運用分群演算法找出Facebook粉絲團的意見領袖

Finding the Opinion Leaders in Facebook Fan Pages via a Clustering Approach

林冠呈(Kuan-Cheng Lin)

指導教授 ： 吳世弘

朝陽科技大學/資訊學院/資訊工程系/碩士(2015年)

摘要

Facebook粉絲團是現今最流行的社群媒體之一，許多企業在粉絲團中發現新的商機，漸漸地粉絲團成為熱門的行銷工具。企業經營者可以透過Facebook粉絲團與粉絲們進行互動，如：發佈產品廣告、宣傳活動…等來經營自家品牌的網路口碑(e-WOM)。本研究收集了2013年10月至2014年9月的Facebook粉絲團資料，並以分群技術為基礎，提出一個找出粉絲團中意見領袖的方法，並以非監督式機器學習方法評估分群結果的好壞，以提供企業經營者作為行銷參考。

關鍵字

社群媒體 ； 分群演算法 ； 粉絲專頁 ； 意見領袖

並列摘要

The Service of Facebook Fan Pages is one of the most popular social network platform for various organizations. Companies can interact with their own fans through the Fan Pages. The interactions include sending direct advertisement, gathering user meetings, and promoting electronic word of mouth (eWoM). For companies that use social network to gather customers’ information, to identify the opinion leaders on the internet is very important, since opinion leaders are active persons and have influence on other potential customers. Based on clustering algorithm, we proposed a system that can find the opinion leaders and test our method on the Facebook Fan Pages. The data set includes 410,045 comments from 173,988 users that we gathered from October 2013 to September 2014. We also use classification methods to evaluate our system and find promising result.

並列關鍵字

social network ； user clustering mining ； facebook fan page ； opinion leader

參考文獻

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