期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：11
页码：240-245
出版社：Science and Information Society (SAI)
摘要：Propaganda is a form of communication that is
used in influencing communities, or people in general, to push
forward an agenda for a certain goal. Nowadays, there are
different means used in distributing propaganda including
postings on social media, illustrations, cartoons and animations,
articles, TV and radio shows. This paper is focused on election
propaganda. Candidates in elections would use propaganda as a
form of communication to channel and deliver messages through
social media. Sentiment analysis (SA) is then used in identifying
the positive and negative elements within the propaganda itself,
through analysing the related documents, social media, articles
or forums. This paper presents the various techniques used by
previous researchers in issues of propaganda using SA, which
include feature selection to remove irrelevant features and
sentiment methods to identify sentiment in documents or others.
Feature selection is a dominant side in sentiment analysis due to
content of textual has a high measurement classification that can
jeopardize SA classification interpretation. This paper also
explores several SA techniques to identify sentiments in issues of
propaganda. This study has also attempted to identify the use of
swarm algorithms as a suitable feature selection method in SA
for propaganda issues.
