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A Social Promotion Chatbot

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Abstract

We describe a chatbot performing advertising and social promotion (CASP) to assist in automation of managing friends and other social network contacts. This agent employs a domain-independent natural language relevance technique that filters web mining results to support a conversation with friends and other network members. This technique relies on learning parse trees and parse thickets (sets of parse trees) of paragraphs of text such as Facebook postings. To yield a web mining query from a sequence of previous postings by human agents discussing a topic, we develop a Lattice Querying algorithm which automatically adjusts the optimal level of query generality. We also propose an algorithm for CASP to make a translation into multiple languages plausible as well as a method to merge web mined textual chunks. We evaluate the relevance features, overall robustness and trust of CASP in a number of domains, acting on behalf of the author of this Chapter in his Facebook account in 2014–2016. Although some Facebook friends did not like CASP postings and even unfriended the host, overall social promotion results are positive as long as relevance, style and rhetorical appropriateness is properly maintained.

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Authors and Affiliations

  1. Oracle (United States), San Jose, CA, USA

    Boris Galitsky

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  1. Boris Galitsky
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Galitsky, B. (2019). A Social Promotion Chatbot. In: Developing Enterprise Chatbots. Springer, Cham. https://doi.org/10.1007/978-3-030-04299-8_12

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  • DOI: https://doi.org/10.1007/978-3-030-04299-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04298-1

  • Online ISBN: 978-3-030-04299-8

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