Uncovering Internet Armies on PTT

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姓名

卓沛妤(Pei-Yu Cho) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

(Uncovering Internet Armies on PTT)

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摘要(中)

由於網路平台的大幅擴張，網軍(Internet army)這個工作也隨之
增加，公關公司會付錢給學生或無工作者，讓他們發文或回覆
來影響輿論風向。
PTT 在台灣是相當大的網路平台，由於其匿名性以及能見度
高，大量的網軍因此將這個平台視為主要的攻擊對象，許多網
軍會針對特殊議題進行帶風向。
因此，找到一種方法來偵測匿名平台中的網軍是很重要的議
題。在此篇研究中，I.A.D 系統針對網軍進行分析獲得數個網
軍的特徵，並藉由網軍特徵建立預測模型，使系統能夠判斷使
用者是否是網軍。

摘要(英)

As the expansion of online social network, the occupation number of Internet
army has increased. Students or unemployed post some article or reply to get
paid by public relationship company, who are also known as paid poster,
would impact peoples’ opinions.
In Taiwan, PTT is such a large platform with anonymity and visibility.
Because of influence of PTT, it has become a main target of Internet armies.
Therefore, it is an important issue to find out a method to detect Internet
armies on anonymous platform. In this research, I.A.D. system(Internet
Armies Detection) analyze and find out some the features of Internet army. In
addition, I.A.D. also build predicted models by features of Internet army. This
makes the system to identify whether a user is Internet army or not.

關鍵字(中)

★ 網軍偵測
★ PTT
★ 機器學習

關鍵字(英)

★ Internet army detection
★ PTT
★ machine learning

論文目次

中文摘要………………………………………………………………………………….i
Abstract………………………………………………………………………………ii
Content………………………………………………………………………………….iii
1. Intrduction…………………………………………………………………………….1
1.1 Research Motivation ………….……..……….…………………………………..….3
1.2 Contribution………….……..……….…………………..…………………..….4
2. Background…………………………………………………………………………….5
2.1 Internet army………….……..……….…………………..…………………..….5
2.2 PTT Bulletin Board System…..……….…………………..…………………..….6
3. Related work…………………………………………………………………………….9
3.1 Internet Army Detection………….……..……….……………………………..….9
3.2 Fake Account Detection…….……..……..….……………………………..….10
3.2.1 Feature-based detection….……..……..….……………………………..….10
3.2.2 Graph-based approaches: ….……..……..….……………….………..….11
4. Methodology………………………………………………………………………….12
4.1 System Architecture…….……..……..….……………………………..….12
4.2 System Execution Flow…….……..……..….……………………………..….13
4.2.1 Data collection….……..………..….……………….………..….16
iv
4.2.2 Manual Identification….……..……..….……………….………..….16
4.2.3 Experiment….……..……………….……………….………..….17
5. Evaluation………………………………………………………………………….19
5.1 Feature Analysis…….……..……..….……………………………..….19
5.1.1 Average Interval Time….……..……..…...……………….………..….19
5.1.2 Number of Replies….……..……..……..……………….………..….20
5.1.3 Board Weight….……..……..………………………….………..….21
5.1.4 Reply to Article Time….……..……..….……………….………..….22
5.2 Identify Internet armies…….……..……..….……………………………..….23
5.2.1 Experiment result….……..……..….……………….………..….23
6. Conclusion………………………………………………………………………….25
Reference………………………………………………………………………….26

參考文獻

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指導教授

許富皓(Fu-Hau Hsu)

審核日期

2022-7-5

推文