Abstract: Techniques are described herein for receiving and analyzing messages originating from one sender for distribution to a recipient. A plurality of messages are received from a sender, each of the plurality of messages includes metadata and content. A sender profile is generated for the sender based on an analysis of the metadata of each of the plurality of messages. Each respective message of the plurality of messages is classified as one of a plurality of categories based on a deep learning network analysis of the content of each respective message. A sender fingerprint is generated based on a machine learning analysis of the content of each respective message. A probability that the sender is a spammer is determined based on the sender profile, the message classifications, and the sender fingerprint. The sender is tagged based on the determined probability.

Abstract: Techniques are described herein for processing intra- and inter-messaging platform communications, including by receiving and analyzing messages originating from one sender for distribution to a recipient, where the sender and recipient may be on a same or separate messaging platform. Clusters of such messages with similar contents or other similar characteristics are identified and categorized, such as in accordance with configuration information regarding one or both of the originating and destination messaging platforms. Based on a determination of one or more categories associated with such an identified message cluster, as well as an analysis of metadata associated with the profile of the sender of the messages, various actions may be taken with respect to such message clusters or with parties associated with such message clusters, including actions based at least in part on the configuration information.

Abstract: Techniques are described herein for processing intra- and inter-messaging platform communications, including by receiving and analyzing messages originating from one sender for distribution to a recipient, where the sender and recipient may be on a same or separate messaging platform. Clusters of such messages with similar contents or other similar characteristics are identified and categorized, such as in accordance with configuration information regarding one or both of the originating and destination messaging platforms. Based on a determination of one or more categories associated with such an identified message cluster, as well as an analysis of metadata associated with the profile of the sender of the messages, various actions may be taken with respect to such message clusters or with parties associated with such message clusters, including actions based at least in part on the configuration information.

Abstract: Techniques are described herein for processing intra- and inter-messaging platform communications, including by receiving and analyzing messages originating from one sender for distribution to a recipient, where the sender and recipient may be on a same or separate messaging platform. Clusters of such messages with similar contents or other similar characteristics are identified and categorized, such as in accordance with configuration information regarding one or both of the originating and destination messaging platforms. Based on a determination of one or more categories associated with such an identified message cluster, as well as an analysis of metadata associated with the profile of the sender of the messages, various actions may be taken with respect to such message clusters or with parties associated with such message clusters, including actions based at least in part on the configuration information.