Abstract: Some embodiments include a method of detecting memes, as “key terms,” in a chatter aggregation in a social networking system. The method can include aggregating user-generated content objects within the social networking system into the chatter aggregation according to a set of filters. A meme analysis engine can define a target group within the chatter aggregation to compare against a background group. The meme analysis engine can extract key terms from textual content of the target group. The meme analysis engine can determine a relevancy rank of a term in the key terms based on an accounting of the term in the textual content of the target group and a linguistic relevance score of the term according to a linguistic model.

Abstract: Managing workflow on a plurality of installed application components that interact with a central hosted component is disclosed. A rule defined on the central hosted component is obtained. A new action item to be executed on an installed application component in the plurality of installed application components is generated at least in part by applying the obtained rule based at least in part on data provided by the installed application component and information that is managed by the central hosted component. The new action item to be executed by the installed application component is communicated. The new action item modifies a workflow on the installed application component without modifying application code on the installed application component.

Abstract: A method of generating a synthetic content feed includes receiving a request to display a synthetic content feed for a class of users of a social networking system, identifying a first user and a second user based on profile data for the first user and second user in the social networking system, constructing a first post of synthetic content feed representative of a first post in the content feed of the first user, constructing a second post of synthetic content feed representative of a second post in the content feed of the second user, and providing the synthetic content feed for display.

Abstract: An online system receives information from an entity identifying a set of users of the online system and groups users included in the set into clusters based on their similarities using a clustering model or algorithm (e.g., k-means clustering) and based on one or more parameters specified by the entity. The online system generates expanded clusters that include additional users in one or more clusters based on similarities between the additional users and users in various clusters. If an additional user is included in multiple expanded clusters, the online assigns the additional user exclusively to an expanded cluster that best fits the user.

Abstract: Some embodiments include a method of detecting memes, as “key terms,” in a chatter aggregation in a social networking system. The method can include aggregating user-generated content objects within the social networking system into the chatter aggregation according to a set of filters. A meme analysis engine can define a target group within the chatter aggregation to compare against a background group. The meme analysis engine can extract key terms from textual content of the target group. The meme analysis engine can determine a relevancy rank of a term in the key terms based on an accounting of the term in the textual content of the target group and a linguistic relevance score of the term according to a linguistic model.

Abstract: Some embodiments include a method of performing a content analysis study around a central theme utilizing a concept study system. The concept study system can generate a classifier machine corresponding to the content analysis study based on a super topic taxonomy including one or more concept identifiers. The concept study system can process a content object, associated with a user activity in a social networking system, through the classifier machine to determine whether to assign the user activity to the content analysis study. The concept study system can aggregate at least an attribute derived from the user activity in a study-specific data container associated with the content analysis study and compute a statistical or analytical insight based on aggregated attributes in the study-specific data container.

Abstract: Managing workflow on a plurality of installed application components that interact with a central hosted component is disclosed. A new rule is defined on the central hosted component. The new rule is applied, based on data provided by an installed application component and information that is managed by the central hosted component, to generate a new action item to be executed on the installed application component. The new action item to be executed by the installed application component is sent. The new action item modifies a workflow on the installed application component without modifying application code on the installed application component.

Abstract: Automated assignment of insurance claim work includes: obtaining an insurance claim work unit; identifying among a plurality of users of the insurance claims processing platform a set of eligible users who are eligible to process the insurance claim work unit; and automatically selecting among the set of eligible users a selected user to process the insurance claim work unit, including determining a set of weighted workloads that corresponds to the set of eligible users and applying a set of one or more assignment rules based on the set of weighted workloads.