BURST OF THE FILTER BUBBLE? Effects of personalization on the diversity of Google News
BURST OF THE FILTER BUBBLE? Effects of personalization on the diversity of Google News
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DOI：
10.1080/21670811.2017.1338145
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发表时间：
2018-01-01
影响因子：
5.4
通讯作者：
Brosius, Hans-Bernd
中科院分区：
文献类型：
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作者：
Haim, Mario;Graefe, Andreas;Brosius, Hans-Bernd
在提供面向用户个人兴趣的个性化内容时，推荐器系统被认为会降低新闻多样性，从而导致部分信息盲目(即过滤气泡)。我们进行了两项探索性研究，以检验内隐和外显个性化对谷歌新闻内容和来源多样性的影响。除了内隐个性化对内容多样性的微小影响外，我们没有发现对过滤气泡假说的支持。然而，我们确实发现了一种普遍的偏见，即谷歌新闻过多地代表了某些新闻机构，而低估了其他频繁访问的新闻机构。这一结果增加了越来越多的证据，这些证据表明，对在线新闻背景下的算法过滤泡沫的担忧可能被夸大了。
In offering personalized content geared toward users' individual interests, recommender systems are assumed to reduce news diversity and thus lead to partial information blindness (i.e., filter bubbles). We conducted two exploratory studies to test the effect of both implicit and explicit personalization on the content and source diversity of Google News. Except for small effects of implicit personalization on content diversity, we found no support for the filter-bubble hypothesis. We did, however, find a general bias in that Google News over-represents certain news outlets and under-represents other, highly frequented, news outlets. The results add to a growing body of evidence, which suggests that concerns about algorithmic filter bubbles in the context of online news might be exaggerated.