research-article

Tweets are forever: a large-scale quantitative analysis of deleted tweets

Authors:

Hazim Almuhimedi,

Alessandro AcquistiAuthors Info & Claims

CSCW '13: Proceedings of the 2013 conference on Computer supported cooperative work

Pages 897 - 908

https://doi.org/10.1145/2441776.2441878

Published: 23 February 2013 Publication History

Abstract

This paper describes an empirical study of 1.6M deleted tweets collected over a continuous one-week period from a set of 292K Twitter users. We examine several aggregate properties of deleted tweets, including their connections to other tweets (e.g., whether they are replies or retweets), the clients used to produce them, temporal aspects of deletion, and the presence of geotagging information. Some significant differences were discovered between the two collections, namely in the clients used to post them, their conversational aspects, the sentiment vocabulary present in them, and the days of the week they were posted. However, in other dimensions for which analysis was possible, no substantial differences were found. Finally, we discuss some ramifications of this work for understanding Twitter usage and management of one's privacy.

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Cited By

Knöpfle PSchatto-Eckrodt T(2024)The Challenges of Replicating Volatile Platform-Data Studies: Replicating Schatto-Eckrodt et al. (2020)Media and Communication10.17645/mac.778912Online publication date: 15-Apr-2024
https://doi.org/10.17645/mac.7789
Sarig RWolff RToch E(2024)Cleaning house or quiet quitting? Large-scale analysis of account deletion behaviour on TumblrBehaviour & Information Technology10.1080/0144929X.2024.2370432(1-21)Online publication date: 18-Jul-2024
https://doi.org/10.1080/0144929X.2024.2370432
Küpfer A(2024)Nonrandom Tweet Mortality and Data Access Restrictions: Compromising the Replication of Sensitive Twitter StudiesPolitical Analysis10.1017/pan.2024.7(1-14)Online publication date: 17-May-2024
https://doi.org/10.1017/pan.2024.7
Show More Cited By

Index Terms

Tweets are forever: a large-scale quantitative analysis of deleted tweets
1. Information systems
  1. Information retrieval
    1. Document representation

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Published In

cover image ACM Conferences

CSCW '13: Proceedings of the 2013 conference on Computer supported cooperative work

February 2013

1594 pages

ISBN:9781450313315

DOI:10.1145/2441776

General Chairs:
Amy Bruckman
Georgia Institute of Technology, USA
,
Scott Counts
Microsoft Research, USA
,
Program Chairs:
Cliff Lampe
University of Michigan, USA
,
Loren Terveen
University of Minnesota, USA

Copyright © 2013 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: 23 February 2013

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February 23 - 27, 2013

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Cited By

Knöpfle PSchatto-Eckrodt T(2024)The Challenges of Replicating Volatile Platform-Data Studies: Replicating Schatto-Eckrodt et al. (2020)Media and Communication10.17645/mac.778912Online publication date: 15-Apr-2024
https://doi.org/10.17645/mac.7789
Sarig RWolff RToch E(2024)Cleaning house or quiet quitting? Large-scale analysis of account deletion behaviour on TumblrBehaviour & Information Technology10.1080/0144929X.2024.2370432(1-21)Online publication date: 18-Jul-2024
https://doi.org/10.1080/0144929X.2024.2370432
Küpfer A(2024)Nonrandom Tweet Mortality and Data Access Restrictions: Compromising the Replication of Sensitive Twitter StudiesPolitical Analysis10.1017/pan.2024.7(1-14)Online publication date: 17-May-2024
https://doi.org/10.1017/pan.2024.7
Szárnyas GBebee BBirler ADeutsch AFletcher GGabb HGosnell DGreen AGuo ZHare KHidders JIosup AKiryakov AKovatchev TLi XLibkin LLin HLuo XPrat-Pérez APüroja DQi Svan Rest OSteer BSzakállas DTong BWaudby JWu MYang BYu WZhang CZhang JZhou YBoncz P(2024)The Linked Data Benchmark Council (LDBC): Driving Competition and Collaboration in the Graph Data Management SpacePerformance Evaluation and Benchmarking10.1007/978-3-031-68031-1_7(90-106)Online publication date: 22-Sep-2024
https://doi.org/10.1007/978-3-031-68031-1_7
Ramokapane KRashid A(2023)ExD: Explainable DeletionProceedings of the 2023 New Security Paradigms Workshop10.1145/3633500.3633503(34-47)Online publication date: 18-Sep-2023
https://dl.acm.org/doi/10.1145/3633500.3633503
Elmas THorvát ÁHall WContractor NFröhling LOgnayova KTaneja HWeber IGligori? KMejova Y(2023)The Impact of Data Persistence Bias on Social Media StudiesProceedings of the 15th ACM Web Science Conference 202310.1145/3578503.3583630(196-207)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3578503.3583630
Diaz Ferreyra NShahi GTony CStieglitz SScandariato R(2023)Regret, Delete, (Do Not) Repeat: An Analysis of Self-Cleaning Practices on Twitter After the Outbreak of the COVID-19 PandemicExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585583(1-7)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585583
Vashistha SLongjam RKaushal R(2023)Gone but Not Forgotten: A Novel Approach for Collecting Deleted Tweets and TTL Prediction2023 International Conference in Advances in Power, Signal, and Information Technology (APSIT)10.1109/APSIT58554.2023.10201692(338-342)Online publication date: 9-Jun-2023
https://doi.org/10.1109/APSIT58554.2023.10201692
Heft ABuehling KZhang XSchindler DMilzner M(2023)Challenges of and approaches to data collection across platforms and time: Conspiracy-related digital traces as examples of political contentionJournal of Information Technology & Politics10.1080/19331681.2023.225077921:3(323-339)Online publication date: 28-Aug-2023
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Buehling K(2023)Message Deletion on Telegram: Affected Data Types and Implications for Computational AnalysisCommunication Methods and Measures10.1080/19312458.2023.218318818:1(92-114)Online publication date: 6-Mar-2023
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