Abstract: 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.

Siti Rohaidah Ahmad, Muhammad Zakwan Muhammad Rodzi, Nurlaila Syafira Shapiei, Nurhafizah Moziyana Mohd Yusop and Suhaila Ismail, “A Review of Feature Selection and Sentiment Analysis Technique in Issues of Propaganda” International Journal of Advanced Computer Science and Applications(IJACSA), 10(11), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101132

@article{Ahmad2019,
title = {A Review of Feature Selection and Sentiment Analysis Technique in Issues of Propaganda},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2019.0101132},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101132},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {11},
author = {Siti Rohaidah Ahmad and Muhammad Zakwan Muhammad Rodzi and Nurlaila Syafira Shapiei and Nurhafizah Moziyana Mohd Yusop and Suhaila Ismail},
}