Exploring the role of social media in shaping sustainable consumer behavior: a qualitative study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines the impact of social media on environmental awareness, perceived environmental responsibility, and sustainable consumption aspirations among Tunisian consumers. Using a qualitative research design, semi-structured, in-depth interviews were conducted with 15 active social media users (students, professionals and retirees) who demonstrated an interest in sustainability-related content. The purposeful sampling approach ensured diversity in age, gender, and occupational backgrounds to capture varied perspectives. The findings reveal that social media plays a critical role in shaping sustainability awareness: Instagram drives aspirational consumption, Facebook fosters community engagement and YouTube serves as a key source of educational content. However, significant barriers—such as the high cost of sustainable products and limited community support—continue to hinder efforts to achieve behavioral change. Trustworthy information and community-driven initiatives on social media were identified as essential enablers of sustainable practices. This study contributes to the growing field of digital sustainability by offering platform-specific insights and practical recommendations for policymakers and marketers seeking to address socio-economic challenges. Future research should explore the long-term impact of social media–based sustainability efforts and examine the role of emerging platforms like TikTok in advancing sustainability advocacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it