Abstract: A processor may analyze one or more unread messages. The one or more unread messages may be from one or more respective conversations. The processor may generate, from the analyzing, an ambiguous strings model. The processor may summarize, via utilization of the ambiguous strings model, the one or more unread messages. The processor may genericize the ambiguous strings model.

Abstract: A processor may analyze one or more unread messages. The one or more unread messages may be from one or more respective conversations. The processor may generate, from the analyzing, an ambiguous strings model. The processor may summarize, via utilization of the ambiguous strings model, the one or more unread messages. The processor may genericize the ambiguous strings model.

Abstract: A user is detected navigating to a webpage. A plurality of web elements of the webpage is identified. One or more web elements is determined to have a risk score that surpasses a risk threshold of being a dark pattern. The risk score is identified by analyzing each of the plurality of web elements. A mitigation action configured to counteract the dark pattern is executed in response to the one or more web elements having the risk score that surpasses the risk threshold. The mitigating action is executed substantially immediately upon the user navigating to the webpage.

Abstract: Disclosed embodiments provide techniques for estimating the accuracy of a user rating score. In embodiments, a user rating score is obtained from a user. Online activity events such as social media posts, purchases, cancellations, online reviews, and/or other activities are analyzed by a computer system to determine a level of agreement between the score the user provided, and the online activity events of the user that pertain to the product and/or service to which the score pertains. A user rating score reliability factor is computed based on the level of agreement and can be made available to stakeholders such as product managers, marketing personnel, and sales teams.