We appreciate the chance to respond to Webster and Taneja’s comments to our article (Mukerjee, Majó-Vázquez, & González-Bailón, 2018). We take this as a welcome opportunity to engage in the always-pertinent discussion on why measurement and methods are so important to reach meaningful theoretical conclusions from empirical work. For the sake of transparency, we would like to begin by stating that we sent the manuscript of our article to Webster and Taneja at the same time we submitted it for review to the Journal of Communication (back in May 2017), asking for comments or clarifications in case we had misinterpreted their analyses or findings. Both authors amiably acknowledged receipt, but they never sent us any written feedback until we received their response from the editor (March 2018), after the article was published. We would also like to state that, in our article, we acknowledge what we genuinely think is an important contribution: Webster and Taneja’s work is amongst the first to apply network methods to the analysis of audience data. As we write in page 30, this past research “shows that the analysis of audience overlap data can offer relevant insights on exposure to information and media diets” and that the “network analysis of audience behavior can offer a powerful methodological approach to uncover the characteristics of media diets and the venues where audiences concentrate more clearly.” However, having carefully read their response, we still stand by the three main claims we make in our article: (a) that their past work does not offer a satisfactory benchmark to assess significant overlap between outlets that are very different in reach; (b) that disregarding the strength of the overlap misses crucial information when analyzing audience networks; and (c) that once overlap strength is taken into account, the conclusions that can be drawn from the analysis of audience networks are not consistent with the idea of a “massive overlap culture.”

中文翻译：

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回应韦伯斯特和塔内贾对“数字新闻消费中受众网络重叠”的回应

我们很高兴有机会回复 Webster 和 Taneja 对我们文章的评论（Mukerjee、Majó-Vázquez 和 González-Bailón，2018 年）。我们将此视为一个受欢迎的机会，就为什么测量和方法对于从实证工作中得出有意义的理论结论如此重要进行始终相关的讨论。为透明起见，我们首先声明，我们将文章手稿发送给 Webster 和 Taneja，同时我们将其提交给 Journal of Communication（早在 2017 年 5 月）进行审查，征求意见或澄清，以防我们误解了他们的分析或发现。两位作者和蔼可亲地承认收到，但他们从未给我们发送任何书面反馈，直到我们在文章发表后收到编辑的回复（2018 年 3 月）。我们还想声明，在我们的文章中，我们承认我们真正认为的一项重要贡献：Webster 和 Taneja 的工作是最早将网络方法应用于受众数据分析的工作之一。正如我们在第 30 页中所写，这项过去的研究“表明，对受众重叠数据的分析可以提供有关接触信息和媒体饮食的相关见解”，并且“受众行为的网络分析可以提供一种强大的方法论方法来揭示特征媒体饮食和观众更清晰地集中注意力的场所。” 然而，仔细阅读他们的回应后，我们仍然支持我们在文章中提出的三个主要主张：(a) 他们过去的工作没有提供令人满意的基准来评估覆盖范围非常不同的网点之间的显着重叠；(b) 在分析受众网络时，忽视重叠的强度会遗漏关键信息；(c) 一旦考虑到重叠强度，从受众网络分析中得出的结论与“大规模重叠文化”的想法不一致。