BibTex Citation Data :
@article{DJA59461, author = {Ida Maulidya and Dwi Cahyo Utomo}, title = {PENGARUH GERAKAN BOIKOT DI MEDIA SOSIAL X TERHADAP KINERJA KEUANGAN PERUSAHAAN YANG MENJADI TARGET BOIKOT DI INDONESIA}, journal = {Diponegoro Journal of Accounting}, volume = {15}, number = {2}, year = {2026}, keywords = {boycott movement, conversation volume, negative sentiment, financial performance}, abstract = { This study examines the effect of boycott-related activities on social media platform X on the financial performance of companies targeted by the Boycott, Divestment, and Sanctions (BDS) movement and listed on the Indonesia Stock Exchange during 2021–2025. The growing use of social media has increased public participation in boycott campaigns and may influence corporate performance. A quantitative approach with panel data regression was employed using a sample of eight companies selected through purposive sampling. Conversation volume and negative sentiment were obtained from platform X through web scraping and classified using the Support Vector Machine (SVM) algorithm. Financial performance was measured by revenue growth and net profit margin. The findings show that neither conversation volume nor negative sentiment significantly affects revenue growth or net profit margin. These results indicate that boycott-related discussions on platform X were not significantly associated with the financial performance of the sampled companies. The study contributes to the literature on digital activism and corporate financial performance. }, issn = {2337-3806}, url = {https://ejournal3.undip.ac.id/index.php/accounting/article/view/59461} }
Refworks Citation Data :
This study examines the effect of boycott-related activities on social media platform X on the financial performance of companies targeted by the Boycott, Divestment, and Sanctions (BDS) movement and listed on the Indonesia Stock Exchange during 2021–2025. The growing use of social media has increased public participation in boycott campaigns and may influence corporate performance.
A quantitative approach with panel data regression was employed using a sample of eight companies selected through purposive sampling. Conversation volume and negative sentiment were obtained from platform X through web scraping and classified using the Support Vector Machine (SVM) algorithm. Financial performance was measured by revenue growth and net profit margin.
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Program Studi AkuntansiFakultas Ekonomika dan BisnisUniversitas DiponegoroJl. Prof. Sudharto, SH – Tembalang, Semarang Jawa Tengah 50275
ISSN : 2337-3806