Unaddressed challenges in persuasive dieting chatbots

Simone Balloccu; Ehud Reiter; Matteo G.  Collu; Federico  Sanna; Manuela  Sanguinetti; Maurizio Atzori

doi:10.1145/3450614.3463602

Unaddressed challenges in persuasive dieting chatbots

Simone Balloccu, Ehud Reiter, Matteo G. Collu, Federico Sanna, Manuela Sanguinetti, Maurizio Atzori

University of Cagliari

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

5 Citations (Scopus)

Abstract

Diet coaching is a behaviour change task which requires lots of interaction with patients. E-health apps gathered lots of interest in research and, recently, chatbots have been leveraged to address this task, with a focus on persuasion to motivate people towards behaviour change. In this paper, we take a look at current approaches in building persuasive dieting chatbots and expose a number of major unsolved challenges. We motivate them with evidence from previous work and show that current chatbots don’t approach certain scenarios properly, hence limiting their communication and persuasion capabilities.

Original language	English
Title of host publication	UMAP '21
Subtitle of host publication	Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization
Publisher	Association for Computing Machinery (ACM)
Pages	392-395
Number of pages	4
ISBN (Print)	978-1-4503-8367-7
DOIs	https://doi.org/10.1145/3450614.3463602
Publication status	Published - 22 Jun 2021
Event	29th Conference on User Modeling, Adaptation and Personalization: UMAP '21 - Online from Utrecht, Utrecht, Netherlands Duration: 21 Jun 2021 → 25 Jun 2021 Conference number: 29th https://www.um.org/umap2021/

Conference

Conference	29th Conference on User Modeling, Adaptation and Personalization
Abbreviated title	UMAP '21
Country/Territory	Netherlands
City	Utrecht
Period	21/06/21 → 25/06/21
Internet address	https://www.um.org/umap2021/

Keywords

conversational agents
chatbots
diet
diet coaching
natural language generation
persuasion
challenges

Access to Document

10.1145/3450614.3463602Licence: Unspecified

Cite this

Unaddressed challenges in persuasive dieting chatbots. / Balloccu, Simone; Reiter, Ehud; Collu, Matteo G. et al.
UMAP '21: Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery (ACM), 2021. p. 392-395.

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

Balloccu, S, Reiter, E, Collu, MG, Sanna, F, Sanguinetti, M & Atzori, M 2021, Unaddressed challenges in persuasive dieting chatbots. in UMAP '21: Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery (ACM), pp. 392-395, 29th Conference on User Modeling, Adaptation and Personalization, Utrecht, Netherlands, 21/06/21. https://doi.org/10.1145/3450614.3463602

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AU - Sanguinetti, Manuela

AU - Atzori, Maurizio

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AB - Diet coaching is a behaviour change task which requires lots of interaction with patients. E-health apps gathered lots of interest in research and, recently, chatbots have been leveraged to address this task, with a focus on persuasion to motivate people towards behaviour change. In this paper, we take a look at current approaches in building persuasive dieting chatbots and expose a number of major unsolved challenges. We motivate them with evidence from previous work and show that current chatbots don’t approach certain scenarios properly, hence limiting their communication and persuasion capabilities.

KW - conversational agents

KW - chatbots

KW - diet

KW - diet coaching

KW - natural language generation

KW - persuasion

KW - challenges

U2 - 10.1145/3450614.3463602

DO - 10.1145/3450614.3463602

M3 - Published conference contribution

SN - 978-1-4503-8367-7

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BT - UMAP '21

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T2 - 29th Conference on User Modeling, Adaptation and Personalization

Y2 - 21 June 2021 through 25 June 2021

ER -

Unaddressed challenges in persuasive dieting chatbots

Abstract

Conference

Keywords

Access to Document

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Cite this