社會(huì)化媒體中提升用戶參與度的關(guān)鍵因素研究
發(fā)布時(shí)間：2018-10-14 13:33
【摘要】：短短幾年間，社會(huì)化媒體得到了迅猛的發(fā)展，用戶數(shù)量和覆蓋率不斷刷新記錄，在社會(huì)生活中的地位和作用日漸重要。社會(huì)化媒體的核心是“社會(huì)化”，即用戶的參與和互動(dòng)。可以說，社會(huì)化媒體的根本價(jià)值來自用戶參與的廣泛性與互動(dòng)性，參與度的低迷將直接導(dǎo)致用戶的流失和平臺(tái)本身的沒落。而只有從理論上和本質(zhì)上深刻影響用戶參與的因素，才能為社會(huì)化媒體的實(shí)際應(yīng)用如推薦和搜索提供有意義的指導(dǎo)。 本文從多角度展開了對(duì)社會(huì)化媒體用戶參與度的研究。首先，需要避免千遍一律的枯燥和雷同，單一的內(nèi)容會(huì)讓用戶乏味而離開，即需要保證多樣性；其次，僅有多樣性是不夠的，必須同時(shí)保證內(nèi)容的相關(guān)性和有用性，讓用戶收獲意料之外的發(fā)現(xiàn)，即在多樣性之上為用戶帶來眼前一亮的意外驚喜；最后，考慮到多樣性和意外驚喜僅提升了用戶個(gè)體層面的體驗(yàn)，應(yīng)該繼續(xù)挖掘用戶關(guān)系，在網(wǎng)絡(luò)層面上激發(fā)更多互動(dòng)和共鳴，實(shí)現(xiàn)廣泛的信息傳播，由此，本文進(jìn)一步對(duì)用戶之間的影響關(guān)系進(jìn)行深入挖掘以最大化整體參與度。對(duì)于以上激勵(lì)用戶參與的三個(gè)重要因素—多樣性、意外驚喜和影響關(guān)系，本文分別展開了以下深入研究。 在多樣性與參與度的研究上，以微博為例，本文對(duì)社會(huì)化媒體用戶的個(gè)體網(wǎng)絡(luò)和所讀內(nèi)容的多樣性進(jìn)行了實(shí)證研究。首先，使用四種不同的度量方法量化了多樣性；之后，對(duì)多樣性進(jìn)行了時(shí)序分析，發(fā)現(xiàn)了微博用戶的多樣性隨著時(shí)間增長；最后，考察了多樣性與用戶參與度的關(guān)系，實(shí)驗(yàn)發(fā)現(xiàn)：結(jié)構(gòu)層面的多樣性與原創(chuàng)數(shù)量顯著正相關(guān)，而內(nèi)容層面的多樣性則對(duì)原創(chuàng)數(shù)量沒有太大影響，這說明平臺(tái)應(yīng)該有意識(shí)地引導(dǎo)用戶加入多個(gè)不同的圈子；不同度量方式下，轉(zhuǎn)發(fā)數(shù)都隨著多樣性的增長而增長，這說明在平臺(tái)設(shè)計(jì)中加入多樣性元素能有效提升用戶的參與度。 在意外驚喜與參與度的研究上，本文首次對(duì)意外驚喜現(xiàn)象進(jìn)行了基于大規(guī)模用戶行為數(shù)據(jù)的量化研究，提出了一種識(shí)別意外驚喜的高效算法，并計(jì)算了意外驚喜在社會(huì)化媒體中的存在比例，揭示了其對(duì)用戶參與度的正面作用。意外驚喜指的是一種非預(yù)期的收獲或無意中的發(fā)現(xiàn)，其在信息系統(tǒng)中對(duì)用戶體驗(yàn)和用戶參與的積極作用已得到了學(xué)術(shù)界和工業(yè)界的普遍認(rèn)同，但這種作用仍缺乏由大規(guī)模數(shù)據(jù)下的理論研究支持。本文定義社會(huì)化媒體中的意外驚喜為“意外的相關(guān)性”。在該定義下，基于統(tǒng)計(jì)假設(shè)檢驗(yàn)，本文提出了一種全新的方法來自動(dòng)、快速、準(zhǔn)確識(shí)別信息傳播中的意外性、相關(guān)性和意外驚喜，該方法適用于多種信息系統(tǒng)，如推薦系統(tǒng)、檢索系統(tǒng)和廣告平臺(tái)。使用該識(shí)別方法，本文計(jì)算了意外驚喜在微博信息傳播中的存在比例，在Twitter的轉(zhuǎn)發(fā)中約占27%，在新浪微博的轉(zhuǎn)發(fā)中約占30%。最后，通過相關(guān)關(guān)系分析和因果關(guān)系分析，本文揭示了意外驚喜對(duì)社會(huì)化媒體中用戶參與度（活躍度和社交度）的正面作用。 在影響關(guān)系與參與度的研究上，本文利用影響關(guān)系提升社會(huì)化媒體的整體參與度，抽象并公式化了參與度最大化問題。為了解決此問題，首先，通過隨機(jī)測試驗(yàn)證了影響關(guān)系對(duì)用戶參與行為的驅(qū)動(dòng)作用；其次，提出了一種迭代算法，根據(jù)用戶歷史交互數(shù)據(jù)計(jì)算用戶之間的影響關(guān)系；最后，針對(duì)參與度最大化問題，提出了一種高效的啟發(fā)式算法TABI，實(shí)驗(yàn)顯示該算法在整體參與度的提升上，，性能顯著優(yōu)于推薦算法和社會(huì)財(cái)富最大化問題的近似算法�；谟绊戧P(guān)系的參與度最大化是推薦系統(tǒng)新思路的一種探索，即出于提升整體參與度的考慮，在推薦中不僅需要匹配當(dāng)前用戶的興趣，還需要考慮當(dāng)前用戶影響力帶來的未來參與度。 綜上所述，本文深入研究了提高社會(huì)化媒體用戶參與度的三個(gè)關(guān)鍵因素：多樣性、意外驚喜和影響關(guān)系。實(shí)驗(yàn)結(jié)果表明，以上三個(gè)因素均對(duì)用戶參與度均產(chǎn)生積極作用。因此，在實(shí)際應(yīng)用和系統(tǒng)設(shè)計(jì)中，可以借鑒本文提出的算法、技術(shù)和框架，在信息內(nèi)容和用戶關(guān)系兩個(gè)層面為用戶帶來更好的用戶體驗(yàn)，從而有效提升社會(huì)化媒體的互動(dòng)程度和參與程度。
[Abstract]:In just a few years, the social media has developed rapidly, the number of users and the coverage rate are constantly being recorded, and the status and role of social life become more and more important. The core of social media is" Socialization "i.e. the user's participation and interaction. It can be said that the basic value of social media comes from the extensive and interactive participation of users, and the downturn of participation will directly affect the loss of users and the loss of the platform itself. Only the factors that profoundly affect the user's participation in theory and nature can provide meaningful guidance for the practical application of social media, such as recommendation and search. In this paper, we expand the participation of social media users from various angles Research. First, there is a need to avoid the boring and thunder of thousands of times, the single content will make the user dull and leave, that is, need to ensure diversity; secondly, only the diversity is not enough, must ensure the relevance and usefulness of the content at the same time, let the user harvest unexpected It has been found that, on the basis of diversity, the user brings an unexpected surprise to the user; finally, taking into account the diversity and unexpected surprise only improves the experience of the individual level of the user, the user relationship should continue to be mined, more interaction and resonance can be stimulated at the network level, and wide information transmission can be realized, Therefore, the relationship between users is further explored in this paper to maximize the whole parameter. With respect to the three important factors, such as diversity, surprise and influence of the above incentive users, this paper respectively expands the following in depth: In this paper, the diversity and the diversity of the individual network and the content of the social media users are studied in the research of diversity and participation. Firstly, the diversity is quantified by four different measurement methods, then the diversity is analyzed in time series, and the diversity of micro-Bo users is found to grow with time. Finally, the relationship between diversity and user participation is investigated. The experiment shows that the diversity of the structure level is positively correlated with the original quantity, while the diversity of the content level has little influence on the original quantity, which means that the platform should consciously guide the user into a plurality of different circles; in different measures, the number of forwarding is varied with diversity. Growth, which suggests that the addition of diversity elements in the platform design can be effectively improved In the research of surprise and participation, this paper makes a quantitative study on unexpected surprises based on large-scale user behavior data for the first time, and presents an efficient algorithm for identifying unexpected surprises, and calculates unexpected surprises in socialization. the presence scale in the media reveals its access to the user, Positive role of engagement. Unexpected surprise refers to a non-expected harvest or unintended discovery that has been universally recognized by academia and industry in the information system, but this role is still lacking in large-scale data The next theoretical research support. This paper defines socialization. Unexpected surprises in the media To Under this definition, based on statistical hypothesis testing, this paper proposes a new method to automatically, quickly and accurately identify the accident, correlation and unexpected surprises in information propagation, which is suitable for various information systems, such as recommendation system and inspection. Cable system and advertising platform. Using this recognition method, this paper calculates the proportion of unexpected surprises in micro-bo information propagation, accounting for about 27% of Twitter's forwarding, Finally, through correlation analysis and causality analysis, this paper reveals the users' participation (activity and society) in social media by surprise surprise. On the research of influence relation and participation, this paper uses influence relation to promote the whole engagement of social media, abstract and public. In order to solve this problem, in order to solve this problem, firstly, the driving effect of the influence relation on the user's participation behavior is verified through the random test; secondly, an iterative algorithm is proposed to calculate the influence relation among users according to the user history interactive data; and finally, an iterative algorithm is proposed. In view of the maximization of engagement, an efficient heuristic algorithm is presented in this paper. The experiment shows that the algorithm is superior to the recommendation algorithm and social wealth in the improvement of the overall engagement. In the recommendation, not only needs to match the interest of the current user, but also needs to take into account the current user. In conclusion, this paper deeply studies the three key factors to improve the participation of social media users. Diversity, surprise and impact. The experimental results show that the above three factors Therefore, in the practical application and the system design, the algorithm, technology and framework proposed in this paper can be used for the user to bring a better user experience at both the information content and the user relation, thus effectively improving the society.
【學(xué)位授予單位】：北京大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP391.3
本文編號(hào)：2270619
[Abstract]:In just a few years, the social media has developed rapidly, the number of users and the coverage rate are constantly being recorded, and the status and role of social life become more and more important. The core of social media is" Socialization "i.e. the user's participation and interaction. It can be said that the basic value of social media comes from the extensive and interactive participation of users, and the downturn of participation will directly affect the loss of users and the loss of the platform itself. Only the factors that profoundly affect the user's participation in theory and nature can provide meaningful guidance for the practical application of social media, such as recommendation and search. In this paper, we expand the participation of social media users from various angles Research. First, there is a need to avoid the boring and thunder of thousands of times, the single content will make the user dull and leave, that is, need to ensure diversity; secondly, only the diversity is not enough, must ensure the relevance and usefulness of the content at the same time, let the user harvest unexpected It has been found that, on the basis of diversity, the user brings an unexpected surprise to the user; finally, taking into account the diversity and unexpected surprise only improves the experience of the individual level of the user, the user relationship should continue to be mined, more interaction and resonance can be stimulated at the network level, and wide information transmission can be realized, Therefore, the relationship between users is further explored in this paper to maximize the whole parameter. With respect to the three important factors, such as diversity, surprise and influence of the above incentive users, this paper respectively expands the following in depth: In this paper, the diversity and the diversity of the individual network and the content of the social media users are studied in the research of diversity and participation. Firstly, the diversity is quantified by four different measurement methods, then the diversity is analyzed in time series, and the diversity of micro-Bo users is found to grow with time. Finally, the relationship between diversity and user participation is investigated. The experiment shows that the diversity of the structure level is positively correlated with the original quantity, while the diversity of the content level has little influence on the original quantity, which means that the platform should consciously guide the user into a plurality of different circles; in different measures, the number of forwarding is varied with diversity. Growth, which suggests that the addition of diversity elements in the platform design can be effectively improved In the research of surprise and participation, this paper makes a quantitative study on unexpected surprises based on large-scale user behavior data for the first time, and presents an efficient algorithm for identifying unexpected surprises, and calculates unexpected surprises in socialization. the presence scale in the media reveals its access to the user, Positive role of engagement. Unexpected surprise refers to a non-expected harvest or unintended discovery that has been universally recognized by academia and industry in the information system, but this role is still lacking in large-scale data The next theoretical research support. This paper defines socialization. Unexpected surprises in the media To Under this definition, based on statistical hypothesis testing, this paper proposes a new method to automatically, quickly and accurately identify the accident, correlation and unexpected surprises in information propagation, which is suitable for various information systems, such as recommendation system and inspection. Cable system and advertising platform. Using this recognition method, this paper calculates the proportion of unexpected surprises in micro-bo information propagation, accounting for about 27% of Twitter's forwarding, Finally, through correlation analysis and causality analysis, this paper reveals the users' participation (activity and society) in social media by surprise surprise. On the research of influence relation and participation, this paper uses influence relation to promote the whole engagement of social media, abstract and public. In order to solve this problem, in order to solve this problem, firstly, the driving effect of the influence relation on the user's participation behavior is verified through the random test; secondly, an iterative algorithm is proposed to calculate the influence relation among users according to the user history interactive data; and finally, an iterative algorithm is proposed. In view of the maximization of engagement, an efficient heuristic algorithm is presented in this paper. The experiment shows that the algorithm is superior to the recommendation algorithm and social wealth in the improvement of the overall engagement. In the recommendation, not only needs to match the interest of the current user, but also needs to take into account the current user. In conclusion, this paper deeply studies the three key factors to improve the participation of social media users. Diversity, surprise and impact. The experimental results show that the above three factors Therefore, in the practical application and the system design, the algorithm, technology and framework proposed in this paper can be used for the user to bring a better user experience at both the information content and the user relation, thus effectively improving the society.
【學(xué)位授予單位】：北京大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP391.3
【引證文獻(xiàn)】
相關(guān)期刊論文 前1條
1 朱長春;李娜;;社會(huì)化媒體技術(shù)在大學(xué)教學(xué)中的實(shí)踐應(yīng)用研究[J];經(jīng)濟(jì)視角(下);2013年12期
本文編號(hào)：2270619
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