From promotion to empathy: a content analysis of brand responses to social justice movements

Journal article


Dilshad, W., Sattar, U. and Ghaffar, A. 2025. From promotion to empathy: a content analysis of brand responses to social justice movements. Bulletin of Management Review . 2 (2), p. 440–453.
AuthorsDilshad, W., Sattar, U. and Ghaffar, A.
Abstract

These days, when people post a hashtag online, the expectation is that companies will join the conversation and take a stand. This study looks at how ten big global brands shaped their responses during three high-profile moments—the Black Lives Matter protests, the Stop Asian Hate rallies, and the surge of Gaza solidarity. Leaning on Framing Theory and Brand Authenticity Theory, the authors read through eighty-four public statements scattered across Twitter, Instagram, YouTube, and company press releases, noting patterns in the words used, the feelings stirred, and how honest the messages seemed. Four main frames popped up: Empathy & Action, Empathy Only, Solidarity Only, and Neutral Tone. Brands that mixed heartfelt language with specific promises-thats the Empathy & Action frame- scored the strongest trust from audiences. By contrast, blurbs that offered only symbols or kept a safe neutral tone felt shallow, triggering doubts and charges of performative activism. Platform also played a role; longer, detailed posts fit better on Twitter and in press releases, while image-first feeds demanded shorter, punchier lines. All of this drives home that talk must line up with real deeds if a brand wants to be seen as truly ethical, not just friendly in the moment. This research adds to the growing pile of articles about brand activism, realness, and online talk, giving marketers clear tips for balancing business goals, moral values, and the noisy conversation happening right now.

KeywordsBrand activism; content analysis; social justice; framing theory; brand authenticity; performative activism; digital marketing; corporate communication
Year2025
JournalBulletin of Management Review
Journal citation2 (2), p. 440–453
PublisherInnovative Education Research Institute
ISSN3006-2268
Web address (URL)https://bulletinofmanagement.com/index.php/Journal/article/view/165
Accepted author manuscript
File Access Level
Restricted
Publisher's version
License
File Access Level
Open
Output statusPublished
Publication dates
Online28 Jun 2025
Publication process dates
Accepted28 Jun 2025
Deposited11 Jul 2025
Permalink -

https://repository.derby.ac.uk/item/qyx7v/from-promotion-to-empathy-a-content-analysis-of-brand-responses-to-social-justice-movements

Download files


Publisher's version
  • 97
    total views
  • 29
    total downloads
  • 2
    views this month
  • 1
    downloads this month

Export as

Related outputs

A personality-informed candidate recommendation framework for recruitment using MBTI typology
Sattar, U. 2025. A personality-informed candidate recommendation framework for recruitment using MBTI typology. Information MDPI. 16 (10), pp. 1-21. https://doi.org/10.3390/info16100863
Artificial intelligence for enhanced quality assurance through advanced strategies and implementation in the software industry
Vivekananthan, J., Sattar, U. and Lackner, M. 2025. Artificial intelligence for enhanced quality assurance through advanced strategies and implementation in the software industry. Journal of Intelligent Systems. 34 (1), pp. 1-19. https://doi.org/10.1515/jisys-2024-0377
Adopting open-source SD-WAN: a comprehensive analysis of performance, cost, and security benefits over traditional WAN architectures
Arogundade, S. V., Sattar, U. and Khan, H. W. 2025. Adopting open-source SD-WAN: a comprehensive analysis of performance, cost, and security benefits over traditional WAN architectures. EAI Endorsed Transactions on Scalable Information Systems. 12 (4). https://doi.org/10.4108/eetsis.7217
Beyond polarity: forecasting consumer sentiment with aspect- and topic-conditioned time series models
Sattar, U., Hasan, R., Palaniappan, S., Mahmood, S. and Khan, H. W. 2025. Beyond polarity: forecasting consumer sentiment with aspect- and topic-conditioned time series models. Information. 16 (8), pp. 1-20. https://doi.org/10.3390/info16080670
Predicting product sales performance using various types of customer review data
Baskaran, J., Sattar, U. and Khan, H. W. 2025. Predicting product sales performance using various types of customer review data. EAI Endorsed Transactions on Scalable Information Systems. 12 (4), pp. 1-11. https://doi.org/10.4108/eetsis.7216
Enhancing supply chain management: a comparative study of machine learning techniques with cost–accuracy and esg-based evaluation for forecasting and risk mitigation
Sattar, U., Dattana, V., Hasan, R., Mahmood, S., Khan, H. W. and Hussain, S. 2025. Enhancing supply chain management: a comparative study of machine learning techniques with cost–accuracy and esg-based evaluation for forecasting and risk mitigation. Sustainability. 17 (13), pp. 1-45. https://doi.org/10.3390/su17135772
Exploring the impact of augmented reality on medical students’ intrinsic motivation: a three-dimensional analysis
Sattar, U., Khan, H. W., Ghaffar, A. and Raza, S. 2025. Exploring the impact of augmented reality on medical students’ intrinsic motivation: a three-dimensional analysis. Journal of Management & Social Science. 2 (2), pp. 257-276. https://doi.org/10.63075/dt4f4h66
Enhancing customer segmentation through factor analysis of mixed data (FAMD)-based approach using K-means and hierarchical clustering algorithms
Sattar, U., Ufeli, C. P., Hasan, R. and Mahmood, S. 2025. Enhancing customer segmentation through factor analysis of mixed data (FAMD)-based approach using K-means and hierarchical clustering algorithms. information. 16 (6), pp. 1-25. https://doi.org/10.3390/info16060441
Stroke detection in brain CT images using convolutional neural networks: model development, optimization and interpretability
Abdi, H., Sattar, U., Dattana, V., Hasan, R., Dattana, V. and Mahmood, S. 2025. Stroke detection in brain CT images using convolutional neural networks: model development, optimization and interpretability. Information. 16 (5), pp. 1-29. https://doi.org/10.3390/info16050345
Mitigating fuel station drive-offs using AI: YOLOv8 OCR and MOT history API for detecting fake and altered plates
Milinda, G., Sattar, U. and Hasan, R. 2025. Mitigating fuel station drive-offs using AI: YOLOv8 OCR and MOT history API for detecting fake and altered plates. Computers, Materials & Continua. 83 (3), pp. 4061-4084. https://doi.org/10.32604/cmc.2025.062826
A human-centered design framework for intuitive mobile AR in medical learning
Sattar, U., Khan, H., Hasan, R. and Hassan, A. 2025. A human-centered design framework for intuitive mobile AR in medical learning. UMT Education Review. 7 (2), p. 94–122. https://doi.org//10.32350/uer.72.05