short-paper

Social responses in mobile messaging: influence strategies, self-disclosure, and source orientation

Authors:

Claire Carlson,

Attapol Thamrongrattanarit,

Marcello Bastea-Forte,

B. J. FoggAuthors Info & Claims

CHI '09: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 1651 - 1654

https://doi.org/10.1145/1518701.1518954

Published: 04 April 2009 Publication History

Abstract

This paper reports on a direct test of social responses to communication technologies theory (SRCT) with mobile messaging. SRCT predicts that people will mindlessly respond to computers in social ways that mirror their responses to humans. A field experiment (N=71) using participants' own mobile phones compared three influence strategies (direct request, flattery, and social norms) in the context of asking intimate questions of participants. These messages came from either an ostensibly human or computer sender. Flattery significantly increased self-disclosure when ostensibly sent by a human, but not when from a computer. The interaction effect for sender and influence strategy is inconsistent with SRCT's predictions. Implications for theories of source orientation, research methods, and future research are discussed.

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Cited By

Marzouk OSalminen JZhang PJansen B(2022)Which Message? Which Channel? Which Customer?: Exploring Response Rates in Multi-Channel Marketing Using Short-Form AdvertisingData and Information Management10.1016/j.dim.2022.100008(100008)Online publication date: Apr-2022
https://doi.org/10.1016/j.dim.2022.100008
Marzouk OSalminen JZhang PJansen B(2021)Which Message? Which Channel? Which Customer? - Exploring Response Rates in Multi-Channel Marketing Using Short-Form AdvertisingData and Information Management10.2478/dim-2021-0011Online publication date: 24-Sep-2021
https://doi.org/10.2478/dim-2021-0011
Caraban AKarapanos EGonçalves DCampos PBrewster SFitzpatrick GCox AKostakos V(2019)23 Ways to NudgeProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300733(1-15)Online publication date: 2-May-2019
https://dl.acm.org/doi/10.1145/3290605.3300733
Show More Cited By

Index Terms

Social responses in mobile messaging: influence strategies, self-disclosure, and source orientation
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence
      1. Cognitive science
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
    2. Interaction paradigms
      1. Graphical user interfaces

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cover image ACM Conferences

CHI '09: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2009

2426 pages

ISBN:9781605582467

DOI:10.1145/1518701

General Chairs:
Dan R. Olsen
Brigham Young University
,
Richard B. Arthur
Brigham Young University
,
Program Chairs:
Ken Hinckley
Microsoft Research
,
Meredith Ringel Morris
Microsoft Research
,
Scott Hudson
Carnegie Mellon University
,
Saul Greenberg
University of Calgary

Copyright © 2009 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: 04 April 2009

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April 4 - 9, 2009

MA, Boston, USA

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CHI '09 Paper Acceptance Rate 277 of 1,130 submissions, 25%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

Marzouk OSalminen JZhang PJansen B(2022)Which Message? Which Channel? Which Customer?: Exploring Response Rates in Multi-Channel Marketing Using Short-Form AdvertisingData and Information Management10.1016/j.dim.2022.100008(100008)Online publication date: Apr-2022
https://doi.org/10.1016/j.dim.2022.100008
Marzouk OSalminen JZhang PJansen B(2021)Which Message? Which Channel? Which Customer? - Exploring Response Rates in Multi-Channel Marketing Using Short-Form AdvertisingData and Information Management10.2478/dim-2021-0011Online publication date: 24-Sep-2021
https://doi.org/10.2478/dim-2021-0011
Caraban AKarapanos EGonçalves DCampos PBrewster SFitzpatrick GCox AKostakos V(2019)23 Ways to NudgeProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300733(1-15)Online publication date: 2-May-2019
https://dl.acm.org/doi/10.1145/3290605.3300733
Srinivasan VTakayama LKaye JDruin ALampe CMorris DHourcade J(2016)Help Me PleaseProceedings of the 2016 CHI Conference on Human Factors in Computing Systems10.1145/2858036.2858217(4945-4955)Online publication date: 7-May-2016
https://dl.acm.org/doi/10.1145/2858036.2858217
Solomon JWash R(2014) Human- What Interaction? Understanding User Source Orientation Proceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/154193121458108858:1(422-426)Online publication date: 17-Oct-2014
https://doi.org/10.1177/1541931214581088
Cramer HEvers Vvan Slooten TGhijsen MWielinga BMynatt EFitzpatrick GHudson SEdwards KRodden T(2010)Trying too hardProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/1753326.1753546(1471-1474)Online publication date: 10-Apr-2010
https://dl.acm.org/doi/10.1145/1753326.1753546
Evers VWinterboer APavlin GGroen F(2010)The Evaluation of Empathy, Autonomy and Touch to Inform the Design of an Environmental Monitoring RobotSocial Robotics10.1007/978-3-642-17248-9_30(285-294)Online publication date: 2010
https://doi.org/10.1007/978-3-642-17248-9_30

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