
Fake news is increasingly an issue on social media platforms. In this work, rather than detect misinformation, we propose the use of nudges to help steer internet users into fact checking the news they read online. We discuss two types of nudging strategies, by presentation and by information. We present the tool BalancedView, a proof-of-concept that shows news stories relevant to a tweet. The method presents the user with a selection of articles from a range of reputable news sources providing alternative opinions from the whole political spectrum, with these alternative articles identified as matching the original one by a combination of natural language processing and search. The results of an initial user study of BalancedView suggest that nudging by information may change the behavior of users towards that of informed news readers.
Big Data, Technology, fake news, Science & Technology, Computer Science, Information Systems, 4609 Information systems, Twitter, Multidisciplinary Sciences, confirmation bias, 4605 Data management and data science, Computer Science, digital nudging, Science & Technology - Other Topics, NLP (natural language processing), Computer Science, Interdisciplinary Applications
Big Data, Technology, fake news, Science & Technology, Computer Science, Information Systems, 4609 Information systems, Twitter, Multidisciplinary Sciences, confirmation bias, 4605 Data management and data science, Computer Science, digital nudging, Science & Technology - Other Topics, NLP (natural language processing), Computer Science, Interdisciplinary Applications
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 45 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
