本文選題：人類動力學(xué) + 冪律分布　； 參考：《北京郵電大學(xué)》2012年碩士論文

【摘要】：隨著終端設(shè)備的更新和網(wǎng)絡(luò)技術(shù)的進(jìn)步,移動互聯(lián)網(wǎng)上的業(yè)務(wù)和應(yīng)用也在不斷的發(fā)展,手機(jī)閱讀就是其中發(fā)展較快的一種。雖然手機(jī)閱讀的用戶基礎(chǔ)好、市場潛力大,但目前仍舊缺乏清晰的盈利模式,用戶付費意愿不強,造成手機(jī)閱讀業(yè)務(wù)收入不高的現(xiàn)狀。本文用人類動力學(xué)的理論和方法研究手機(jī)在線用戶的行為特征,分析影響其閱讀行為的主要因素,并且針對性的提出利于手機(jī)在線閱讀發(fā)展的合理化建議。 基于手機(jī)在線閱讀用戶行為的數(shù)據(jù)統(tǒng)計,發(fā)現(xiàn)用戶的行為除了具有周期性、相關(guān)性等基本特征之外,其胖尾特征也十分明顯,無論是從讀者還是作品的角度分析,評論時間間隔分布均可以用冪律函數(shù)很好的刻畫。分布的冪指數(shù)會因用戶的活躍度、作品的狀態(tài)等方面的不同而存在差異,用戶活躍度越高,其冪指數(shù)越大,相對于完結(jié)作品,連載作品更能夠引發(fā)頻繁的評論,而用戶不會因為作品收費而減少對它的評論或點擊,說明對于用戶來說,能吸引他們的往往是質(zhì)量高、更新快的作品,“免費的午餐”不能賺取關(guān)注度。 用戶行為的這些特征主要是由其興趣變化引起的,用戶的興趣會隨時間推移慢慢衰減,但有可能因偶然事件的發(fā)生而突然回升,同時用戶行為還會受作者的行為、網(wǎng)站的經(jīng)營模式等因素的影響。據(jù)此建立人類動力學(xué)模型,仿真重現(xiàn)用戶行為的主要特征,通過與實際數(shù)據(jù)的分析結(jié)果對比,驗證了該模型能夠比較準(zhǔn)確的反應(yīng)手機(jī)在線閱讀用戶的行為特征。通過模型優(yōu)化和參數(shù)調(diào)整,發(fā)現(xiàn)作者加快其更新作品的頻率或者網(wǎng)站采取個性化推薦的方式都可以增加用戶的關(guān)注程度,因此建議網(wǎng)站優(yōu)化推薦方式,并邀約高水平的寫手入駐。
[Abstract]:With the update of the terminal equipment and the progress of the network technology, the business and application on the mobile Internet are developing constantly, and the mobile phone reading is one of them. Although the mobile phone reading user base is good, the market potential is big, but at present still lacks the clear profit pattern, the user pays the will is not strong, causes the handset reading service income not to be high the present situation. In this paper, we use the theory and method of human dynamics to study the behavior characteristics of mobile phone online users, analyze the main factors that affect their reading behavior, and put forward some reasonable suggestions for the development of mobile phone online reading. Based on the statistics of mobile phone online reading user behavior, it is found that in addition to the periodicity, correlation and other basic characteristics of user behavior, its fat-tailed features are also very obvious, whether from the perspective of readers or works. The distribution of comment time interval can be well characterized by power law function. The power exponent of the distribution will vary according to the user's activity, the state of the work, etc. The higher the user's activity, the greater the power exponent. Compared with the finished work, serial works are more likely to trigger frequent comments. The fact that users don't comment or click on a work for a fee means that it's often high quality, fast-updated works that appeal to users, and "free lunches" don't earn a lot of attention. These characteristics of user behavior are mainly caused by changes in their interests, which slowly attenuate over time, but may suddenly pick up as a result of accidental events, while user behavior is also subject to the behavior of the author. Website business model and other factors. Based on this, the human dynamics model is established, and the main characteristics of user behavior are simulated and reproduced. By comparing with the analysis results of actual data, it is verified that the model can accurately reflect the behavior characteristics of mobile phone online reading users. Through model optimization and parameter adjustment, it is found that the author can increase the attention of the user by speeding up the frequency of updating his work or the website adopting personalized recommendation, so it is suggested that the website should optimize the recommendation mode. And invite a high level of writers to enter.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：C912.6

【引證文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 李凱凱;用戶行為記憶性及其驅(qū)動機(jī)制研究[D];中北大學(xué);2017年

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本文編號：1982088