Abstract: Methods, systems, apparatuses, devices, and computer program products are described. A group-based communication system may use machine learning techniques to classify teams of the system, determine discount messaging for teams of the system, or both. The group-based communication system may receive concurrency data for a team of users and may input the concurrency data (e.g., with one or more other features associated with the team) into a machine learning model to generate a classifier for the team. The classifier may indicate whether the team is a work team, an educational team, or a social team. Based on the classifier for the team, the system may send a message to at least one user of the team (e.g., an administrative user). In some examples, the system may use another machine learning model to generate a discount message for sending to the at least one user based on the team classifier.

Abstract: Techniques for generating graphical elements via a communication platform are discussed herein. For example, one or more machine-learning models associated with a communication platform may be configured to receive, as input and from a user of the communication platform, a sentiment and/or a graphical element. The machine-learning model may be trained, using prior natural language statements and prior confidence levels associated with previous graphical elements, to output one or more graphical elements associated with the input. The one or more graphical elements may be shared via the communication platform and used to accurately and effectively convey thoughts, emotions, reactions, and ideas, for example.

Abstract: Techniques for generating user profile data including one or more frequent channels, related users, and/or related topics within a communication platform are discussed herein. In some examples, a machine-learning model can receive user interaction data (messages sent, messages read, channel posts, documents shared, frequent key words used, etc.) associated with the communication platform and output one or more frequent channels, related users, and/or related topics. The communication platform may then associate the one or more frequent channels, related users, and/or related topics with the user's profile data. In some examples, the communication platform may present different frequent channels, related users, and/or related topics associated with a profile page based on interaction action associated with the user account viewing the profile page.

Abstract: Methods, systems, apparatuses, devices, and computer program products are described. A group-based communication system may determine timing for sending notifications to users of the group-based communication system to improve the likelihood of the users interacting with the notifications, interacting with other users in the system, or both. For example, the group-based communication system may identify a notification to send to a user, where the user is associated with a user identifier and a workspace identifier in the group-based communication system. The system may dynamically determine a time for sending the notification based on activity data for the user corresponding to the user identifier and activity data for multiple other users corresponding to the workspace identifier (e.g., members of a team with the user). The system may send the notification for display in a user interface of a user device operated by the user at the determined time.

Abstract: Systems, methods, and computer-readable media are provided for adding connections for a user. External graphs may be analyzed to identify connections and relationships which may be missing in a group-based communication system. These missing connections may be suggested to the user as a suggested virtual space. A user may then create the virtual space based on the suggestions.

Abstract: Methods, systems, apparatuses, devices, and computer program products are described. A group-based communication system may determine timing for sending notifications to users of the group-based communication system to improve the likelihood of the users interacting with the notifications, interacting with other users in the system, or both. For example, the group-based communication system may identify a notification to send to a user, where the user is associated with a user identifier and a workspace identifier in the group-based communication system. The system may dynamically determine a time for sending the notification based on activity data for the user corresponding to the user identifier and activity data for multiple other users corresponding to the workspace identifier (e.g., members of a team with the user). The system may send the notification for display in a user interface of a user device operated by the user at the determined time.