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Adaptive Modelling of Attentiveness to Messaging: A Hybrid Approach

Published: 07 June 2019 Publication History

Abstract

Identifying instances when a user will not able to attend to an incoming message and constructing an auto-response with relevant contextual information may help reduce social pressures to immediately respond that many users face. Mobile messaging behavior often varies from one person to another. As a result, compared to a generic model considering profiles of several users, a personalized model can capture a user's messaging behavior more accurately to predict their inattentive states. However, creating accurate personalized models requires a non-trivial amount of individual data, which is often not available for new users. In this work, we investigate a weighted hybrid approach to model users' attention to messaging. Through dynamic performance-based weighting, we combine the predictions of three types of models, a general model, a group model and a personalized model to create an approach which can work through the lack of initial data while adapting to the user's behavior. We present the details of our modeling approach and the evaluation of the model with over three weeks of data from 274 users. Our results highlight the value of hybrid weighted modeling to predict when a user cannot attend to their messages.

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  • (2023)Co-Designing with Users the Explanations for a Proactive Auto-Response Messaging AgentProceedings of the ACM on Human-Computer Interaction10.1145/36042487:MHCI(1-23)Online publication date: 13-Sep-2023
  • (2023)Design and Evaluation of a Virtual Assistant for improving Awareness in Mobile MessagingCompanion Proceedings of the 2023 ACM International Conference on Supporting Group Work10.1145/3565967.3571758(63-65)Online publication date: 8-Jan-2023
  • (2022)Laila is in a Meeting: Design and Evaluation of a Contextual Auto-Response Messaging AgentProceedings of the 2022 ACM Designing Interactive Systems Conference10.1145/3532106.3533493(1457-1471)Online publication date: 13-Jun-2022
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cover image ACM Conferences
UMAP '19: Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization
June 2019
377 pages
ISBN:9781450360210
DOI:10.1145/3320435
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 June 2019

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Author Tags

  1. adaptive modelling
  2. inattentiveness
  3. messaging
  4. user clustering

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UMAP '19 Paper Acceptance Rate 30 of 122 submissions, 25%;
Overall Acceptance Rate 162 of 633 submissions, 26%

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Cited By

View all
  • (2023)Co-Designing with Users the Explanations for a Proactive Auto-Response Messaging AgentProceedings of the ACM on Human-Computer Interaction10.1145/36042487:MHCI(1-23)Online publication date: 13-Sep-2023
  • (2023)Design and Evaluation of a Virtual Assistant for improving Awareness in Mobile MessagingCompanion Proceedings of the 2023 ACM International Conference on Supporting Group Work10.1145/3565967.3571758(63-65)Online publication date: 8-Jan-2023
  • (2022)Laila is in a Meeting: Design and Evaluation of a Contextual Auto-Response Messaging AgentProceedings of the 2022 ACM Designing Interactive Systems Conference10.1145/3532106.3533493(1457-1471)Online publication date: 13-Jun-2022
  • (2021)Context-based Automated Responses of Unavailability in Mobile MessagingComputer Supported Cooperative Work (CSCW)10.1007/s10606-021-09399-z30:3(307-349)Online publication date: 25-May-2021
  • (2020)Maintaining Privacy and Utility in IoT System Analytics2020 Second IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)10.1109/TPS-ISA50397.2020.00030(157-164)Online publication date: Oct-2020

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