How Does the Adoption of Ad Blockers Affect News Consumption? (with Klaus M. Miller & Bernd Skiera)
- R&R, Journal of Marketing Research
Abstract: Ad blockers allow users to browse websites without viewing ads. Online news providers that rely on advertising revenue tend to perceive users’ adoption of ad blockers purely as a threat to revenue. Yet, this perception ignores the possibility that avoiding ads—which users presumably dislike—may affect users’ online news consumption behavior in positive ways. Using 3.1 million anonymized visits from 79,856 registered users on a news website, we find that adopting an ad blocker has a robust positive effect on the quantity and variety of articles users consume (21.5% -43.3% more articles and 13.4% -29.1% more content categories). An increase in repeat user visits of the news website, rather than the number of page impressions per visit, drives the news consumption. These visits tend to start with direct navigation to the news website, indicating user loyalty. The increase in news consumption is more substantial for users who have less prior experience with the website. We discuss how news publishers could benefit from these findings, including exploring revenue models that consider users’ desire to avoid ads.
Paywall and Content Polarization
- Presented at Statistical Challenges in Electronic Commerce Research (SCECR) 2020, Workshop on Information System and Economics (WISE) 2020, INFORMS Marketing Science Conference 2021, the European Marketing Academy Conference 2021
Abstract: News media connects and charges two groups of users — advertisers and news readers — and thus it is always considered as a two-sided market. Theoretical work on two-sided market predicts that financing content by subscription results in maximum content differentiation à la Hotelling because publishers need to soften the price competition by capturing more value from readers with higher willingness to pay. Empirical evidence on this prediction is lacking. This paper studies how a news publisher’s decision to finance content by subscription through a paywall (as opposed to advertising) impacts the extent to which the publisher’s content is politically polarized (i.e., right- or left-leaning). I analyze 620,950 news articles from the four largest news media channels in the US, published over the course of 3 years. To quantify articles’ polarization levels—as well as the polarization levels of the journalists who wrote the articles—I use a novel polarization index trained on speeches from US Congress. This paper shows that the New York Times became 20% more polarized (specifically, left-leaning) after adopting a paywall. As the mechanism, this paper finds that the newsroom became more polarized after paywall adoption: Post-paywall, journalists who wrote more left-leaning news articles were more likely to get new byline assignments. I discuss the policy implication of these findings for the media market.
Information-Seeking Argument Mining: A Step Towards Identifying Reasons in Textual Analysis to Improve Services (with Bernd Skiera, Johannes Daxenberger, Marcus Dombois, and Iryna Gurevych)
- Presented at Artificial Intelligence in Management Conference 2021
Service providers increasingly use textual analysis such as sentiment mining or topic models on unstructured data. Still, those techniques fall short when providing linguistic relations such as reasons behind changes in sentiment or topics. Information-seeking argument mining (IS‑AM) is a text mining technique that automatically extracts and identifies the argumentative structures (e.g., reasoning) from natural language text. So far, however, service researchers and managers hardly use IS‑AM. This article outlines how to use IS‑AM to improve services. The empirical study applies IS‑AM to news articles about scooter-sharing systems, i.e., a service enabling the short-term rentals of electric motorized scooters. The results outline that (i) arguments differ strongly across time, providers of scooter-sharing systems, and media, (ii) knowledge of arguments enable to improve services and communications with customers, and (iii) results from sentiment analysis support the validity of IS‑AM. The article closes with an outlook for further research.