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Adaptive Modelling of Attentiveness to Messaging: A Hybrid Approach

Authors:

Adam J. LeeAuthors Info & Claims

UMAP '19: Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization

Pages 261 - 270

https://doi.org/10.1145/3320435.3320461

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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Cited By

Jain PFarzan RLee A(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
https://dl.acm.org/doi/10.1145/3604248
Jain P(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
https://dl.acm.org/doi/10.1145/3565967.3571758
Jain PFarzan RLee A(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
https://dl.acm.org/doi/10.1145/3532106.3533493
Show More Cited By

Index Terms

Adaptive Modelling of Attentiveness to Messaging: A Hybrid Approach
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User models
    2. HCI theory, concepts and models

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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

General Chairs:
George Angelos Papadopoulos
University of Cyprus, Cyprus
,
George Samaras
University of Cyprus, Cyprus
,
Stephan Weibelzahl
PFH Private University of Applied Sciences Göttingen, Germany
,
Program Chairs:
Dietmar Jannach
Alpen-Adria-Universität Klagenfurt, Austria
,
Olga C. Santos
aDeNu Research Group - UNED, Spain

Copyright © 2019 ACM.

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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National Science Foundation

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UMAP '19

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UMAP '19: 27th Conference on User Modeling, Adaptation and Personalization

June 9 - 12, 2019

Larnaca, Cyprus

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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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UMAP '25

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33rd ACM Conference on User Modeling, Adaptation and Personalization

June 16 - 19, 2025

New York City , NY , USA

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Cited By

Jain PFarzan RLee A(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
https://dl.acm.org/doi/10.1145/3604248
Jain P(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
https://dl.acm.org/doi/10.1145/3565967.3571758
Jain PFarzan RLee A(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
https://dl.acm.org/doi/10.1145/3532106.3533493
Jain PFarzan RLee A(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
https://doi.org/10.1007/s10606-021-09399-z
Mosse DPotter HLee S(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
https://doi.org/10.1109/TPS-ISA50397.2020.00030

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