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"i read my Twitter the next morning and was astonished": a conversational perspective on Twitter regrets

Published: 27 April 2013 Publication History

Abstract

We present the results of an online survey of 1,221 Twitter users, comparing messages individuals regretted either saying during in-person conversations or posting on Twitter. Participants generally reported similar types of regrets in person and on Twitter. In particular, they often regretted messages that were critical of others. However, regretted messages that were cathartic/expressive or revealed too much information were reported at a higher rate for Twitter. Regretted messages on Twitter also reached broader audiences. In addition, we found that participants who posted on Twitter became aware of, and tried to repair, regret more slowly than those reporting in-person regrets. From this comparison of Twitter and in-person regrets, we provide preliminary ideas for tools to help Twitter users avoid and cope with regret.

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    cover image ACM Conferences
    CHI '13: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
    April 2013
    3550 pages
    ISBN:9781450318990
    DOI:10.1145/2470654
    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: 27 April 2013

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    1. conversation
    2. messaging
    3. regrets
    4. survey
    5. twitter

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    • (2024)Proof of Unlearning: Definitions and InstantiationIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.335899319(3309-3323)Online publication date: 2024
    • (2024)Influencing Factors of Social Media Users’ Information Deletion Behavior Based on the Grounded TheorySustainability and Empowerment in the Context of Digital Libraries10.1007/978-981-96-0868-3_13(156-167)Online publication date: 6-Dec-2024
    • (2024)Factors of Intention to Use a Photo Tool: Comparison Between Privacy-Enhancing and Non-privacy-enhancing ToolsICT Systems Security and Privacy Protection10.1007/978-3-031-56326-3_23(321-334)Online publication date: 24-Apr-2024
    • (2023)Detecting and identifying the reasons for deleted tweets before they are postedFrontiers in Artificial Intelligence10.3389/frai.2023.12197676Online publication date: 29-Sep-2023
    • (2023)Twitter has a Binary Privacy Setting, are Users Aware of How It Works?Proceedings of the ACM on Human-Computer Interaction10.1145/35795377:CSCW1(1-18)Online publication date: 16-Apr-2023
    • (2022)Runtime permissions for privacy in proactive intelligent assistantsProceedings of the Eighteenth USENIX Conference on Usable Privacy and Security10.5555/3563609.3563643(633-651)Online publication date: 8-Aug-2022
    • (2022)What Users Want From Cloud Deletion and the Information They Need: A Participatory Action StudyACM Transactions on Privacy and Security10.1145/354657826:1(1-34)Online publication date: 7-Nov-2022
    • (2022)From Sentiment to Sensitivity: The Role of Emotions on Privacy Exposure in TwitterProceedings of the 2022 Workshop on Open Challenges in Online Social Networks10.1145/3524010.3539501(10-15)Online publication date: 28-Jun-2022
    • (2022)BlackLivesMatter 2020: An Analysis of Deleted and Suspended Users in TwitterProceedings of the 14th ACM Web Science Conference 202210.1145/3501247.3531539(290-295)Online publication date: 26-Jun-2022
    • (2022)Understanding Privacy Switching Behaviour on TwitterProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517675(1-14)Online publication date: 29-Apr-2022
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