Machine Learning Techniques for Identifying Textual Propaganda on Social Media: Development of a Detecting Digital Manipulation System
The dissemination of propaganda on social media presents a significant challenge in today’s digital age. Utilizing advanced tools and diverse methods, propaganda aims to influence public opinion on a massive scale. Social media platforms serve as prime channels for such messages, leveraging sophist...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Institute of Technology and Education Galileo da Amazônia
2025-05-01
|
| Series: | ITEGAM-JETIA |
| Online Access: | http://br940.teste.website/~itegamjetia/journal/index.php/jetia/article/view/1443 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849761626240057344 |
|---|---|
| author | Belkacem Mostefai Tarek Boutefara Abid Chahinez Marwa Aberkane |
| author_facet | Belkacem Mostefai Tarek Boutefara Abid Chahinez Marwa Aberkane |
| author_sort | Belkacem Mostefai |
| collection | DOAJ |
| description |
The dissemination of propaganda on social media presents a significant challenge in today’s digital age. Utilizing advanced tools and diverse methods, propaganda aims to influence public opinion on a massive scale. Social media platforms serve as prime channels for such messages, leveraging sophisticated strategies to shape public perceptions and attitudes. This research aims to develop an advanced system capable of evaluating whether the content disseminated on these platforms qualifies as propaganda. The hypothesis suggests that it is possible to distinguish propaganda from non-propaganda texts on social media by analyzing specific linguistic features. Employing advanced linguistic analysis and machine learning methods, this detection system achieves approximately 70% accuracy, indicating its promising potential for effectively identifying propaganda. This approach could significantly enhance the transparency and reliability of online information, encouraging a more informed and critical use of social media.
Keywords: Propaganda Detection, Social media, Machine Learning Techniques, Linguistic Analysis, Digital manipulation,
|
| format | Article |
| id | doaj-art-a6fb7586758e4df4868f0fe258fd7c19 |
| institution | DOAJ |
| issn | 2447-0228 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Institute of Technology and Education Galileo da Amazônia |
| record_format | Article |
| series | ITEGAM-JETIA |
| spelling | doaj-art-a6fb7586758e4df4868f0fe258fd7c192025-08-20T03:05:57ZengInstitute of Technology and Education Galileo da AmazôniaITEGAM-JETIA2447-02282025-05-01115310.5935/jetia.v11i53.1443Machine Learning Techniques for Identifying Textual Propaganda on Social Media: Development of a Detecting Digital Manipulation SystemBelkacem Mostefai0Tarek Boutefara1Abid Chahinez2Marwa Aberkane3Computer Science Department, University of DjelfaFaculty of Exact Sciences and Computer Sciences, University of Jijel,18000 DZ Jijel, AlgeriaFaculty of Exact Sciences and Computer Sciences, University of Jijel,18000 DZ Jijel, AlgeriaFaculty of Exact Sciences and Computer Sciences, University of Jijel,18000 DZ Jijel, Algeria The dissemination of propaganda on social media presents a significant challenge in today’s digital age. Utilizing advanced tools and diverse methods, propaganda aims to influence public opinion on a massive scale. Social media platforms serve as prime channels for such messages, leveraging sophisticated strategies to shape public perceptions and attitudes. This research aims to develop an advanced system capable of evaluating whether the content disseminated on these platforms qualifies as propaganda. The hypothesis suggests that it is possible to distinguish propaganda from non-propaganda texts on social media by analyzing specific linguistic features. Employing advanced linguistic analysis and machine learning methods, this detection system achieves approximately 70% accuracy, indicating its promising potential for effectively identifying propaganda. This approach could significantly enhance the transparency and reliability of online information, encouraging a more informed and critical use of social media. Keywords: Propaganda Detection, Social media, Machine Learning Techniques, Linguistic Analysis, Digital manipulation, http://br940.teste.website/~itegamjetia/journal/index.php/jetia/article/view/1443 |
| spellingShingle | Belkacem Mostefai Tarek Boutefara Abid Chahinez Marwa Aberkane Machine Learning Techniques for Identifying Textual Propaganda on Social Media: Development of a Detecting Digital Manipulation System ITEGAM-JETIA |
| title | Machine Learning Techniques for Identifying Textual Propaganda on Social Media: Development of a Detecting Digital Manipulation System |
| title_full | Machine Learning Techniques for Identifying Textual Propaganda on Social Media: Development of a Detecting Digital Manipulation System |
| title_fullStr | Machine Learning Techniques for Identifying Textual Propaganda on Social Media: Development of a Detecting Digital Manipulation System |
| title_full_unstemmed | Machine Learning Techniques for Identifying Textual Propaganda on Social Media: Development of a Detecting Digital Manipulation System |
| title_short | Machine Learning Techniques for Identifying Textual Propaganda on Social Media: Development of a Detecting Digital Manipulation System |
| title_sort | machine learning techniques for identifying textual propaganda on social media development of a detecting digital manipulation system |
| url | http://br940.teste.website/~itegamjetia/journal/index.php/jetia/article/view/1443 |
| work_keys_str_mv | AT belkacemmostefai machinelearningtechniquesforidentifyingtextualpropagandaonsocialmediadevelopmentofadetectingdigitalmanipulationsystem AT tarekboutefara machinelearningtechniquesforidentifyingtextualpropagandaonsocialmediadevelopmentofadetectingdigitalmanipulationsystem AT abidchahinez machinelearningtechniquesforidentifyingtextualpropagandaonsocialmediadevelopmentofadetectingdigitalmanipulationsystem AT marwaaberkane machinelearningtechniquesforidentifyingtextualpropagandaonsocialmediadevelopmentofadetectingdigitalmanipulationsystem |