Is sharing just a function of viewing? The sharing of political and non-political news on Facebook

Abstract

How is political news shared online? This fundamental question for political communication research in today’s news ecology is still poorly understood. In particular, very little is known about whether and how news sharing differs from news viewing. Based on a unique dataset of ≈ 870,000 URLs shared ≈ 100 million times on Facebook, grouped by countries, age brackets, and months, we study the correlates of viewing versus sharing of political versus non-political news. We first identify websites that at least occasionally contain news items, and then analyze metrics of the news items published on these websites. We enrich the dataset with natural language processing and super- vised machine learning. We find that political news items are viewed less than non-political news items, but are shared more than one would expect based on their views. Furthermore, the source of a news item and textual features, which are often studied in clickbait research and in commercial A/B testing, matter. Our findings are conditional on age, but are very similar across four different countries (Italy, Germany, Netherlands, Poland). While our research design does not allow for causal claims, our findings suggest that future work is well-advised to both theoretically and methodologically differentiate between factors that may explain (a) viewing versus sharing of news, and (b) political versus non-political news.

Algorithmic Curation. Encyclopedia of Political Communication.

“…Unlike algorithmic exposure, which refers to the mere presentation of content to users, algorithmic curation involves a more active selection and arrangement of information tailored to individual preferences and interests (Bandy & Diakopoulos, 2021;Gausen et al, 2022;Jürgens & Stark, 2022;Swart, 2021). Algorithmic curation operates on the principle of filtering and prioritizing content based on various factors such as relevance, popularity, and user behavior (Shin et al, 2023;Trilling et al, 2022). By leveraging vast amounts of data, algorithms aim to deliver personalized experiences to users, offering them content that aligns with their preferences and keeping them engaged based on their past behavior, interests, and demographic characteristics.…”

Diversity of News Consumption in a Digital Information Environment

“…Another factor to consider is the general audience reach of outlets (e.g. only considering popular outlets; Stier, Breuer, et al, 2020;Trilling et al, 2022;Wojcieszak, de Leeuw, et al, 2021). However, this should involve discussions on whether sources with a small reach (e.g., small websites or TV stations) should be part of the population, depending on the particular research interest.…”