Social Media and domestic violence against women; Hashtag analysis and reaction of Instagram users to the murder of Romina Ashrafi
Social Media sites are now the main sphere for expressing emotions as well as being affected by news and social issues. Therefore, understanding the nature of this sphere is the root to understand user behavior and the role of cyberspace. In the current study, Instagram was selected, as the most imp...
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| Format: | Article |
| Language: | fas |
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Allameh Tabataba'i University Press
2021-12-01
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| Series: | مطالعات رسانههای نوین |
| Subjects: | |
| Online Access: | https://nms.atu.ac.ir/article_13929_c061eed284d5561b7743bd49c3f0b249.pdf |
| _version_ | 1797392767378259968 |
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| author | Amir Hossein Alemi seyed nooredin razavizadeh |
| author_facet | Amir Hossein Alemi seyed nooredin razavizadeh |
| author_sort | Amir Hossein Alemi |
| collection | DOAJ |
| description | Social Media sites are now the main sphere for expressing emotions as well as being affected by news and social issues. Therefore, understanding the nature of this sphere is the root to understand user behavior and the role of cyberspace. In the current study, Instagram was selected, as the most important social media platform among Persian-speaking users (in terms of volume of users), to examine the domestic violence against women as an important social topic that has affected public opinion in recent years. In the current study, the subject of honor killing (murder of Romina Ashrafi) is assessed as one of the most acute forms of domestic violence.Through analyzing the Rumina_Ashrafi hashtag on Instagram, most of the content posted in this social media related to the incident was extracted. Out of 45,800 posts, 33,740 posts were sampled based on the most visits and the highest engagements. Then the content production timeline on Instagram was extracted and the posted content was also categorize using similar hashtags. In addition, during the study, the top posts, the most visited and most participated contents as well as the participating users were identified. Finally, with the netnographic method, the comments of the most visited posts were analyzed and categorized. This study tries to answer what kind of approach and behavior is more likely to be expressed by the social media users in the face of such incidents. |
| first_indexed | 2024-03-08T23:52:18Z |
| format | Article |
| id | doaj.art-f1ce90ffb4cd4709a275f67804657e79 |
| institution | Directory Open Access Journal |
| issn | 2538-2209 2476-6550 |
| language | fas |
| last_indexed | 2024-03-08T23:52:18Z |
| publishDate | 2021-12-01 |
| publisher | Allameh Tabataba'i University Press |
| record_format | Article |
| series | مطالعات رسانههای نوین |
| spelling | doaj.art-f1ce90ffb4cd4709a275f67804657e792023-12-13T10:28:23ZfasAllameh Tabataba'i University Pressمطالعات رسانههای نوین2538-22092476-65502021-12-01728784310.22054/nms.2022.62839.126113929Social Media and domestic violence against women; Hashtag analysis and reaction of Instagram users to the murder of Romina AshrafiAmir Hossein Alemi0seyed nooredin razavizadeh1Communication and Journalism faculty, ATU, Tehran, iranFaculty member of the Faculty of Communication, Allameh Tabatabai University, Tehran, IranSocial Media sites are now the main sphere for expressing emotions as well as being affected by news and social issues. Therefore, understanding the nature of this sphere is the root to understand user behavior and the role of cyberspace. In the current study, Instagram was selected, as the most important social media platform among Persian-speaking users (in terms of volume of users), to examine the domestic violence against women as an important social topic that has affected public opinion in recent years. In the current study, the subject of honor killing (murder of Romina Ashrafi) is assessed as one of the most acute forms of domestic violence.Through analyzing the Rumina_Ashrafi hashtag on Instagram, most of the content posted in this social media related to the incident was extracted. Out of 45,800 posts, 33,740 posts were sampled based on the most visits and the highest engagements. Then the content production timeline on Instagram was extracted and the posted content was also categorize using similar hashtags. In addition, during the study, the top posts, the most visited and most participated contents as well as the participating users were identified. Finally, with the netnographic method, the comments of the most visited posts were analyzed and categorized. This study tries to answer what kind of approach and behavior is more likely to be expressed by the social media users in the face of such incidents.https://nms.atu.ac.ir/article_13929_c061eed284d5561b7743bd49c3f0b249.pdfdomestic violencehashtag analysissocial networksinstagram |
| spellingShingle | Amir Hossein Alemi seyed nooredin razavizadeh Social Media and domestic violence against women; Hashtag analysis and reaction of Instagram users to the murder of Romina Ashrafi مطالعات رسانههای نوین domestic violence hashtag analysis social networks |
| title | Social Media and domestic violence against women;
Hashtag analysis and reaction of Instagram users to the murder of Romina Ashrafi |
| title_full | Social Media and domestic violence against women;
Hashtag analysis and reaction of Instagram users to the murder of Romina Ashrafi |
| title_fullStr | Social Media and domestic violence against women;
Hashtag analysis and reaction of Instagram users to the murder of Romina Ashrafi |
| title_full_unstemmed | Social Media and domestic violence against women;
Hashtag analysis and reaction of Instagram users to the murder of Romina Ashrafi |
| title_short | Social Media and domestic violence against women;
Hashtag analysis and reaction of Instagram users to the murder of Romina Ashrafi |
| title_sort | social media and domestic violence against women hashtag analysis and reaction of instagram users to the murder of romina ashrafi |
| topic | domestic violence hashtag analysis social networks |
| url | https://nms.atu.ac.ir/article_13929_c061eed284d5561b7743bd49c3f0b249.pdf |
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