Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu
<p dir="ltr">In today’s digital era, the escalating phenomenon of cyberbullying is a pervasive and growing concern. With the increasing prevalence of social media platforms, such as Twitter, online abusive behavior has become a significant issue that often leads to unpleasant experie...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | , , , , , |
| منشور في: |
2024
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
| _version_ | 1864513540955570176 |
|---|---|
| author | Ayesha Atif (22155133) |
| author2 | Amna Zafar (12369151) Muhammad Wasim (8319120) Talha Waheed (22155136) Amjad Ali (51075) Hazrat Ali (421019) Zubair Shah (231886) |
| author2_role | author author author author author author |
| author_facet | Ayesha Atif (22155133) Amna Zafar (12369151) Muhammad Wasim (8319120) Talha Waheed (22155136) Amjad Ali (51075) Hazrat Ali (421019) Zubair Shah (231886) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ayesha Atif (22155133) Amna Zafar (12369151) Muhammad Wasim (8319120) Talha Waheed (22155136) Amjad Ali (51075) Hazrat Ali (421019) Zubair Shah (231886) |
| dc.date.none.fl_str_mv | 2024-09-11T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2024.3445288 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Cyberbullying_Detection_and_Abuser_Profile_Identification_on_Social_Media_for_Roman_Urdu/30023257 |
| 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 Cybersecurity and privacy Human-centred computing Machine learning Cyberbullying detection social media Roman Urdu machine learning deep learning abuser profile identification Cyberbullying Hate speech Blogs Support vector machines Feature extraction Deep learning Data models Detection algorithms Social networking (online) Machine learning Identification of persons |
| dc.title.none.fl_str_mv | Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">In today’s digital era, the escalating phenomenon of cyberbullying is a pervasive and growing concern. With the increasing prevalence of social media platforms, such as Twitter, online abusive behavior has become a significant issue that often leads to unpleasant experiences for users. Manual detection of abnormal and bullying behavior within the realm of social media is inherently not scalable. Moreover, most existing studies on cyberbullying detection have been predominantly conducted in English and very limited work has been done on Urdu (a widely used language in Asia). This paper presents an approach for detecting cyberbullying in Roman Urdu tweets and identifying abuser profiles on Twitter. Firstly, we develop a text corpus of Roman Urdu tweets with user profile data. Subsequently, we employ Gated Recurrent Unit (GRU) model coupled with the application of word2vec technique for word embedding to develop a cyberbullying detection model. Furthermore, we present temporal abusive tweet probability analysis method to provide a nuanced analysis of the number of bullying and non-bullying tweets sent by individuals within a specific time interval. To evaluate the performance, we compare the GRU-based approach with other machine learning models. The results show that the GRU model with lexical normalization gives the best results with an accuracy of 97% and F1-measure of 97%.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2024.3445288" target="_blank">https://dx.doi.org/10.1109/access.2024.3445288</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_a6bb9e30e45acf98984b50a960b11ed4 |
| identifier_str_mv | 10.1109/access.2024.3445288 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/30023257 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman UrduAyesha Atif (22155133)Amna Zafar (12369151)Muhammad Wasim (8319120)Talha Waheed (22155136)Amjad Ali (51075)Hazrat Ali (421019)Zubair Shah (231886)Information and computing sciencesArtificial intelligenceCybersecurity and privacyHuman-centred computingMachine learningCyberbullying detectionsocial mediaRoman Urdumachine learningdeep learningabuser profile identificationCyberbullyingHate speechBlogsSupport vector machinesFeature extractionDeep learningData modelsDetection algorithmsSocial networking (online)Machine learningIdentification of persons<p dir="ltr">In today’s digital era, the escalating phenomenon of cyberbullying is a pervasive and growing concern. With the increasing prevalence of social media platforms, such as Twitter, online abusive behavior has become a significant issue that often leads to unpleasant experiences for users. Manual detection of abnormal and bullying behavior within the realm of social media is inherently not scalable. Moreover, most existing studies on cyberbullying detection have been predominantly conducted in English and very limited work has been done on Urdu (a widely used language in Asia). This paper presents an approach for detecting cyberbullying in Roman Urdu tweets and identifying abuser profiles on Twitter. Firstly, we develop a text corpus of Roman Urdu tweets with user profile data. Subsequently, we employ Gated Recurrent Unit (GRU) model coupled with the application of word2vec technique for word embedding to develop a cyberbullying detection model. Furthermore, we present temporal abusive tweet probability analysis method to provide a nuanced analysis of the number of bullying and non-bullying tweets sent by individuals within a specific time interval. To evaluate the performance, we compare the GRU-based approach with other machine learning models. The results show that the GRU model with lexical normalization gives the best results with an accuracy of 97% and F1-measure of 97%.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2024.3445288" target="_blank">https://dx.doi.org/10.1109/access.2024.3445288</a></p>2024-09-11T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2024.3445288https://figshare.com/articles/journal_contribution/Cyberbullying_Detection_and_Abuser_Profile_Identification_on_Social_Media_for_Roman_Urdu/30023257CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/300232572024-09-11T09:00:00Z |
| spellingShingle | Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu Ayesha Atif (22155133) Information and computing sciences Artificial intelligence Cybersecurity and privacy Human-centred computing Machine learning Cyberbullying detection social media Roman Urdu machine learning deep learning abuser profile identification Cyberbullying Hate speech Blogs Support vector machines Feature extraction Deep learning Data models Detection algorithms Social networking (online) Machine learning Identification of persons |
| status_str | publishedVersion |
| title | Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu |
| title_full | Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu |
| title_fullStr | Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu |
| title_full_unstemmed | Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu |
| title_short | Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu |
| title_sort | Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu |
| topic | Information and computing sciences Artificial intelligence Cybersecurity and privacy Human-centred computing Machine learning Cyberbullying detection social media Roman Urdu machine learning deep learning abuser profile identification Cyberbullying Hate speech Blogs Support vector machines Feature extraction Deep learning Data models Detection algorithms Social networking (online) Machine learning Identification of persons |