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The complexity and diversity of today's media landscape provides many challenges for scholars studying online news consumption. Yet it is unclear how news consumers navigate online. Moving forward, we used a custom-built browser plug-in-passively tracking Dutch online news consumers 24/7-to examine how context (website) and content (news topic) features affect patterns of online news consumption. This resulted in a data set containing more than one million Web pages, from 175 websites (news websites, search engines, social media), collected over 8 months in 2017/18. We used automated content analysis to retrieve news topics, and estimated Markov chains to detect consumption patterns. Our findings indicate that news consumers often directly visit their favorite (typically mainstream) news outlet, and continue browsing within that outlet. We also found a strong preference for entertainment news over any other topic. Although social media often offer entertainment news, they are not necessarily the starting point to such news.

In recent years, the volume of clickstream and user data collected by news organizations has reached enormous proportions. As a result, news organizations-as well as journalism scholars-face novel methodological challenges to describe and analyze this wealth of information. To move forward, we demonstrate a computational approach to understand the news journeys Web users take to find the news they want to read. We propose the use of Markov chains. These models provide an effective and compact way to discover meaningful patterns in clickstream data. In particular, they capture the sequentiality in news use patterns. We illustrate this approach with an analysis of more than 1 million Web pages, from 175 websites (news websites, search engines, social media), collected over 8 months in 2017/18. The analysis of such data is of high interest to journalism scholars, but can also help news organizations to design sales strategies, provide more personalized content, and find the most effective structure for their website.

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With an increasing number of people, especially adolescents, using more private online platforms, such as WhatsApp, for news, an important question for democracy is whether such platforms can facilitate learning about politics and current events. In this study, we examine adolescents’ affective (emotions, feelings), behavioral (actions and behavioral intentions), and cognitive (political knowledge) responses to interpersonal political discussion on WhatsApp. We conducted a preregistered field experiment at six secondary schools in the Netherlands ( N = 230). We assigned respondents with strong ties to a WhatsApp group. For seven days, respondents received a link to an online political news item on a daily basis; and (1) either had to read or (2) read and discuss it. The results indicate that interpersonal discussion evokes stronger positive emotions and feelings, as well as issue-specific knowledge. In addition, elaboration on the content of political discussion was positively related to issue-specific knowledge. In this way, instant messaging apps may serve as a resource for engaging adolescents with politics and current events.