基于支持向量机的KOMINFO数据泄露事件舆情分析

Rayhan Sabian, Antok Supriyanto, Sulistiowati
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引用次数: 0

摘要

一个名为Bjorka的账户声称从通信和信息部(Kemkominfo)的政府数据库(Kemkominfo)中获取了数十亿张身份证和家庭卡号形式的SIM卡注册数据,人们开始质疑政府数据库的网络安全。Bjorka黑客的出现在推特上引起了各种各样的反应,一些人支持Bjorka的行为,一些人不同意。因此,需要进行情绪分析,以确定公众的情绪是消极的还是积极的,以便政府可以进行评估和战略规划,以应对未来的数据泄露事件。本研究使用包含公众回应的推文,使用支持向量机算法来预测消极或积极的情绪。从总共1017条公众回应数据中,我们发现97.35%(990条)的人有负面情绪,2.65%(27条)的人有正面情绪,因此可以知道公众对Bjorka泄露数据的反应是负面的。总之,对公众进行有关Bjorka数据泄露的教育并不是政府的首要任务。政府可以把更多精力放在处理其他领域,比如提高数据本身的安全性。
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Public Sentiment Analysis of KOMINFO Data Leaking by Bjorka using Support Vector Machine
An account with the name Bjorka claims to have obtained billions of SIM card registration data in the form of Identity Card and Family Card Nuber from the government database of the Ministry of Communication and Informatics (Kemkominfo), people start questioning the cybersecurity of the government database. The appearance of the Bjorka hacker caused various responses on Twitter, some supported Bjorka’s action and some disagree. Hence the need for sentiment analysis to determine public sentiment is more towards negative or positive, so the government can do evaluation as well as strategic planning to deal with future data leaking incidents. This study uses tweets that contain public responses to predict negative or positive sentiment using Support Vector Machine algorithm. From a total of 1017 public response data, have been found 97.35% (990 tweets) to have negative sentiment and 2.65% (27 tweets) have positive sentiment, so it can be known that public responses are towards negative about data leaking by Bjorka. In conclusion, education to the public about data leaks by Bjorka is not the main priority to do for the government. The government can focus more on dealing with other sectors such as improving the security of the data itself.
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