精準社群廣告投資策略：以機器學習技術為基礎之社會影響力管理模式

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、以作者查詢臺灣博碩士

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姓名

史庭安(Ting-Ann Shih) 查詢紙本館藏

畢業系所

資訊管理學系

論文名稱

精準社群廣告投資策略：以機器學習技術為基礎之社會影響力管理模式
(Precision Social Advertising Investment Strategy: Managing the Social Influence of Public Figures on Social Media)

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至系統瀏覽論文 (2027-9-6以後開放)

摘要(中)

在 Web 2.0 的背景下，社群網站變得越來越普遍。社群廣告變成了個人和公司接觸其他社交圈的人的強大工具。因此，他們可以提高他們在社群網絡中的社會影響力。然而，線上社群網絡上的有效社交廣告策略尚未得到研。本研究試圖為想要管理個人品牌的人提供精準的社群廣告投資指南。我們選擇了政治這個相對貼近每個人生活的生態系統作為研究對象。為了達到這個目標，我們首先整理了社群媒體平台上的社群廣告。然後我們對廣告進行區隔，探索有效的廣告模式。最後，我們對粉絲專頁進行了分群，並確定了最具社會影響力的粉絲專頁群集。從結果中，我們發現花費和觸及區域是廣告效果的關鍵。除此之外，我們發現加強推廣次數、花費和廣告投遞總天數對於“加強推廣貼文”很重要。最後，除了總廣告數量、廣告數量和免責聲明數量之外真實性驗證也是影響粉絲專頁社會影響力的一個重要因素。

摘要(英)

In the context of Web 2.0, social networking sites become more and more common. Social advertising turned into a powerful tool for individuals and firms to reach people in other social circles. They can thus improve their social influence in the social network. However, effective social advertising strategy on online social network has not been studied. This research tried to provide precision social advertising investing guideline for those who want to manage personal brands. We chose politics, an ecosystem that is relatively close to everyone’s life, as research target. To reach this objective, we first sorted out the social advertisements on social media platform. Then we made the segments of the advertisements and explored the effective
advertising patterns. Finally, we clustered the fan pages and identified the most socially influential cluster of fan pages. From the results, we found that the spends and regions reached are key to advertising performance. Further, we found that boosted times, spends, and delivering days are important to “boosted post”, which is a sub type of advertisement. Finally, authenticity verification is also an important factor for social influence of fan pages besides higher total advertising number, advertising amount, and disclaimer number.

關鍵字(中)

★ 個人品牌
★ 社群廣告
★ 分群

關鍵字(英)

★ Personal Branding
★ Social Advertising
★ Clustering

論文目次

Table of Contents
Chinese Abstract .........................................................................................................................i
English Abstract .........................................................................................................................ii
Acknowledgements ..................................................................................................................iii
Table of Contents......................................................................................................................iv
List of Figures........................................................................................................................... vi
List of Tables ...........................................................................................................................vii
I. Introduction ....................................................................................................................... 1
1-1 Research Background and Motivation .................................................................. 1
1-2 Research Objectives .............................................................................................. 5
1-3 Research Structure................................................................................................. 7
II. Literature Review .............................................................................................................. 9
2-1 Personal Branding on Social Media ...................................................................... 9
2-2 Social Influence Management ............................................................................. 13
2-3 Machine Learning in Social Commerce .............................................................. 16
III. Methodology.................................................................................................................... 25
3-1 Research Design .................................................................................................. 25
3-2 Data Collection.................................................................................................... 26
3-3 Data Preprocessing .............................................................................................. 33
3-4 Data Analysis Tools............................................................................................. 41
3-5 Data Analysis Techniques.................................................................................... 42
v
IV. Research Results and Discussion .................................................................................... 46
4-1 Segmentation Results of the Advertisements ...................................................... 46
4-2 Results of “Boosted Posts” Patterns and the Feedback ....................................... 51
4-3 Clustering Results of the Fan Pages.................................................................... 57
4-4 Evaluation............................................................................................................ 62
V. Research Conclusion and Contribution ........................................................................... 65
5-1 Conclusion and Contribution............................................................................... 65
5-2 Limitation and Future Research .......................................................................... 67
References ............................................................................................................................... 68

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kol100

指導教授

曾筱珽(Hsiao-Ting Tseng)

審核日期

2022-9-6

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