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在线阅读 --哲学社会科学版 2020年6期《内容推荐传播的效能与启示——基于一次算法驱动的实验研究》
内容推荐传播的效能与启示——基于一次算法驱动的实验研究--[在线阅读]
刘雪梅, 黄玉凤
广州大学 新闻与传播学院, 广东 广州 510006
起止页码: 112--119页
DOI: 10.13763/j.cnki.jhebnu.psse.2020.06.015
摘要
为了研究网络信息的推荐传播现象,有必要在文献回顾的基础上构建一个内容推荐模型。在此算法实验中可以察觉,尽管内容推荐对受众产生明确显著的影响,然而它对受众行为发生误判的几率也不容忽视,而且其在信息偏食者和其他用户的平衡上同样存在技术漏洞。此外,算法是否中性,网络用户是否会被算法接管,算法对集体注意力的贡献以及算法与传播环境的关系,这四个方面的问题仍有待给出进一步的思考,从中可以发现,尽管内容推荐传播是一种信息获取的升级,但还需要更多实践的检验与反馈。
关键字: 算法 内容推荐 传播

Efficiency and Inspiration of Information Pushing—Based on an Experimental Study Driven by Algorithm
LIU Xuemei, HUANG Yufeng
School of Journalism and Communication, Guangzhou University, Guangzhou Guangdong 510006, China
Abstract:
To investigate the pushing mechanism of information on cyber communication, the author constructed a model of pushing behavior based on literature view. In the algorithm experiment, it was observed that although information pushing had a clear and remarkable impact on the receivers, the probability of misjudgment of receiver behavior should not be ignored, and there were also technical loopholes in the balance between picky information receivers and other users. In addition, algorithm neutrality, the dominance of algorithm over network users, the contribution of the algorithm to collective attention and the relationship between the algorithm and the communication environment need further consideration. It is concluded that although information pushing is an upgrade of information acquisition, it still needs more practical test and feedback.

收稿日期: 2020-07-15
基金项目: 教育部哲学社会科学一般项目“数据驱动的网络大电影用户画像研究”(项目编号:19YJA760038)

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