Abstract: A computer program product for recommending a dialog act to a participant in a conversation according to one embodiment includes a computer readable storage medium having program instructions embodied therewith. The computer readable storage medium is not a transitory signal per se, where the program instructions are executable by a processor to cause the processor to perform a method including receiving textual data associated with a real-time conversation between a first participant and a second participant, utilizing the processor, receiving an objective of the first participant for the real-time conversation between the first participant and the second participant, utilizing the processor, determining, utilizing the processor, a dialog act to be entered by the first participant at a current point in the real-time conversation that meets the objective, utilizing a model, and returning the dialog act to the first participant, utilizing the processor.

Abstract: A computer-implemented method according to one embodiment includes identifying a plurality of communications each having an associated objective, automatically determining a plurality of dialog acts within the plurality of communications, utilizing a classifier, determining a plurality of features within each of the plurality of communications, training the model, utilizing the plurality of communications and associated objectives, the plurality of dialog acts, and the plurality of features, receiving textual data associated with a real-time conversation between a first participant and a second participant, receiving an objective of the first participant for the real-time conversation between the first participant and the second participant, determining a dialog act to be entered by the first participant at a current point in the real-time conversation that meets the objective, utilizing the model, and determining the dialog act to be entered, based on the scoring, and returning the dialog act to the first pa

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a real-time conversation between a first participant and a second participant, receiving, utilizing the processor, an objective of the first participant for the real-time conversation between the first participant and the second participant, receiving, utilizing the processor, a proposed dialog act to be entered at a current point in the real-time conversation from the first participant, determining, utilizing the processor, an impact of the proposed dialog act on the objective of the first participant, utilizing a model, and performing, utilizing the processor, one or more actions based on the impact of the proposed dialog act.

Abstract: Tracking of brand followers utilizing social media history and generation of directed advertising. A computing device receives a brand for market analysis, the brand having a brand account on a social media platform. Social media history is received regarding social media habits of social media users. A distribution of brand followers is determined among social media users following the brand account. One or more clusters are generated for viewing market segmentation regarding the brand for market analysis. Brand data is received regarding a plurality of brands having brand accounts on the social media platform, follower profiles for brand followers of the plurality of brand accounts, and social media information for the followers of the plurality of brand accounts. An influencer analysis is generated. Historical follower profiles are received. A historical distribution analysis is generated. A market analysis is generated. Directed advertising is generated based upon the market analysis.

Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a conversation between a first participant and a second participant, receiving, utilizing the processor, an objective of the first participant for the conversation between the first participant and the second participant, receiving, utilizing the processor, a proposed dialog act to be entered in the conversation from the first participant, determining, utilizing the processor, an impact of the proposed dialog act on the objective of the first participant, utilizing a model, and performing, utilizing the processor, one or more actions based on the impact of the proposed dialog act.

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: A system, computer program product, and method are disclosed. In an approach to train customer service agent using chatbots. The method includes training a chatbot for a customer chat simulation based on a customer service conversation data, a task scenario, and a customer persona. The method also includes monitoring an interaction between a customer service agent and the chatbot. The method further includes determining an assessment of the performance of the customer service agent based on the interaction between the customer service agent and the chatbot. The method additionally includes generating feedback for the customer service agent based on the assessment of the performance of the customer service agent.

Abstract: A system, computer program product, and method are disclosed. In an approach to train customer service agent using chatbots. The method includes training a chatbot for a customer chat simulation based on a customer service conversation data, a task scenario, and a customer persona. The method also includes monitoring an interaction between a customer service agent and the chatbot. The method further includes determining an assessment of the performance of the customer service agent based on the interaction between the customer service agent and the chatbot. The method additionally includes generating feedback for the customer service agent based on the assessment of the performance of the customer service agent.

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: A computer program product for determining an impact of a proposed dialog act in a conversation according to one embodiment includes a computer readable storage medium having program instructions embodied therewith. The computer readable storage medium is not a transitory signal per se. The program instructions are executable by a processor to cause the processor to perform a method comprising receiving textual data associated with a real-time conversation between a first participant and a second participant, receiving an objective of the first participant for the real-time conversation between the first participant and the second participant, receiving a proposed dialog act to be entered at a current point in the real-time conversation from the first participant, determining an impact of the proposed dialog act on the objective of the first participant, and performing one or more actions based on the impact of the proposed dialog act.

Abstract: A method, a computer program product, and an information handling system is provided for labeling unlabeled utterances given a taxonomy of labels utilizing topic word semi-supervised learning.

Abstract: A computer program product for determining an impact of a proposed dialog act in a conversation according to one embodiment includes a computer readable storage medium having program instructions embodied therewith. The computer readable storage medium is not a transitory signal per se. The program instructions are executable by a processor to cause the processor to perform a method comprising receiving textual data associated with a real-time conversation between a first participant and a second participant, receiving an objective of the first participant for the real-time conversation between the first participant and the second participant, receiving a proposed dialog act to be entered at a current point in the real-time conversation from the first participant, determining an impact of the proposed dialog act on the objective of the first participant, and performing one or more actions based on the impact of the proposed dialog act.

Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a real-time conversation between a first participant and a second participant, receiving, utilizing the processor, an objective of the first participant for the real-time conversation between the first participant and the second participant, receiving, utilizing the processor, a proposed dialog act to be entered at a current point in the real-time conversation from the first participant, determining, utilizing the processor, an impact of the proposed dialog act on the objective of the first participant, utilizing a model, and performing, utilizing the processor, one or more actions based on the impact of the proposed dialog act.

Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a real-time conversation between a first participant and a second participant, receiving, utilizing the processor, an objective of the first participant for the real-time conversation between the first participant and the second participant, determining, utilizing the processor, a dialog act to be entered by the first participant at a current point in the real-time conversation that meets the objective, utilizing a model, and returning, utilizing the processor, the dialog act to the first participant.

Abstract: A computer program product for recommending a dialog act to a participant in a conversation according to one embodiment includes a computer readable storage medium having program instructions embodied therewith. The computer readable storage medium is not a transitory signal per se, where the program instructions are executable by a processor to cause the processor to perform a method including receiving textual data associated with a real-time conversation between a first participant and a second participant, utilizing the processor, receiving an objective of the first participant for the real-time conversation between the first participant and the second participant, utilizing the processor, determining, utilizing the processor, a dialog act to be entered by the first participant at a current point in the real-time conversation that meets the objective, utilizing a model, and returning the dialog act to the first participant, utilizing the processor.

Abstract: Input of a conversation is received. The conversation includes at least a first user. An utterance of the conversation is analyzed to identify a dialog act attribute, an emotion attribute, and a tone attribute. The dialog act attribute, emotion attribute, and tone attribute are annotated to the utterance of the conversation. The conversation is validated based on the annotated attributes compared with a threshold. The annotated conversation and the validation of the conversation are stored.

Abstract: A method, system and a computer program product are provided for enabling personal branding by using the symbolic meanings and utilities of products and a user's brand perceptions along with users input of a desired personal brand imagery to output visual information identifying one or more gaps between the user's desired and actual self-brand, thereby enabling a user to navigate products that shape their personal imagery.