Tweets for tots: using Twitter to promote a charity and its supporters
Bibliographic record
Abstract
Purpose Twitter provides an ideal channel for a non-profit organisation (NPO) to add value to its corporate partners by providing the ability to send tweets to its own network of followers. This research aims to examine the extent to which one NPO used Twitter for this purpose and discuss the implications. Design/methodology/approach The research examined tweets sent by a large US-based charitable organisation, Toys for Tots (T4T), across two Christmas periods. All tweets that mentioned or retweeted T4T’s corporate partners were analysed. Findings The findings show surprisingly limited mentions of partners by T4T, with many never mentioned, and markedly fewer mentions of partners in the second period. Separate analysis of partner tweets retweeted by T4T revealed that none was modified to add value for T4T and/or for the partner, and many were unrelated to T4T, raising a risk of alienating T4T’s followers. Research limitations/implications Only one NPO was examined, and the study focused on Twitter, with limited analysis of T4T’s Facebook posts. However, the relatively low, decreasing and largely indirect promotion of partners in T4T’s tweets suggests a lack of strategic use of Twitter by T4T. Practical implications Coupled with other research, the results show the need for this and other NPOs to more effectively use Twitter to reinforce partnerships with corporate partners. Originality/value The results demonstrate the failure of a major US charity to use Twitter to add value for its corporate partners. Even in the unlikely event that this NPO is an isolated case, the results show the need for NPOs and their corporate partners to work together to provide reciprocal benefits.
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How this classification was reachedexpand
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".