Detecting and identifying the reasons for deleted tweets before they are posted
<p dir="ltr">Social media platforms empower us in several ways, from information dissemination to consumption. While these platforms are useful in promoting citizen journalism, public awareness, etc., they have misuse potential. Malicious users use them to disseminate hate speech, of...
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| مؤلفون آخرون: | , , |
| منشور في: |
2023
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إضافة وسم
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| _version_ | 1864513509178474496 |
|---|---|
| author | Hamdy Mubarak (19365502) |
| author2 | Samir Abdaljalil (11513178) Azza Nassar (19365505) Firoj Alam (14158866) |
| author2_role | author author author |
| author_facet | Hamdy Mubarak (19365502) Samir Abdaljalil (11513178) Azza Nassar (19365505) Firoj Alam (14158866) |
| author_role | author |
| dc.creator.none.fl_str_mv | Hamdy Mubarak (19365502) Samir Abdaljalil (11513178) Azza Nassar (19365505) Firoj Alam (14158866) |
| dc.date.none.fl_str_mv | 2023-09-29T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3389/frai.2023.1219767 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Detecting_and_identifying_the_reasons_for_deleted_tweets_before_they_are_posted/26535508 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Artificial intelligence Human-centred computing disinformation deleted tweets hate-speech Arabic social media |
| dc.title.none.fl_str_mv | Detecting and identifying the reasons for deleted tweets before they are posted |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Social media platforms empower us in several ways, from information dissemination to consumption. While these platforms are useful in promoting citizen journalism, public awareness, etc., they have misuse potential. Malicious users use them to disseminate hate speech, offensive content, rumor, etc. to promote social and political agendas or to harm individuals, entities, and organizations. Oftentimes, general users unconsciously share information without verifying it or unintentionally post harmful messages. Some of such content often gets deleted either by the platform due to the violation of terms and policies or by users themselves for different reasons, e.g., regret. There is a wide range of studies in characterizing, understanding, and predicting deleted content. However, studies that aim to identify the fine-grained reasons (e.g., posts are offensive, hate speech, or no identifiable reason) behind deleted content are limited. In this study, we address an existing gap by identifying and categorizing deleted tweets, especially within the Arabic context. We label them based on fine-grained disinformation categories. We have curated a dataset of 40K tweets, annotated with both coarse and fine-grained labels. Following this, we designed models to predict the likelihood of tweets being deleted and to identify the potential reasons for their deletion. Our experiments, conducted using a variety of classic and transformer models, indicate that performance surpasses the majority baseline (e.g., 25% absolute improvement for fine-grained labels). We believe that such models can assist in moderating social media posts even before they are published.</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Artificial Intelligence<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/frai.2023.1219767" target="_blank">https://dx.doi.org/10.3389/frai.2023.1219767</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_d9d0f39acf24a1d64e6da06f38e42c66 |
| identifier_str_mv | 10.3389/frai.2023.1219767 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/26535508 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Detecting and identifying the reasons for deleted tweets before they are postedHamdy Mubarak (19365502)Samir Abdaljalil (11513178)Azza Nassar (19365505)Firoj Alam (14158866)Information and computing sciencesArtificial intelligenceHuman-centred computingdisinformationdeleted tweetshate-speechArabicsocial media<p dir="ltr">Social media platforms empower us in several ways, from information dissemination to consumption. While these platforms are useful in promoting citizen journalism, public awareness, etc., they have misuse potential. Malicious users use them to disseminate hate speech, offensive content, rumor, etc. to promote social and political agendas or to harm individuals, entities, and organizations. Oftentimes, general users unconsciously share information without verifying it or unintentionally post harmful messages. Some of such content often gets deleted either by the platform due to the violation of terms and policies or by users themselves for different reasons, e.g., regret. There is a wide range of studies in characterizing, understanding, and predicting deleted content. However, studies that aim to identify the fine-grained reasons (e.g., posts are offensive, hate speech, or no identifiable reason) behind deleted content are limited. In this study, we address an existing gap by identifying and categorizing deleted tweets, especially within the Arabic context. We label them based on fine-grained disinformation categories. We have curated a dataset of 40K tweets, annotated with both coarse and fine-grained labels. Following this, we designed models to predict the likelihood of tweets being deleted and to identify the potential reasons for their deletion. Our experiments, conducted using a variety of classic and transformer models, indicate that performance surpasses the majority baseline (e.g., 25% absolute improvement for fine-grained labels). We believe that such models can assist in moderating social media posts even before they are published.</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Artificial Intelligence<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/frai.2023.1219767" target="_blank">https://dx.doi.org/10.3389/frai.2023.1219767</a></p>2023-09-29T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3389/frai.2023.1219767https://figshare.com/articles/journal_contribution/Detecting_and_identifying_the_reasons_for_deleted_tweets_before_they_are_posted/26535508CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/265355082023-09-29T09:00:00Z |
| spellingShingle | Detecting and identifying the reasons for deleted tweets before they are posted Hamdy Mubarak (19365502) Information and computing sciences Artificial intelligence Human-centred computing disinformation deleted tweets hate-speech Arabic social media |
| status_str | publishedVersion |
| title | Detecting and identifying the reasons for deleted tweets before they are posted |
| title_full | Detecting and identifying the reasons for deleted tweets before they are posted |
| title_fullStr | Detecting and identifying the reasons for deleted tweets before they are posted |
| title_full_unstemmed | Detecting and identifying the reasons for deleted tweets before they are posted |
| title_short | Detecting and identifying the reasons for deleted tweets before they are posted |
| title_sort | Detecting and identifying the reasons for deleted tweets before they are posted |
| topic | Information and computing sciences Artificial intelligence Human-centred computing disinformation deleted tweets hate-speech Arabic social media |