Understanding Russian Information Operations Using Unsupervised Multilingual Topic Modeling

2017 ◽  
pp. 102-107 ◽  
Author(s):  
Peter A. Chew ◽  
Jessica G. Turnley
Keyword(s):  
Topic Modeling ◽  
Information Operations

scholarly journals Leveraging Publicly Available Information to Analyze Information Operations

2022 ◽  
Vol 9 (2) ◽  
pp. 142-148
Author(s):  
Nico Manzonelli ◽  
Taylor Brown ◽  
Antonio Avellandea-Ruiz ◽  
William Bagley ◽  
Ian Kloo
Keyword(s):  
Language Processing ◽  
Subject Matter ◽  
Topic Modeling ◽  
Model System ◽  
Subject Matter Experts ◽  
Intensive Study ◽  
Automated Method ◽  
Information Operations ◽  
Available Information

Traditionally, a significant part of assessing information operations (IO) relies on subject matter experts’ time- intensive study of publicly available information (PAI). Now, with massive amounts PAI made available via the Internet, analysts are faced with the challenge of effectively leveraging massive quantities of PAI to draw meaningful conclusions. This paper presents an automated method for collecting and analyzing large amounts of PAI from China that could better inform assessments of IO campaigns. We implement a multi-model system that involves data acquisition via web scraping and analysis using natural language processing (NLP) techniques with a focus on topic modeling and sentiment analysis. After conducting a case study on China’s current relationship with Taiwan and comparing the results to validated research by a subject matter expert, it is clear that our methodology is valuable for drawing general conclusions and pinpointing important dialogue over a massive amount of PAI.

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.

A Topic Modeling Analysis on the Major Social Issues of the Students’ Human Rights Ordinance in Korea

2017 ◽  
Vol 18 (4) ◽  
pp. 683-711
Author(s):  
Hyun-Jeong Park ◽  
Hanna Kim ◽  
YuJung Hong
Keyword(s):  
Human Rights ◽  
Topic Modeling ◽  
Social Issues ◽  
Modeling Analysis

Research Trends of Consumer Education Using Topic Modeling

2020 ◽  
Vol 16 (2) ◽  
pp. 83-115
Author(s):  
Mira Kim ◽  
◽  
Hye Sun Hwang ◽  
Xu Li
Keyword(s):  
Topic Modeling ◽  
Research Trends ◽  
Consumer Education

The Effect of Reference List in the Article on Topic Modeling using LDA

2019 ◽  
Vol 58 (6) ◽  
pp. 197-207
Author(s):  
Juhae Baeck ◽  
Hyungil Kwon ◽  
Mihwa Choi ◽  
Yi-Hsiu Lin
Keyword(s):  
Topic Modeling ◽  
Reference List

SCM Patent Analysis Using Topic Modeling: 1997~2016

2017 ◽  
Vol 17 (2) ◽  
pp. 19-29
Author(s):  
Mi-Ae Kim ◽  
Chang-Kyo Suh
Keyword(s):  
Topic Modeling ◽  
Patent Analysis

A comparative analysis of crime fiction and crime nonfiction using topic modeling

2018 ◽  
Vol 22 (3) ◽  
pp. 109-134
Author(s):  
JIHYO KIM ◽  
Eon-Suk Ko
Keyword(s):  
Comparative Analysis ◽  
Topic Modeling ◽  
Crime Fiction
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