework that integrates deep learning methods and clustering techniques to model the supply-side and demand-side topics of health information and to quantify the thematic alignment of supply and demand. To validate the effectiveness of the framework, we have conducted an empirical analysis on a dataset with 90,418 pieces of textual data from two prominent social networking platforms. The results show that the supply of health information in general has not yet met the demand, the demand for health information has not yet been met to a considerable extent, especially for disease-related topics, and there is clear inconsistency between the supply and demand sides for the same health topics. Public health policy-making departments and content producers can adjust their information selection and dissemination strategies according to the distribution of identified health topics, thereby improving the effectiveness of public health information dissemination.

Type

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Type

a