scholarly journals Expert Opinion and Coherence Based Topic Modeling

2018 ◽  
Author(s):  
Natchanon Suaysom ◽  
Weiqing Gu
Keyword(s):  
Expert Opinion ◽  
Topic Modeling

scholarly journals Expert Opinion and Coherence Based Topic Modeling

2018 ◽  
Vol 7 (2) ◽  
pp. 01-14 ◽  
Author(s):  
Natchanon Suaysom ◽  
Weiqing Gu
Keyword(s):  
Expert Opinion ◽  
Topic Modeling

Half a Century of NVSQ: Thematic Stability Across Years and Editors

2021 ◽  
pp. 089976402110176
Author(s):  
Chul Hee Kang ◽  
Young Min Baek ◽  
Erin Hea-Jin Kim
Keyword(s):  
Expert Opinion ◽  
Topic Modeling ◽  
Nonprofit Sector ◽  
Voluntary Sector ◽  
Analytic Method ◽  
Structural Topic Modeling ◽  
Over Time

The aim of this article is to understand how the scholarship of the nonprofit sector shifted after almost half a century (1972–2019) of publication in the field’s premier journal, Nonprofit and Voluntary Sector Quarterly. Unlike previous attempts to understand the field’s scholarly evolution, we did not rely on expert opinion and analysis of themes but applied an automated content analytic method, more specifically structural topic modeling (STM). Using this method, we identified 37 key thematic topics that most optimally represent the 1,516 articles that were published in the studied period. After reporting these 37 thematic topics, we analyzed fluctuations based on three key periods of the journal and the editors’ disciplinary fields. While overall there was a trend of continuity (29 out of 37 topics) and little if any impact of the editors’ disciplines, a few thematic topics showed decline and fewer showed increase over time.

Innovative Approach to Information Search by Example of a Patent Analysis of an Important Substitution Plan

2020 ◽  
pp. 143-157
Author(s):  
Maria A. Milkova
Keyword(s):  
Information Search ◽  
Topic Modeling ◽  
Cognitive Biases ◽  
A Priori ◽  
Import Substitution ◽  
Innovative Approach ◽  
Iterative Search ◽  
Comprehensive Picture ◽  
Priori Information ◽  
Selection Of

Nowadays the process of information accumulation is so rapid that the concept of the usual iterative search requires revision. Being in the world of oversaturated information in order to comprehensively cover and analyze the problem under study, it is necessary to make high demands on the search methods. An innovative approach to search should flexibly take into account the large amount of already accumulated knowledge and a priori requirements for results. The results, in turn, should immediately provide a roadmap of the direction being studied with the possibility of as much detail as possible. The approach to search based on topic modeling, the so-called topic search, allows you to take into account all these requirements and thereby streamline the nature of working with information, increase the efficiency of knowledge production, avoid cognitive biases in the perception of information, which is important both on micro and macro level. In order to demonstrate an example of applying topic search, the article considers the task of analyzing an import substitution program based on patent data. The program includes plans for 22 industries and contains more than 1,500 products and technologies for the proposed import substitution. The use of patent search based on topic modeling allows to search immediately by the blocks of a priori information – terms of industrial plans for import substitution and at the output get a selection of relevant documents for each of the industries. This approach allows not only to provide a comprehensive picture of the effectiveness of the program as a whole, but also to visually obtain more detailed information about which groups of products and technologies have been patented.

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