The lure of decentralized social media: Extending the UTAUT model for understanding users’ adoption of blockchain-based social media
Bibliographic record
Abstract
The study uses 31 semi-structured interviews to explore users' motivations for adopting and using blockchain-based social media (BSM) platforms. The objective of the study is twofold-to collect empirical data on early adopters of BSM and to test the applicability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model for explaining why some users are choosing BSM over mainstream social media (MSM) platforms. Manual content analysis of the interviews reveals that users are initially drawn to BSM due to social influence and financial incentives, but they continue to use it mainly because of the sense of community they experience. We also find that the steep learning curve, the absence of content moderation, as well as security and privacy concerns hinder the widespread adoption of these platforms. From the theoretical side, although the UTAUT model is generally suitable for examining why individuals use BSM, we suggest integrating two additional factors into the model: financial incentives and content moderation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".