In today's society, people often find it difficult to read news outside their social circle or comfort zone. The questions of whether limited availability or active avoidance of such information determines its limited reach and which neurocognitive factors contribute to this outcome are of huge importance but not adequately studied. MyNewsScan is a news aggregator platform that we developed to tackle such questions. We performed experiments asking participants to select, read and evaluate news articles on MyNewsScan: either in our Edinburgh lab with collection of biometric information such as eye movements, heart rates and emotional expressions, or online (recruiting from Malaysia, Germany and UK). We analysed the collected data, investigating which factors affect participants’ choices of articles and engagement in MyNewsScan, and if their behavioural patterns could be predictive of personality traits or conditions such as anxiety and depression. Our results indicate that tiredness predicts usefulness and accuracy judgments of articles, motivation and openness to experience are linked to change in view as a result of reading an article, depression and conscientiousness are linked to perceived clarity of articles, and anxiety, neuroticism, extraversion and agreeableness to the number of opened articles. We also found various associations between facial expressions and article assessments. Finally, we’re developing a computational model of news selection that uses different article features and their associated values of successful performance to infer which article would be selected. Our work provides a much-needed toolbox for neurocognitive assessment of news-related decision making and a number of new findings.