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长尾理论视阈的知识分享变现条件分析

Analysis on the Realization Condition of Knowledge Sharing in the Perspective of Long Tail Theory

【作者】 杨静

【导师】 陈堂发;

【作者基本信息】 南京大学 , 新闻与传播(专业学位), 2017, 硕士

【副题名】以果壳、知乎付费问答模式为例

【摘要】 2016年被称为知识付费元年,分答、在行、知乎等众多知识分享平台纷纷进行了知识分享变现的尝试,通过付费问答的模式在市场上进行商业化探索,依托互联网知识分享平台,拥有无限广阔的商品售卖"货架"以及极为丰富的知识产品品类,能够满足消费者的个性化消费需求。这种"长尾"的特性成为付费问答模式实现知识分享变现的重要条件。本文从长尾理论视角深入探讨知识分享变现问题,用长尾理论的生产、传播、连接生产与消费三个关键环节具体分析知识分享长尾市场变现的发生条件、付费问答模式在实际运营过程中的长尾思维表现以及在长尾理论视角下这一变现模式存在的问题,最后根据长尾理论思维提出了一些对策思考,以期为今后相关领域的研究提供一些思路借鉴,为知识分享变现的发展做出一些理论上的指导。具体来说,网络技术发展降低了知识分享长尾内容生产边际成本,海量认知盈余增加了知识分享长尾品类。这两个因素保证了知识分享的内容长尾和需求长尾,为长尾经济的发生打下了基础;小众传播的兴起促进知识长尾信息圈层传播、便捷支付方便消费者快速获取知识长尾、专业化知识分享平台作为知识分享长尾的集合器,共同促进知识分享长尾产品的易被发现和易被购买,有效促进了知识分享长尾的消费;付费和问答成为优质知识长尾过滤器、知识焦虑刺激了消费者的知识需求长尾、个性化消费促使需求方规模经济产生、分享经济的发展助力知识分享长尾市场崛起,这几个因素将知识分享长尾的生产与消费连接了起来,有效促进了消费者对知识分享长尾的消费和继续探索长尾的尾部市场。在实际业务操作层面,分答、在行、知乎三个知识分享平台的许多运营细节,如标签分类,页面展现,定价策略等也体现出了对长尾理论的运用。最后,本论文认为这一知识分享变现模式在市场发展过程中也存在知识分享长尾品类有限、传播断层和精准匹配度低的问题。因此,可以通过加强平台外部资源合作、建设用户交流社区、加强智能算法相关推荐等手段来解决这些问题。

【Abstract】 2016 is known as the first year of knowledge payment.Guokr,zhihu,zaihang and so many knowledge sharing platforms have carried out the knowledge sharing to realize the attempt,through the paid Q&A model in the market for commercial exploration.They rely on the Internet knowledge sharing platform,with unlimited sales of goods "shelves" and a very rich category of intellectual products,to meet the consumer’s personalized consumer demand.This "long tail" of the characteristics of the paid Q&A model to achieve the important conditions for the realization of knowledge sharing.This paper explores the realization of knowledge sharing from the perspective of long tail theory.This paper analyzes the occurrence conditions of the long-tail market of knowledge sharing,the long-tail performance of the paid Q&A pattern in the actual operation process and the problems existing in this realization mode by using the long-tail theory of production,communication,connection production and consumption.Finally,some countermeasures are put forward according to the theory of long tail,so as to provide some ideas for future research in related fields and make some theoretical guidance for the development of knowledge sharing.Specifically,the development of network technology reduces the marginal cost of knowledge sharing long tail content,and the massive cognitive surplus increases the knowledge sharing long tail.These two factors to ensure the content of the knowledge to share the long tail and long tail,for the long tail of the economy laid the foundation;the rise of small public communication to promote the knowledge of the long-tailed information circle spread,easy to pay to facilitate the rapid acquisition of knowledge of consumers long tail,professional knowledge sharing platform as a knowledge to share the long tail of the assembly,to promote knowledge sharing long tail products are easy to find And easy to be purchased,effectively promoting the knowledge to share the long tail of consumption;payment and Q&A to become a high-quality knowledge of long tail filter,knowledge anxiety to stimulate the consumer’s knowledge needs long tail,personalized consumption to promote the demand side economies of scale,share the economic development of knowledge to share the long tail market rise,these factors will Knowledge sharing long tail production and consumption linked up,effectively promote the consumer to share the knowledge of the long tail of the knowledge and continue to explore the tail of the tail market.In the actual business operation level,the answer,in line,know the three knowledge sharing platform,many operational details,such as label classification,page display,pricing strategy also reflects the use of long tail theory.Finally,this paper argues that this knowledge-sharing realization model also has the problem of limited knowledge-sharing long-tailed category,propagation fault and low precision matching in the process of market development.Therefore,these issues can be solved by strengthening the platform external resources cooperation,building user exchange community,strengthening the relevant recommendation of intelligent algorithm and so on.

  • 【网络出版投稿人】 南京大学
  • 【网络出版年期】2018年 02期
  • 【分类号】G206
  • 【被引频次】28
  • 【下载频次】2428
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