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• W2903249390 abstract "Purpose The number of internet consumers who adopt ad-blocking is increasing rapidly all over the world. The purpose of this paper is to evaluate this phenomenon by: assembling the existing considerations and key theoretical aspects of the determinants of online ad-blocking; and by exploring the consumers’ beliefs and sentiments toward online ads and expected outcomes of ad-blocking behavior. Design/methodology/approach Data consist of 4,093 consumers’ opinions in response to the news items about ad-blocking, published by a leading news and technology website in the period 2010–2016. The unstructured data are analyzed using probabilistic topic modeling and sentiment analysis. Findings Five main topics are identified, unveiling the hidden structure of consumers’ beliefs. A sentiment analysis profiling the clustered opinions reveals that the opinions that are focused on the behavioral characteristics of ads express the strongest negative sentiment, while the opinions centered on the possibility to subscribe to an ad-free fee-financed website are characterized on average by a positive sentiment. Practical implications The findings provide useful insights for practitioners to create/adopt more acceptable ads that translate into less ad-blocking and improved internet surfing experience. It brings insights on the question of whether ad-free subscription websites have or do not have the potential to become a viable business opportunity. Originality/value The research: improves the current understanding of the determinants of ad-blocking by introducing a conceptual framework and testing it empirically; makes use of consumer-generated data on the internet; and implements novel techniques from the data mining literature." @default.
• W2903249390 created "2018-12-11" @default.
• W2903249390 creator A5081533012 @default.
• W2903249390 date "2019-02-04" @default.
• W2903249390 modified "2023-10-09" @default.
• W2903249390 title "Why do internet consumers block ads? New evidence from consumer opinion mining and sentiment analysis" @default.
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• W2903249390 doi "https://doi.org/10.1108/intr-06-2017-0221" @default.
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