Skip to main content
36
Views
163
Downloads
Reviewed article

Aspect Level Sentiment Analysis Methods Applied to Text in Formal Military Reports

How to cite:
Ivana Mestric, Arvid Kok, Giavid Valiyev, Michael Street, Peter Lenk
"Aspect Level Sentiment Analysis Methods Applied to Text in Formal Military Reports"
Information & Security: An International Journal,
46
no. 3
(2020):
227-238.
https://doi.org/10.11610/isij.4616

Aspect Level Sentiment Analysis Methods Applied to Text in Formal Military Reports

Source:

Information & Security: An International Journal,
Volume: 46,
Issue3,
p.227-238
(2020)

Abstract:

Many military functions such as intelligence collection or lessons learned analysis demand an understanding of situations derived from large quantities of written material. This paper describes approaches to gain greater understanding of document content by applying rule-based approaches in addition to open source machine learning models. The performance of two approaches to sentiment analysis are assessed, when operating on document sets from NATO sources. This combination enables analysts to identify items of interest within large document sets more effectively, by indicating the sentiment around specific aspects (nouns) which refer to a specific target (noun) in the text. This enables data science to give users a more detailed understanding of the content of large quantities of documents with respect to a particular target or subject.

36
Views
163
Downloads