YouTube is a valuable source of user‐generated content on a wide range of topics, and it encourages user participation through the use of a comment system. Video content is increasingly addressing scientific topics, and there is evidence that both academics and consumers use video descriptions and video comments to refer to academic research and scientific publications. Because commenting is a discursive behavior, this study will provide insights on why individuals post links to research publications in comments. For this, a qualitative content analysis and iterative coding approach were applied. Furthermore, the reasons for mentioning academic publications in comments were contrasted with the reasons for citing in scholarly works and with reasons for commenting on YouTube. We discovered that the primary motives for sharing research links were (1) providing more insights into the topic and (2) challenging information offered by other commentators.

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Every year, traffic congestion costs the global economy billions of dollars in lost productivity, particularly in urban areas. Traffic congestion is a complex problem, as traffic conditions may change at any time. Tidal-flow lanes can be utilised as a feasible traffic-congestion-mitigation strategy to balance the fluctuating traffic demands throughout the day. This paper proposes an adaptive-lane-reversal approach for tidal-flow lanes, to decrease the impact of traffic congestion in urban areas. In order to evaluate the adaptive approach under various traffic conditions, several algorithms and parameter sets are examined, using various network models and traffic demands. As a result, the total travel time of the vehicles in the various networks was decreased by up to 81%.