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  1. NTU Theses and Dissertations Repository
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Please use this identifier to cite or link to this item: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/18198
Title: 中國大陸網路小說搜索量擴散模型之建構
The Diffusion Model Creation of the search volume of Network Paid Novels in Mainland China
Authors: Yuan-Yuan Tang
湯媛媛
Advisor: 任立中
Keyword: Bass模型,網路文學,搜索引擎,
Bass Model,Network Literature,search engine,
Publication Year : 2014
Degree: 碩士
Abstract: 近15年,中國互聯網迅速發展,為網路小說的大眾化奠定了基礎。與此同時,全新的盈利模式催生出一大批網路作者。其中按字收費的銷售方式,相比傳統整本出售的銷售方式,對作者提出了更高的要求。
目前大多數小說的績效研究,多以銷量收入作為指標依據。但是對於作者而言,如果他能在小說上架之前提前預期讀者的反饋,便能在選材、篇幅、單價等可控因素上做更多的調整,從而獲得更大的收益。
本研究應用 Bass (1969) 所推出創新產品擴散模型架構。模型假設,受眾決定購買新產品的行為基於兩種影響,大眾傳媒的影響以及口碑傳播的影響。前者稱之為『創新者』;後者稱之為『模仿者』。
本研究取得2013年百度搜索引擎上最受關註的小說的周搜索數據,為網路小說產業尋找有效的預測模型,並研究其準確性。
論文將以過去的研究為基礎,將不同的、可能影響新產品擴散過程的因素導入模型。藉由不同的因素之比較,期待能找出一個較為有效的預測模型,協助網路小說作者訂定更有效的寫作策略。
For the past 15 years,the Internet was prospering to a point that it has provided a foundation for the popularization of network literature in China. Meanwhile, a large number of network novel writers have appeared with a new revenue-making model——the so called “pay-per-word” strategy that makes more demands to the writers than the traditional pay-per-copy strategy.
Most novel researches were based on the revenue of sales. However, to the writers,if they can predict the reactions of readers and the market values before their novels hit shelves,they may be able to obtain the maximum benefit by adjusting the controllable-factors such as subjects,chapters,and unit prices. The main analytical method of this research is based on Bass Diffusion Model, which is based on the hypothesis that a prospector decides to adapt innovation products is under two kinds of influences:“mass media” and “word-of mouth”. In this hypothesis, the “innovator”means the purchase behavior is influenced by mass media; on the other hand,the purchase behavior of“imitator”is influenced by word-of mouth.
This study seeks to develop an effective forecasting model for network novel industry. This study focuses on weekly data of the most popular network novels on the Baidu search engine in 2013 to construct the diffusion models and investigate their accuracy. In this thesis, it introduces different factors that may influence the diffusion process of the new product into the models. By comparing different factors,it is hoped to find an efficient forecasting method,with greater forecasting ability and help network novel writers developing more profitable writing strategy.
URI: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/18198
Fulltext Rights: 未授權
Appears in Collections:國際企業學系

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