论文部分内容阅读
在2016年美国大选中,由于算法控制,脸书用户通常看到的推送信息是与自己想法接近的观点。这解释了为什么很多人在大选结果揭晓时备感突然,毫无准备。网络行动主义者埃利·帕利瑟在其著作《过滤泡泡》中认为“过滤泡泡”的算法限制,一方面使得数据呈现方式极度个人化,另一方面用户将很难看到冲突性的观点。乔治·华盛顿大学的媒介研究学者尼科·莱塞对此也不无担忧,认为“过滤泡泡”将大众传播转化为大众化的自我传播,其数据质量大为可疑。
In the 2016 US presidential election, the push messages that Facebook users typically see due to algorithmic controls are close to their own beliefs. This explains why many people are suddenly and unprepared for the outcome of the election. Network activist Elly Palisser, in his book Filtering Bubbles, argues that the algorithmic limitations of “bubble-blowing” make the data presentation extremely personal, and on the other hand users will find it hard to see the conflict Sexual point of view. Nicole Reese, a media research scholar at George Washington University, is equally concerned about this as “filtering bubbles” that transform mass media into mass self-media whose quality of data is suspicious.