Title

基於Google Analytics之自主學習網站內容評估管理機制

DOI

10.6679/TANET.2016.121

Authors

許舜博;梅興

Key Words

自主學習 ; 網站管理 ; 網頁內容評估 ; 臉書通訊機器人 ; Self-Motivated Learning ; Web Management ; Web Content Quality ; FaceBook Messenger Bot

PublicationName

TANET2016 臺灣網際網路研討會

Volume or Term/Year and Month of Publication

2016(2016 / 11 / 01)

Page #

673 - 678

Content Language

繁體中文

Chinese Abstract

由於網路的普及,網站已成為傳遞內容或自主學習最主要的平台。網站管理者期望網站的內容能夠符合使用者的需求,內容品質是影響網站整體價值的關鍵因素。了解網站內容動態狀況成了管理者的重要課題。對自主學習而言,眾多的內容經常讓學習者困惑,要找到符合期望的內容相當不容易。本研究運用Google Analytics 分析宅學習網路社群學習平台的流量。藉由分析流量數據中的瀏覽量;及根據時戳推演的平均瀏覽時間;設計了一個網頁內容評估指標。評估指標搭配另一個內容長度參數,能夠針對訪客想要查看的內容網頁提出最佳品質推薦。除了在內容網站得到推薦,我們也在FaceBook 粉絲頁以Messenger Bot 實作推薦機制。另一方面,本研究也將網頁依據其內容評估指標分類,網站經營者能夠分辨出高效益內容網頁、需要內容更新、甚或可以直接刪除的內容網頁。

English Abstract

Due to the popularity of the Internet, the website has become a major platform of content delivering and self-learning. Content quality is a key factor affecting the overall value of the site. Webmasters hope content of the site can answer the expectations of users. Aware of the dynamic content status is a critical responsibility for webmasters. As to self-motivated learners, the huge amount of contents usually confusing them to locate the desired page. This research analyzed web traffic of the Social Learning Space through web site with Google Analytics. By analyzing traffic data in page views; together with the time-stamped average browsing time; we proposed a Quality Rank index for web page content evaluation. Consider both the Quality Rank and the length of content, the recommendation with most qualified pages is ready to deliver. Beside the web site itself, We implemented the recommendation on FaceBook fan page with Messenger Bot. On the other hand, this research also classifies web content with the Quality Rank index. With the classification, webmaster can easily distinguish pages with high efficiency; pages need to be updated, or pages can be removed.

Topic Category 基礎與應用科學 > 資訊科學