Towards an online emotional support agent: Identifying emotional support strategies via crowdsourcing

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Abstract

In this paper, an empirical study conducted with Amazon Mechanical Turk workers is presented that aims to make a correspondence between messages about stressful situations, which were shared via Twitter, and 5 different types of supportive replies to them. Around 10.00 tweets were collected and analyzed in the terms previously described. We performed statistical tests to determine possible correlations between causes of stress and supportive response strategies. We are about to use these findings to improve a previously implemented algorithm that automatically generates supportive messages to stressed users. This algorithm is the core of an agent, in the form of a chatbot, that would be able to interact with such stressed users as if it would belong to their social networks.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS'18
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages2242-2244
Number of pages3
Volume3
ISBN (Print)9781450356497, 9781510868083
Publication statusPublished - Jul 2018
EventAAMAS 2018 Conference : July 10-15, 2018 Stockholm - Stockholm, Sweden
Duration: 10 Jul 201815 Jul 2018
http://www.ifaamas.org/AAMAS/aamas2018/

Publication series

NameAAMAS Conference proceedings.
PublisherIFAAMAS
Volume17th
ISSN (Print)2523-5699

Conference

ConferenceAAMAS 2018 Conference : July 10-15, 2018 Stockholm
CountrySweden
CityStockholm
Period10/07/1815/07/18
Internet address

Keywords

  • Chatbots
  • Crowdsourcing
  • Social agents
  • Social media
  • Social support

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