Abstract: Weighting sentiment information includes capturing sentiment information of a post from an electronic source, categorizing the post into categories based on the sentiment information, and assigning a weight to the post based on an interest attribute.

Abstract: Embodiments include method, systems and computer program products for dynamic processing for collaborative events. In some embodiments, first data associated with a collaborative event may be received. Second data from one or more sensors of a user device may be received. The first data and the second data may be analyzed. An action recommendation may be generated based on the analyzed first data and the analyzed second data. The action recommendation may be transmitted.

Abstract: Embodiments include method, systems and computer program products for dynamic processing for collaborative events. In some embodiments, first data associated with a collaborative event may be received. Second data from one or more sensors of a user device may be received. The first data and the second data may be analyzed. An action recommendation may be generated based on the analyzed first data and the analyzed second data. The action recommendation may be transmitted.

Abstract: A method, computer program product, and system for ranking meeting topics is described. A plurality of participants in an electronic meeting is identified. One or more interests associated with one or more individuals included in the plurality of participants are identified. One or more topics associated with the meeting are received. A ranking of the one or more topics is determined based upon, at least in part, the one or more identified interests.

Abstract: Methods, products, apparatus, and systems may identify one or more relevant social communities for one or more questions. Additionally, a user-question affinity value between a user and a question may be determined. In addition, a user-community affinity value between the user and each of a plurality of candidate social communities may be determined. Moreover, a question-community affinity value between the question and each of the plurality of candidate social communities may be determined based on the user-question affinity value and the user-community affinity value. The question-community affinity value determination may involve calculating a running average using the user-question affinity value and the user-community affinity value. The question-community affinity value may identify the one or more relevant social communities from the plurality of candidate social communities.

Abstract: Methods, products, apparatus, and systems may identify one or more relevant social communities for one or more questions. Additionally, a user-question affinity value between a user and a question may be determined. In addition, a user-community affinity value between the user and each of a plurality of candidate social communities may be determined. Moreover, a question-community affinity value between the question and each of the plurality of candidate social communities may be determined based on the user-question affinity value and the user-community affinity value. The question-community affinity value determination may involve calculating a running average using the user-question affinity value and the user-community affinity value. The question-community affinity value may identify the one or more relevant social communities from the plurality of candidate social communities.

Abstract: Weighting sentiment information includes capturing sentiment information of a post from an electronic source, categorizing the post into categories based on the sentiment information, and assigning a weight to the post based on an interest attribute.

Abstract: Weighting sentiment information includes capturing sentiment information of a post from an electronic source, categorizing the post into categories based on the sentiment information, and assigning a weight to the post based on an interest attribute.

Abstract: Weighting sentiment information includes capturing sentiment information of a post from an electronic source, categorizing the post into categories based on the sentiment information, and assigning a weight to the post based on an interest attribute.

Abstract: Methods, products, apparatus, and systems may identify one or more relevant social communities for one or more questions. Additionally, a user-question affinity value between a user and a question may be determined. In addition, a user-community affinity value between the user and each of a plurality of candidate social communities may be determined. Moreover, a question-community affinity value between the question and each of the plurality of candidate social communities may be determined based on the user-question affinity value and the user-community affinity value. The question-community affinity value determination may involve calculating a running average using the user-question affinity value and the user-community affinity value. The question-community affinity value may identify the one or more relevant social communities from the plurality of candidate social communities.

Abstract: Methods, products, apparatus, and systems may identify one or more relevant social communities for one or more questions. Additionally, a user-question affinity value between a user and a question may be determined. In addition, a user-community affinity value between the user and each of a plurality of candidate social communities may be determined. Moreover, a question-community affinity value between the question and each of the plurality of candidate social communities may be determined based on the user-question affinity value and the user-community affinity value. The question-community affinity value determination may involve calculating a running average using the user-question affinity value and the user-community affinity value. The question-community affinity value may identify the one or more relevant social communities from the plurality of candidate social communities.

Abstract: A method, computer program product, and system for ranking meeting topics is described. A plurality of participants in an electronic meeting is identified. One or more interests associated with one or more individuals included in the plurality of participants are identified. One or more topics associated with the meeting are received. A ranking of the one or more topics is determined based upon, at least in part, the one or more identified interests.