Are we human, or are we users? The role of natural language processing in human-centric news recommenders that nudge users to diverse content

Proceedings of the 1st Workshop on NLP for Positive Impact Pub Date : 1900-01-01 DOI:10.18653/v1/2021.nlp4posimpact-1.6

Myrthe Reuver, Nicolas Mattis, M. Sax, S. Verberne, N. Tintarev, N. Helberger, Judith Moeller, Sanne Vrijenhoek, Antske Fokkens, Wouter van Atteveldt

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引用次数: 4

Abstract

In this position paper, we present a research agenda and ideas for facilitating exposure to diverse viewpoints in news recommendation. Recommending news from diverse viewpoints is important to prevent potential filter bubble effects in news consumption, and stimulate a healthy democratic debate.To account for the complexity that is inherent to humans as citizens in a democracy, we anticipate (among others) individual-level differences in acceptance of diversity. We connect this idea to techniques in Natural Language Processing, where distributional language models would allow us to place different users and news articles in a multidimensional space based on semantic content, where diversity is operationalized as distance and variance. In this way, we can model individual “latitudes of diversity” for different users, and thus personalize viewpoint diversity in support of a healthy public debate. In addition, we identify technical, ethical and conceptual issues related to our presented ideas. Our investigation describes how NLP can play a central role in diversifying news recommendations.

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我们是人类，还是用户?自然语言处理在以人为中心的新闻推荐中的作用，将用户推送到不同的内容

在这个立场文件中，我们提出了一个研究议程和想法，以促进新闻推荐中不同观点的暴露。从不同的角度推荐新闻，对于防止新闻消费中潜在的过滤泡沫效应，以及激发健康的民主辩论非常重要。为了解释作为民主国家公民的人类所固有的复杂性，我们预计(除其他外)个体在接受多样性方面的差异。我们将这个想法与自然语言处理中的技术联系起来，其中分布式语言模型将允许我们将不同的用户和新闻文章放置在基于语义内容的多维空间中，其中多样性被操作为距离和方差。通过这种方式，我们可以为不同的用户建立个体“多样性纬度”模型，从而个性化观点多样性，以支持健康的公共辩论。此外，我们还确定了与我们提出的想法相关的技术、伦理和概念问题。我们的调查描述了NLP如何在多样化的新闻推荐中发挥核心作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 1st Workshop on NLP for Positive Impact

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