Twitter Newcomers: Uncovering the Behavior and Fate of New Accounts Through Early Detection and Monitoring
There is a significant body of literature concerning the analysis of Twitter accounts, yet the behavior of newly created accounts remains relatively unexplored. In this study, we introduce a novel approach to detect Twitter accounts right after registration and explore their behavioral patterns. In...
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Format: | Article |
Language: | English |
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IEEE
2023-01-01
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Series: | IEEE Access |
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Online Access: | https://ieeexplore.ieee.org/document/10143198/ |
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author | Guglielmo Cola Michele Mazza Maurizio Tesconi |
author_facet | Guglielmo Cola Michele Mazza Maurizio Tesconi |
author_sort | Guglielmo Cola |
collection | DOAJ |
description | There is a significant body of literature concerning the analysis of Twitter accounts, yet the behavior of newly created accounts remains relatively unexplored. In this study, we introduce a novel approach to detect Twitter accounts right after registration and explore their behavioral patterns. In a two-week period in April 2020, our technique identified over 500,000 accounts before they even started interacting with the platform. Each account was monitored for 21 days by sampling profile information and timelines at scheduled intervals, retrieving over 8 million tweets. An additional sample of profile information was collected approximately two years after creation, in May 2022. One of the key findings of our study is the lack of sustained and genuine engagement from new accounts. Indeed, a large proportion of them (almost 25%) were suspended by Twitter in the first 21 days, and the evaluation conducted after two years reveals that only a tiny fraction of the remaining enabled accounts seem to be active and genuine users (3.8% of the initial sample). Additionally, despite the early suspensions enforced by Twitter, it turns out that some short-lived accounts still managed to have a substantial impact on the total volume of content and interactions from new accounts. Overall, our findings may have important implications for understanding the dynamics of new accounts’ behavior as well as Twitter’s suspension policy prior to the recent change in ownership. This could stimulate further research to evaluate the impact of the ongoing changes introduced by the new administration. |
first_indexed | 2024-03-13T06:38:03Z |
format | Article |
id | doaj.art-5e64660453d540b9ad09f4d713f305b0 |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-03-13T06:38:03Z |
publishDate | 2023-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
spelling | doaj.art-5e64660453d540b9ad09f4d713f305b02023-06-08T23:01:29ZengIEEEIEEE Access2169-35362023-01-0111552235523210.1109/ACCESS.2023.328258010143198Twitter Newcomers: Uncovering the Behavior and Fate of New Accounts Through Early Detection and MonitoringGuglielmo Cola0https://orcid.org/0000-0003-2890-723XMichele Mazza1Maurizio Tesconi2Institute of Informatics and Telematics (IIT), National Research Council (CNR), Pisa, ItalyInstitute of Informatics and Telematics (IIT), National Research Council (CNR), Pisa, ItalyInstitute of Informatics and Telematics (IIT), National Research Council (CNR), Pisa, ItalyThere is a significant body of literature concerning the analysis of Twitter accounts, yet the behavior of newly created accounts remains relatively unexplored. In this study, we introduce a novel approach to detect Twitter accounts right after registration and explore their behavioral patterns. In a two-week period in April 2020, our technique identified over 500,000 accounts before they even started interacting with the platform. Each account was monitored for 21 days by sampling profile information and timelines at scheduled intervals, retrieving over 8 million tweets. An additional sample of profile information was collected approximately two years after creation, in May 2022. One of the key findings of our study is the lack of sustained and genuine engagement from new accounts. Indeed, a large proportion of them (almost 25%) were suspended by Twitter in the first 21 days, and the evaluation conducted after two years reveals that only a tiny fraction of the remaining enabled accounts seem to be active and genuine users (3.8% of the initial sample). Additionally, despite the early suspensions enforced by Twitter, it turns out that some short-lived accounts still managed to have a substantial impact on the total volume of content and interactions from new accounts. Overall, our findings may have important implications for understanding the dynamics of new accounts’ behavior as well as Twitter’s suspension policy prior to the recent change in ownership. This could stimulate further research to evaluate the impact of the ongoing changes introduced by the new administration.https://ieeexplore.ieee.org/document/10143198/Ephemeral accountsfake accountssocial botssocial media analysissuspended accountsuser engagement |
spellingShingle | Guglielmo Cola Michele Mazza Maurizio Tesconi Twitter Newcomers: Uncovering the Behavior and Fate of New Accounts Through Early Detection and Monitoring IEEE Access Ephemeral accounts fake accounts social bots social media analysis suspended accounts user engagement |
title | Twitter Newcomers: Uncovering the Behavior and Fate of New Accounts Through Early Detection and Monitoring |
title_full | Twitter Newcomers: Uncovering the Behavior and Fate of New Accounts Through Early Detection and Monitoring |
title_fullStr | Twitter Newcomers: Uncovering the Behavior and Fate of New Accounts Through Early Detection and Monitoring |
title_full_unstemmed | Twitter Newcomers: Uncovering the Behavior and Fate of New Accounts Through Early Detection and Monitoring |
title_short | Twitter Newcomers: Uncovering the Behavior and Fate of New Accounts Through Early Detection and Monitoring |
title_sort | twitter newcomers uncovering the behavior and fate of new accounts through early detection and monitoring |
topic | Ephemeral accounts fake accounts social bots social media analysis suspended accounts user engagement |
url | https://ieeexplore.ieee.org/document/10143198/ |
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