BUSINESS INTELLIGENCE (BI) PRESIDENTIAL CANDIDATES BASED ON SOCIAL NETWORK ANALYSIS (SNA) WITH TWITTER DATA

The twitter social network is widely used to discuss all kinds of topics, including those related to politics. Analyzing online conversations on Twitter to map the popularity of political figures as candidates for the Indonesian presidential election is a popular and challenging research area. In the Twitter network, citizens can express themselves and communicate with political figures. The conversational data in Twitter is very complex, so Business Intelligence is needed to transform raw data into meaningful and useful information to see the popularity of Indonesian presidential election candidates. The analysis used is Social Network Analysis (SNA) by measuring Degree Centrality, Eigenvector Centrality, Betweenness Centrality, Closeness Centrality. The presidential candidates in this study, Ganjar Pranowo with a twitter account “ganjarpranowo”, Puan Maharani with a twitter account “puanmaharani_ri”, and Anies Baswedan with a twitter account “aniesbaswedan”. The actor "aniesbaswedan" excels in the value of degree centrality and betweenness centrality. The “aniesbaswedan” account is the actor who has the most influence on social network interactions based on the total number of interactions generated, then the account also becomes a bridge or liaison in the interactions of other actors in the network.

Authors

Institutions

Publication Details

Journal
Parameter Journal of Statistics
Published
2024-12-31
DOI
https://doi.org/10.22487/27765660.2024.v4.i2.17143
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

BUSINESS INTELLIGENCE (BI) PRESIDENTIAL CANDIDATES BASED ON SOCIAL NETWORK ANALYSIS (SNA) WITH TWITTER DATA

Imran Ali, Abba Suganda Girsang
Parameter Journal of Statistics
Big Data and Business Intelligence
article

BUSINESS INTELLIGENCE (BI) PRESIDENTIAL CANDIDATES BASED ON SOCIAL NETWORK ANALYSIS (SNA) WITH TWITTER DATA

Imran Ali, Abba Suganda Girsang
article en

Abstract

The twitter social network is widely used to discuss all kinds of topics, including those related to politics. Analyzing online conversations on Twitter to map the popularity of political figures as candidates for the Indonesian presidential election is a popular and challenging research area. In the Twitter network, citizens can express themselves and communicate with political figures. The conversational data in Twitter is very complex, so Business Intelligence is needed to transform raw data into meaningful and useful information to see the popularity of Indonesian presidential election candidates. The analysis used is Social Network Analysis (SNA) by measuring Degree Centrality, Eigenvector Centrality, Betweenness Centrality, Closeness Centrality. The presidential candidates in this study, Ganjar Pranowo with a twitter account “ganjarpranowo”, Puan Maharani with a twitter account “puanmaharani_ri”, and Anies Baswedan with a twitter account “aniesbaswedan”. The actor "aniesbaswedan" excels in the value of degree centrality and betweenness centrality. The “aniesbaswedan” account is the actor who has the most influence on social network interactions based on the total number of interactions generated, then the account also becomes a bridge or liaison in the interactions of other actors in the network.

Parameter Journal of StatisticsVol. 4(2)
Binus University (ID)
Openalex Percentile: Top 60%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.