TY - GEN
T1 - A Campaign Mining in Social Media using Improved K-Means
T2 - 5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022
AU - Zaman, Badrus
AU - Putra, Cendra Devayana
AU - Justitia, Army
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The presidential candidate socializes the vision and mission to persuade supporters and voters as much as possible during the campaign. Since 2010, presidential campaigns in Indonesia have extensively used social media networks as a standard form of presidential communication. However, the presidential candidate's campaign duration has not been maximized to convey the vision and mission to prospective voters. This study aims to identify each candidate's focus based on tweet analysis using Improved K-Means and a second-level normalization algorithm. The data consisted of 2,786 tweets from January to April 2019, obtained from two sources: 1,485 tweets from candidate#1 and 1,301 tweets from candidate#2. The results show that there are 16 clusters created from candidate#1 and 14 from others. Most candidate#1 aligns with its mission. Consequently, our study could clarify the presidential candidate's mission focus. The more frequently the mission is discussed on social media, the more notable it is as the President's primary work program. The first candidate's tweets mainly mentioned the fourth mission, and the second one was about the first mission. Furthermore, there is a link between the frequency of tweets from the presidential candidate's mission and the theme of the presidential debate.
AB - The presidential candidate socializes the vision and mission to persuade supporters and voters as much as possible during the campaign. Since 2010, presidential campaigns in Indonesia have extensively used social media networks as a standard form of presidential communication. However, the presidential candidate's campaign duration has not been maximized to convey the vision and mission to prospective voters. This study aims to identify each candidate's focus based on tweet analysis using Improved K-Means and a second-level normalization algorithm. The data consisted of 2,786 tweets from January to April 2019, obtained from two sources: 1,485 tweets from candidate#1 and 1,301 tweets from candidate#2. The results show that there are 16 clusters created from candidate#1 and 14 from others. Most candidate#1 aligns with its mission. Consequently, our study could clarify the presidential candidate's mission focus. The more frequently the mission is discussed on social media, the more notable it is as the President's primary work program. The first candidate's tweets mainly mentioned the fourth mission, and the second one was about the first mission. Furthermore, there is a link between the frequency of tweets from the presidential candidate's mission and the theme of the presidential debate.
KW - campaign
KW - k-means
KW - mission
KW - presidential election
KW - tweet
UR - http://www.scopus.com/inward/record.url?scp=85150192994&partnerID=8YFLogxK
U2 - 10.1109/ISRITI56927.2022.10052929
DO - 10.1109/ISRITI56927.2022.10052929
M3 - Conference contribution
AN - SCOPUS:85150192994
T3 - 2022 5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022
SP - 230
EP - 235
BT - 2022 5th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 December 2022 through 9 December 2022
ER -